Mapping Market Access Barriers
for Food and Drink Exports
Final report prepared for Defra
16th May 2013
(Project Code: DO 0126)
Stephen Rigby
Partner, Performance Improvement
T
+44 (0)207 865 2101
E
[email protected]
Ioana Nobel
Associate Director, Strategy and Commercial Advisory
T
+44 (0)207 865 2142
E
[email protected]
Vangelis Apostolidis
Assistant Manager, Strategy and Commercial Advisory
T
+44 (0)207 865 2535
E
[email protected]
Grant Thornton report commissioned by the Department for
Environment, Food and Rural Affairs
Contents
Glossary
3
Executive summary
6
Introduction
9
Chapter 1.
Literature review
11
Section 1.1.
Section 1.2.
Section 1.3.
Section 1.4.
Section 1.5.
Introduction and scope
Benefits of free trade
Trade barriers definition and types
Market failure
Evidence at a global or European level of the benefits of removing trade
barriers
Quantifying the effect of trade barriers
Trade barriers/Market access databases
11
12
15
22
Section 1.6.
Section 1.7.
Chapter 2.
25
33
37
Longlist of target export countries, agri-food products
where the UK has a comparative advantage and trade
barrier mapping
40
Section 2.1.
Section 2.2.
Section 2.3.
Section 2.4.
Section 2.5.
Introduction and scope
Identification of longlist of target countries
Identification of longlist of key product categories
Non-Tariff Measures (NTMs) analysis
Tariff analysis
40
41
51
59
61
Chapter 3.
Address any evidence gaps in the longlist of
countries, products and barriers through primary
research
63
Section 3.1.
Section 3.2.
Section 3.3.
Introduction and scope
Methodology and primary research sample
Key findings from interviews
63
64
67
Chapter 4.
Areas for Government support based on primary
research outputs
85
Section 4.1.
Section 4.2.
Section 4.3.
Introduction and scope
Business interviews output
Policymakers/industry associations interview output
85
86
89
Chapter 5.
Case studies
91
Section 5.1.
Section 5.2.
Introduction and scope
Case studies
91
92
Chapter 6.
Shortlisting target countries and products
95
Section 6.1.
Section 6.2.
Section 6.3.
Section 6.4.
Section 6.5.
Introduction and scope
Methodology overview
Step 1 of the analysis
Step 2 of the analysis
Step 3 of the analysis
95
96
97
103
106
© 2013 Grant Thornton UK LLP. All rights reserved.
1
Chapter 7.
Section 7.1.
Section 7.2.
Section 7.3.
Section 7.4.
Forecasting the export opportunity for the selected
UK products
113
Introduction and scope
Literature review
Methodology followed and common themes in the analysis of all
products
Regression analysis and forecasting outputs
113
114
116
120
Conclusion
128
Appendix
131
A.
B.
C.
D.
E.
F.
Estimating the value of UK chicken meat exports to China
Estimating the value of UK sheep meat exports to China
Estimating the value of UK crustaceans exports to USA
Estimating the value of UK chocolate exports to Mexico
Estimating the value of UK bakers' wares and biscuits exports to Mexico
Estimating the value of UK beef to Japan
131
142
151
161
169
179
Bibliography
190
Important Notice
194
2
© 2013 Grant Thornton UK LLP. All rights reserved.
Glossary
$/Dollar
Refers to US Dollars
unless otherwise stated
CPI
Consumer Price
Index
€
Euro
DEFRA
Department for
Environment, Food
and Rural Affairs
AMA and NAMA
Agricultural MarketAccess and NonAgricultural Market
Access
DG Sanco
Directorate General
For Health &
Consumers
AQSIQ
China‟s Administration DH
of Quality Supervision,
Inspection and
Quarantine
Department for
Health
BIS
Department for
DOLS
Business, Innovation &
Skills
Dynamic Ordinary
Least Squares
bn
billions
European Free
Trade Association
BRIC
Grouping acronym
EIU
referring to Brazil,
Russia, India and China
Economist
Intelligence Unit
BSE
Bovine Spongiform
Encephalopathy
EPA
Economic
Partnership
Agreement
CAD
Canadian Dollar
EU
European Union
CAGR
Compound Annual
Growth Rate
EUR
Euro
CBA
Cost Benefit Analysis
FAO
Food and
Agriculture
Organisation
CEPII
Centre d'Etudes
Prospectives et
d'Informations
Internationales
FAPRI
Food and
Agricultural Policy
Research Institute
(FAPRI)
© 2013 Grant Thornton UK LLP. All rights reserved.
EFTA
3
FCBs
Farmer Controlled
Businesses
FCO
Foreign and
IPFSAPH
Commonwealth Office
Animal Plant
Health
FDA
Food and Drug
Administration
ITC
International Trade
Centre
FGLS
Feasible Generalized
Least Squares
k
thousands
FTA
Free Trade Agreement
m
millions
G-20
Group of 20
MADB
Market Access
Database
GATT
General Agreement on
Tariffs and Trade
MEP
Member of the
European
Parliament
GBP
British Pound Sterling
MXN
Mexican Peso
GDP
Gross Domestic
Product
NAFTA
North American
Free Trade
Agreement
GI
Geographic
Identification
NES
Not Elsewhere
Specified
GMM
Generalised Method of NTE
Moments
National Trade
Estimate
GMO
Genetically Modified
Organism
NTE
National Trade
Estimate Report on
Foreign Trade
HS
Harmonized System
NTM
Non-Tariff
Measures
ICC
International Chamber
of Commerce
OECD
Organisation of
Economic
Cooperation and
Development
IGD
Institute of Grocery
Distribution
OLS
Ordinary Least
Squares
4
IP
Intellectual
Property
© 2013 Grant Thornton UK LLP. All rights reserved.
PCSE
Panels corrected
standard errors
UNSD
the United Nations
Statistical Division
RCA
Revealed Comparative
Advantage
US/USA
United States of
America
RMB
Chinese Renminbi
USD
US Dollar
SERIO
Specialist Social
USDA
Economic Market
Research of the
University of Plymouth
United States
Department of
Agriculture
SME
Small and Medium
Sized Enterprise
USMCOC
US-Mexico
Chamber of
Commerce
SPS
Sanitary and
Phytosanitary
USTR
The United States
Trade
Representative
STC
Specific Trade
Concerns
USTR
US Trade
Representative
TBT
Technical Barriers to
Trade
VEC
Vector error
correction
TED
Turtle Excluder Device VER
Voluntary Export
Restraints
TPR
Trade Policy Reviews
World Integrated
Trade Solution
TRAINS
The Trade Analysis and WTO
Information System
World Trade
Organisation
UKTI
UK Trade &
Investment
United Nations
Conference on
Trade and
Development
UNCTAD
United Nations
Conference on Trade
and Development
© 2013 Grant Thornton UK LLP. All rights reserved.
WITS
UNCTAD
5
Executive summary
Market access barriers, which have historically taken the form of tariffs and taxes,
represent a significant obstacle to export growth. International efforts to remove them
have been on-going for over 50 years; starting with the General Agreement on Tariffs and
Trade and followed by the rounds of international trade negotiations under the umbrella of
the World Trade Organisation (WTO). However, the current trade policy challenge is
primarily overcoming non-tariff barriers, which can take many forms (e.g. labelling rules,
poor protection of intellectual property and of products with a controlled designation of
origin, the misuse of sanitary and phytosanitary measures as well as unfair subsidies). In
this context, the Department for Environment, Food and Rural Affairs (Defra) proposed
to investigate market access barriers, a key inhibitor to UK export growth and
commissioned this study to gather evidence and understand where removing trade barriers
can unlock the
greatest opportunities.
Defra commissioned Grant Thornton to identify key market access barriers for UK food
and drink exports and to investigate the following issues:

Establish where the most significant barriers are;

Map these against the ease with which and the time line in which the barriers can
be addressed;

Estimate the overall opportunity presented;

Identify how to best align and take advantage of export support services; and

Identify where effort from Government and industry should be focused to achieve the
greatest potential gain from reducing trade barriers.
The project's scope excluded EU nations, given that Defra's focus is on identifying trade
barriers and unlocking exports outside the EU, where a lot of opportunities but also
barriers are still in place for UK exports.
The project comprised of four phases:
1. A detailed programme of literature and data review aimed at synthesising the body of
knowledge on market access barriers in general, and for the agri-food and drink sector
in particular;
2. A structured detailed interview programme with businesses, trade bodies and policy
makers to bridge the knowledge gaps from the literature review and explore the
interviewees' experience regarding the incidence of market access barriers and
support structures;
3. A comprehensive, quantitative analysis to identify the most appropriate opportunities
in terms of target export markets, product categories and the associated market access
barriers. The first step was to collate a longlist of 30 target countries and 20 product
categories based on analysing a wide range of macro-economic and trade parameters
from desktop sources. The second step involved designing a 'logic tree' which filtered
the potential 600 opportunities down to 118 by considering the openness of the
specific market in question, its market size and growth prospects. Then, by factoring in
primary research evidence and additional desktop research, the opportunities were
reduced to a shortlist of 56, across 7 countries and 11 product categories; and
6
© 2013 Grant Thornton UK LLP. All rights reserved.
4. This work was followed by the quantification of six of the opportunities shortlisted
above to estimate the potential economic value of UK exports if the relevant trade
barriers were removed. The import-demand equation was chosen in order to explain
the behaviour of imports to the target market and assist with forecasting the potential
opportunity for UK exports through regression analyses. Forecasts were made under
three different scenarios and in each case the assumptions made are clearly outlined.
This involved investigating the target market and product of interest at a micro-level
and collecting data on a wide range of parameters (e.g. trade statistics, market size,
pricing, trade barriers, etc.).
The key output of this project is the robust methodology established that allows the
identification of opportunities where high barriers may be in place and the evaluation of
the potential economic value associated with them. More specifically, the application of the
methodology has produced the following key findings:
Primary research findings on trade barriers and export opportunities

The companies interviewed identified 32 countries as target markets in the short to
medium term time horizon; USA, China, Australia, Canada, Russia and Japan were
most frequently quoted by interviewees; and

The companies and associations interviewed identified a total of 157 barriers, of which
14% were tariff barriers and 86% were non-tariff barriers. Technical Barriers to Trade
(TBT) and Sanitary and Phytosanitary barriers (SPS) appeared to be the most prevalent
non-tariff barriers that companies in the sample faced when exporting, followed by
complex registration/documentation procedures and customs procedures. Not all of
these barriers were deemed to be prohibitive and a sample of six case studies has been
included in the report that showcases initiatives and strategies used by UK businesses
to overcome trade barriers and grow their export revenues.
Longlist of target export countries (30 countries) and agri-food products
(20 products)

Outside the EU, opportunities still exist in mature developed economies (e.g. USA,
Japan, Australia, Canada). However, the majority of opportunities lie with emerging
markets and primarily the BRICs, but also, further afield, in countries like Thailand,
Algeria, Paraguay and others. These markets were selected by accounting for a range of
macroeconomic indicators (e.g. population, GDP, gini coefficient) and trade statistics
(e.g. EU & UK exports, food imports); and

In terms of the product categories where the UK is well positioned to compete
globally, this project has identified 20 product categories (at the 4-code HS level), 10 of
which are highly processed (e.g. spirits, biscuits, chocolate, breakfast cereals, etc), 8 are
lightly processed (e.g. soft drinks, beef meat, tea, cheese, etc) and 2 are unprocessed
(e.g. fish). All of these 20 products have high Relative Comparative Advantage (RCA)
scores (i.e. the UK appears to have a relative advantage in trade for these products), are
currently heavily exported by the UK and are heavily in demand as measured by world
import statistics.
Shortlisting target countries and products (118 opportunities in total)

Having separately identified target markets for UK exports and UK product categories
with global export potential, this exercise aimed to address the specific opportunities in
each target country for each product. This step identified Brazil, China, Mexico and
Russia as the countries with most potential opportunities across the widest range of
products. Amongst developed markets, USA and Japan involved the most
opportunities. The product categories which presented the most opportunities across
© 2013 Grant Thornton UK LLP. All rights reserved.
7
countries were meat products, seafood, tea, chocolate products and breads & biscuits;
and

These 118 opportunities were further filtered qualitatively and quantitatively to help
select the six opportunities, whose potential economic value would next be evaluated.
The final six product/country combinations selected represent significant
opportunities that were carefully selected based on a rigorous approach, but the
remaining 112 should not be disregarded.
Forecasting the export opportunity for the selected (six) UK products

The potential opportunity behind removing the trade barriers associated with the six
final product/country combinations was then estimated. As per the base case scenario
in each case, the potential annualised economic opportunity for UK exports in the
medium term was:
 Chicken meat to China: £40.3m;
 Sheep meat to China: £5.5m;
 Crustaceans to USA: £10.8m;
 Chocolate to Mexico: £9.5m;
 Breads & biscuits to Mexico: £5.5m; and
 Beef meat to Japan: £11.8m.
Sensitivity cases around these estimates are provided in the main body of the report.
The long and shortlists derived in the steps above provide a representation of potential UK
export opportunities, yet where there are barriers in the way of realising those
opportunities, based on the quantitative and qualitative analysis undertaken. There may
well be strong export opportunities elsewhere, but where there are not significant trade
barriers in place preventing the potential being realised – this study is not considering such
opportunities. It is also important not to focus solely on the six opportunities shortlisted
and evaluated in Chapter 7, as many other opportunities considered may provide
significant scope for export.
The outcomes of the study rely on the very detailed analysis that has been carried out, but
importantly are also backed up by interviews and engagement with industry. The study was
commissioned with practical objectives in mind. Going forward, Defra will be able to use
this robust methodology, with further industry input, to identify and explore opportunities,
and to understand where the Government could focus its resources and efforts in breaking
down barriers.
8
© 2013 Grant Thornton UK LLP. All rights reserved.
Introduction
Project objectives and scope
The Department for Environment, Food and Rural Affairs (Defra) commissioned Grant
Thornton to identify key market access barriers for UK food and drink exports and to
investigate the following issues:

Establish where the most significant barriers are;

Map these against the ease with which and the time line in which the barriers can be
addressed;

Estimate the overall opportunity presented;

Identify how to best align and take advantage of export support services; and

Identify where effort from Government and industry should be focused to achieve the
greatest potential gain from reducing them.
In collaboration with Defra, the project scope has been further refined as follows:

The engagement had a medium-term horizon, meaning that it would shortlist and
evaluate opportunities by accounting for a 3-5 year timeframe in removing trade
barriers and unlocking growth;

The outputs presented in the following chapters concern areas for which there are
sizeable opportunities (as measured by market size and growth prospects) and for
which significant trade barriers are already in place as well (as measured by tariffs or
non-tariff measures). If a product has not been shortlisted, it does not mean that it
does not present strong export opportunity, but rather that high trade barriers may not
be in place, that the UK or other European countries have successfully exported the
product to the target country and therefore Government support may not be essential
to unlock its growth potential;

The project scope excluded Whisky, which is already the most successful UK food and
drink export. The Scottish Whisky Association has opened markets for its members;
this being an example of how industry action can overcome trade barriers. Defra is of
course keen to protect the Scotch Whisky brand, ensuring its authenticity is protected
through the European legislation of Geographic Identification (GI). In addition, the
project's scope excluded European nations (except for non-EU Eastern European
nations), given that Defra's focus is on identifying trade barriers and unlocking exports
outside the EU; and

The scope of work did not include testing the outputs from Chapters 2 and 6 (longlists
and shortlists of target countries and products where the UK has a 'competitive
advantage' and for which there is sufficient demand abroad) with retailers, distributors
or consumers in target countries. However, the comprehensive desktop research
conducted and the varied data collected should provide a good proxy for the
opportunities and barriers in place.
© 2013 Grant Thornton UK LLP. All rights reserved.
9
Report structure
The report has been structured to clearly address the key issues and objectives agreed with
Defra. The report is organised in the following seven chapters:

Chapter 1- Literature review: covers a wide range of academic studies and reports
published by international organisations in the field of trade economics, market access
barriers and the quantification of the barriers' impact on trade;

Chapter 2- Longlist of target export countries, agri-food products where the UK
has a comparative advantage and trade barrier mapping: following extensive data
collection and analysis, provides a longlist of 30 countries the UK food and drink
industry may target and 20 product categories where the UK appears to have a
competitive advantage on a global scale. In addition, the chapter provides an overview
of tariffs and non-tariff measures (NTMs) these countries impose on the UK across
the identified products;

Chapter 3- Addressing any evidence gaps in the longlist of countries, products
and barriers through primary research: presents the findings of interviews
conducted with UK agri-food businesses as well as policymakers with regards to
countries actively targeted by the UK food and drink sector and details on the trade
barriers confronted;

Chapter 4- Areas for Government support based on primary research outputs:
presents the findings of the interviews conducted in Chapter 3 with regards to areas for
Government support;

Chapter 5- Success stories of bringing down barriers and growing abroad: based
on the interviews conducted, the chapter presents a selection of six case studies from
small, medium and large UK food and drink businesses who have successfully
overcome certain trade barriers and grew revenues through exports;

Chapter 6- Shortlisting target countries and products: presents the methodology
used and the results of shortlisting the longlists of 30 countries and 20 products
identified in Chapter 2. Through a structured approach, the 600 potential opportunities
are reduced to 118 and then filtered to 56. Out of these 56 potential opportunities, 6
opportunities were selected across 4 countries and 6 product categories using
qualitative and quantitative criteria; and

Chapter 7- Forecasting the export opportunity for the selected UK products: for
the six opportunities identified at the end of Chapter 6, an extensive data collection
and analysis has been undertaken in order to forecast the potential opportunity in place
by removing the most important trade barriers for UK exports.
10
© 2013 Grant Thornton UK LLP. All rights reserved.
Chapter 1. Literature review
Section 1.1. Introduction and scope
The main objectives of this project are to map the trade barriers relating to UK agri-food
products, consider the economic potential and penetrability of those barriers and,
therefore, the overall potential opportunity presented by the market, which can be opened
through Government and industry negotiations. The literature review is, therefore, not the
central nor the largest element of the engagement, but is nonetheless essential in building
the evidence required to inform the business case for engaging in trade negotiations and
providing improved overseas market access for UK agri-food products.
There is a wide body of literature on trade barriers within the academic and international
organisation arenas. The various research papers and studies are highly analytical, usually
relying on statistical and economic models. However, the topic is fragmented and the main
issue is that there are very limited examples of literature that provide a comprehensive
overview of the major issues associated with international trade and market access that
directly meet the project brief. To conduct the literature review, a vast body of literature
was consulted to identify the relevant topics for the Defra engagement. As mentioned
already, the principal objective of the Defra engagement was to identify the main trade
barriers that apply to UK agri-food products and to seize the opportunity that the removal
of these barriers would create for UK agri-food businesses. Therefore, the literature review
was not the project aim, but it was necessary to provide context. Accordingly, this section
does not aim to be a detailed and exhaustive review of all literature on the topics of market
access and international trade.
The literature review addresses the requirements set out by Defra in the invitation to
tender, namely to provide a brief and broad overview of the theory behind market access
and is structured as follows:

Section 1.2- Benefits of free trade: provides an overview of the benefits that economic
theory associates with free trade, and empirical evidence of the benefits achieved by
consumers and businesses and reiterates why removing trade barriers is important for
the UK agri-food industry;

Section 1.3- Trade barriers definition and types: gives a short overview of the main
trade barriers (tariff and non-tariff) and the various classifications for non-tariff
measures;

Section 1.4- Market failure: sets the context in which market barriers operate, explains
the objectives of regulations adopted by Governments to protect consumers', animals'
and plants' health and illustrates where market access barriers exist due to market
failures;

Section 1.5- Evidence at a global or European level of the benefits of removing trade
barriers: gives evidence of potential benefits from overcoming barriers through specific
examples from ex-ante and ex-post analysis of international and bilateral trade
negotiations;

Section 1.6- Quantifying the effect of trade barriers: provides a brief overview of the
main economic models used in literature for quantifying the impact of non-tariff
barriers; and

Section 1.7- Trade barriers/Market access databases: gives a short overview of the
various databases available in the public domain that attempt to map trade barriers by
type, geography and product code.
© 2013 Grant Thornton UK LLP. All rights reserved.
11
Section 1.2. Benefits of free trade
Market access is the removal of trade barriers and the opening up of new markets and
opportunities on the basis of a level playing field for providers and consumers alike where
all can compete freely and fairly for the benefit of all.1
There are several elements which can affect the market access of a product originating in a
country to the market of other countries, from trade barriers, to the exchange rate, the
distance the product has to travel to more unquantifiable elements such as historic,
economic and cultural links between the importing and exporting country. For this
literature review, market access was only concerned with trade barriers and the effect that
these have on trade.
Trade opening and increased market access result in an increase in trade flows, but trade
growth in itself is not the aim; it is a means to reap economic and social benefits.
“A common joke about economists is that, if you line all of us up, we will all point in a different
direction. On trade policy, however, economists nearly all point in the direction of free trade. Robert
Whaples (2006) surveyed American Economic Association members in 2005 and found that
87.5% agreed that the USA should eliminate its remaining trade barriers.” 2 Magee (2011)
However, economists do not agree on the link between free trade and economic growth.
Some consider that trade in itself is not sufficient to drive growth and argue that structural
reforms and institutional quality maximise the benefits created by free trade (Rodriguez &
Rodrik (2011), Chang et al. (2009))3. An ex-post analysis of EU free trade agreements
(FTAs) demonstrates that where a sharp drop in tariffs across sectors was accompanied by
domestic reform and liberalisation, countries maximised the opportunities created by the
reduction/removal of trade barriers (see section 1.5 for more details of the impact of the
various FTAs signed by the EU).
When considering global benefits resulting from the removal of trade barriers and their
distribution between developed and developing countries, according to a study by the
European Commission4, following the Uruguay Round5, developing countries have in
general gained more than developed countries as their market share in world trade as a
group has increased from 25.9% to 30.6% between 1995 and 2003. An interesting point is
that when looking at the market share gain of major developing countries such as China,
India and Mexico, their evolution has been different. China experienced the largest market
share growth, followed by Mexico, which increased its market share from 1.63% to 2.32%,
while India‟s share rose from 0.63% to 0.87%. India is closer to China in economic size
and certainly should have had a larger share of the world market, but India liberalised to a
limited extent and later than other large developing countries. This, again, illustrates the
1
Definition given by the Department for Business, Innovation and Skills (BIS)
2
Magee, C. (2011), Why Are Trade Barriers so Low?, Institute of Economic Affairs, October 2011
3
Rodriguez, F.& Rodrik, D. (2001) "Trade Policy and Economic Growth: A Skeptic's Guide to the CrossNational Evidence," NBER and Chang, R, Kaltani, L., Loayza, N. (2009) "Openness can be good for growth:
The role of policy complementarities", Journal of Development Economics 90 (2009)
European Commission (2006), What were the main effects and who were the beneficiaries of the Uruguay
Round? – Brussels, 3 April 2006
4
Uruguay Round was the 8th round of multilateral trade negotiations (MTN) conducted within the framework
of the General Agreement on Tariffs and Trade (GATT), between 1986-1994. At this round, GATT was
transformed into the World Trade Organization (WTO). The measures agreed were implemented between
1995 to 2000 (2004 in the case of developing countries)
5
12
© 2013 Grant Thornton UK LLP. All rights reserved.
point that trade alone cannot create significant and sustainable economic growth and it
needs to be combined with domestic reform to maximise its impact.
A recent EU document6 points out that conceptually, there are several arguments for a
positive link between trade and economic growth: from a more efficient allocation of
resources, dissemination of knowledge and innovation to competition which leads to a
price/quality advantage for consumers and benefits to exporters as they access new
markets and can reap the advantages of increasing returns to scale and specialisation.
A large body of literature focuses on the benefits that free trade offers to the economy,
consumers, and businesses, with some studies quantifying the impact on productivity,
intermediary and consumer prices, job numbers and wage levels. According to various
studies, trade increases productivity and therefore, leads to higher international
competitiveness. In Europe, Chen et al.7, for example, estimate that between 1998-2000
productivity in manufacturing increased by 11% as a result of international trade.
Consumers may also benefit from free trade as they have access to a wider range of goods
and services, but more importantly, trade liberalisation reduces tariffs and increases
competition for domestic firms, both of which result in lower prices for consumers. For
instance, during 1996-2006 import prices for textiles and clothing fell by 27.5% and 38.4%
respectively in real terms (i.e. relative to the general consumer price index (CPI)). For the
same period the import price of consumer electronics fell by around 50%.
A 2004 study (Boda et al., 2004)8 estimates the gains to American consumers of the growth
in global variety during the period 1972-2001 to be circa 2.6% of GDP. Translating these
„variety gains‟ into an EU context suggests that the average European consumer benefits
are circa €600 per year, on top of the benefits due to lower prices.
Free trade is also credited with having a positive effect on job creation and wage levels.
Based on a detailed analysis of the EU25 input-output tables for 2000, it is estimated that
around 14 million jobs throughout Europe depend on exports to the rest of the world. On
the basis of a model simulation aimed at quantifying the wage premium arising from the
current EU trade patterns, it is estimated that the average wage in Europe would be 7%
lower if the EU did not trade internationally. The same analysis shows that, if real wages
are constant, abandoning EU external trade would result in an 18% drop (36 million jobs)
in EU employment.
Section 1.2.1. Market access for UK agri-food products
The agri-food industry is a major contributor to the UK economy, with the entire food
chain contributing £96.1 billion to national Gross Value Added in 2011 and employing
3.3 million people as of Q3 20129. However, the difficult economic context puts the
industry under pressure, as some cash-strapped consumers have reduced their spend on
food. In this context, exports are an opportunity to offset the low growth/stagnating
domestic market. However, the UK's traditional trade partners have also been significantly
impacted by the economic downturn in their home markets. In contrast, the socioeconomic trends in emerging markets (especially in Asia and Latin America) indicate that
these markets present the best opportunities for the UK agri-food sector. Strong economic
6
EU Commission, Trade as a Driver of Prosperity, European Commission
7
Chen, N., Imbs, J., Scott, A., (2004), “Competition, Globalization and the Decline of Inflation”, CEPR
Discussion Paper Series No. 4695, 2004
Broda, C., Weinstein, D.E., (2006), “Globalization and the Gains from Variety”, The Quarterly Journal of
Economics, 2006, pp. 541-585
8
9
Defra (2012), Food Statistics Pocketbook 2012, Defra
© 2013 Grant Thornton UK LLP. All rights reserved.
13
growth, combined with population growth and food inflation, will create big food and
drink grocery markets among emerging countries, overtaking the traditional leaders, the US
and Japan in terms of value. According to research by the Institute of Grocery Distribution
(IGD Research)10, China has overtaken the US as the world‟s biggest food and grocery
retail market. By 2015, the Chinese market is forecast to reach £918bn compared to a US
value of £675bn, representing a 10.9% compound annual growth (CAGR) over 2011-2015,
compared to 3.2% forecast for the UK.
The favourable context set by globalisation, which favours convergence of dietary
attitudes, combined with rising consumer spending, results in emerging market consumers
demanding Westernised, higher-value products. UK multinationals have already tapped
significantly into the emerging markets, but small and medium enterprises (SMEs) in the
agri-food sector are lagging behind the UK and EU average across all sectors. 10% of UK
agri-food SMEs export compared to 21% of UK companies across sectors and 25% of EU
companies across sectors. However, this is not a UK agri-food sector problem, as agrifood companies in the main EU economies (excluding Spain) also lag behind. Similarly, in
the agricultural sector, many countries have globally operating Farmer Controlled
Businesses (FCBs) that are specifically focusing on exports e.g. Fronterra in New Zealand.
These are multinational companies that are owned by farmers. In contrast, UK FCBs are
relatively small and production focused, mainly operating within the Co-op legal structure.
Given the slow economic growth forecast for the UK's historic trading partners, the
industry needs to re-orientate itself towards high-growth economies which have the
potential to turn into strong and large consumer markets.11 By focusing on the emerging
markets, the industry can take advantage of potentially sizeable opportunities and ensure it
continues to play a key role in driving strong and sustainable growth for the UK overall,
while continuing to employ a large workforce within the UK.
The UK agri-food export growth over the past decade showcases the appeal of British
products; although recent trade statistics show that the UK lags behind the world average
and the growth obtained by competing European countries, indicating that the UK is
losing market share.12 This implies that despite the opportunities presented by export
markets, UK food and drink manufacturing businesses are likely to face strong competition
from other countries that are also focusing on exports as a way to tackle sluggish
domestic markets.
Marketing products overseas has its own challenges and companies need to conduct
market opportunity assessments and devise market entry strategies to ensure their products
address local consumers' needs, purchasing power and preferences. Moreover, agri-food
businesses have to tackle international trade barriers, which represent a significant obstacle
to export growth and which require concerted action in World Trade Organisation (WTO)
and bilateral trade negotiations as part of the EU or by the UK Government.
IGD Research (2012) press release, China's grocery market overtakes the US as biggest in the world, 02 April
2012
10
Ireland, the UK's main agri-food and drink export market is forecast 0.5% GDP growth in 2012, while
France, the second largest UK agri-food and drink export market is forecast to grow by 0.4% compared to
2011. Source: European Commission (2012), Interim Forecast (February 2012)
11
The compound annual growth (CAGR) of food, drinks and tobacco in 2000-2010 was 10% for the world,
9% for the EU27, 10.5% for Germany, 9.1% for Italy, 8.9 % for Spain, 6.5% for France and 5.4% for the UK.
Source: World Trade Organisation (2011), Trade Statistics
12
14
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 1.3. Trade barriers definition and types
Many policymakers and academics prefer the more neutral term „measures‟ rather than
„barriers‟ because they believe most of these measures have been designed without
considering their potential impact on trade. Nevertheless, some policy instruments affect
the flow of goods and services and, therefore can be considered trade barriers. The
traditional policy instrument used to be import tariffs.13 Therefore, trade barriers have
historically taken the form of tariffs and taxes. International efforts to remove them have
been on-going for over 50 years, starting with the General Agreement on Tariffs and Trade
(GATT) and followed by rounds of international trade negotiations under the umbrella of
the World Trade Organisation (WTO).
Section 1.3.1. Tariff barriers
An import tariff is a tax collected on imported goods. Governments apply tariffs on
imports in order to generate income and/or to protect strategically important sectors or, in
the case of developing countries, infant industries, from international competition. Tariffs
are applied to products entering the country, thus raising their price in comparison with
domestic products and making them more expensive or uncompetitive compared to the
domestic offering. Additionally, tariffs reduce efficiencies by allowing companies that
would not exist in a more competitive market to exist.
As successive Rounds of GATT negotiations have reduced tariff barriers (or the poorest
countries have been given preferential access to Western markets), they have become a
lesser feature of national trade policy. Non-tariff measures have become more prominent
and frequent and overcoming them is considered by policymakers, academics and
businesses as the main challenge of current trade policy.14
Section 1.3.2. Non-tariff measures
Non-tariff measures (NTMs) can take many forms and the first challenge when attempting
to analyse the impact that NTMs have is to identify them and develop a clear
nomenclature. Academic studies point towards this as a pre-condition for a coherent and
robust analysis. However, they also point out that the commonly accepted definition of
NTM is not very useful. The United Nations Conference on Trade and Development
(UNCTAD) defines NTMs as "policy measures, other than ordinary customs tariffs that can
potentially have an economic effect on international trade in goods, changing quantities traded, or
prices or both",15 which is too broad and does not provide an insight into the types of
NTMs. Therefore, academics and policymakers have looked at various categorisations to
gain more insight into NTMs. There are several approaches to categorising them.16 The
first typology of NTM was developed by Baldwin in 1970, followed by Laird and
Vossenaar. The latter classify NTMs according to their intent or immediate impact.
Root, F. (200), International Trade and Investment, The Wharton School University of Pennsylvania. SouthWestern Publishing Co
13
The GATT had 23 signatories when it came on stream in 1948, and 84 signatories by the end of the Tokyo
Round in 1979. More than 110 countries signed the Uruguay Round accords in Marrakesh in April 1994
(including several countries with observer status in the GATT). As of January 2000, the WTO has 135
members with an additional 31 in the process of accession. At the close of the 8th Round of GATT
negotiations the average ad valorem tariff on industrial goods had fallen from some 40% to just below 4%
(although high barriers remain in agriculture and apparel)
14
UNCTAD 2010 definition quoted in Nicita, A., Gourdon, J.,(2011) Preliminary Analysis of Newly Collected
Data on Non-Tariff Measures, Policy Issues in International Trade and Commodities Studies, United Nations
15
Dee P. and M. Ferrantino (ed) (2005), Quantitative Methods for Assessing the Effects of Non-Tariff
Measures and Trade Facilitation, Asia Pacific Economic Cooperation
16
© 2013 Grant Thornton UK LLP. All rights reserved.
15
The most recent systematic work on classifying NTMs belongs to Deardorff and Stern 17
who define NTMs by their characteristics:

Reduction in the quantity of imports;

Increase in the price of imports;

Change in the elasticity of demand for imports;

Variability of NTMs;

Uncertainty of NTMs;

Welfare costs of NTMs; and

Resource costs of NTMs.
Nicita and Gourdon (2011) state that: “Broadly defined, NTMs include all policy related trade
costs incurred from production to final consumer, with the exclusion of tariffs. For practical
purposes NTMs are categorized depending on their scope and/or design and are broadly
distinguished in technical measures (Sanitary and Phytosanitary Standards, (SPS); and Technical
Barriers to trade, (TBT)) and nontechnical measures. These are further distinguished in hard
measures (e.g. price and quantity control measures), threat measures (e.g. antidumping and
safeguards), and other measures such as trade-related finance and investment measures).” 18
Non-tariff barriers appear in the form of regulations and can take many guises which make
them difficult to tackle by Governments or exporters. Some of them touch on sensitive
cultural and social issues. Although in some cases, there may be intentional trade barriers
favouring domestic products against imports, sometimes they are put in place to address
legitimate concerns such as consumer information through labelling, food safety, abuse of
intellectual property rights or environmental protection.
In the 2012 World Trade Report, the WTO “Non-tariff measures, such as TBT/SPS
measures (including labelling), taxes and subsidies, are often the first-best policy instruments to
achieve public policy objectives, including correcting market failures such as information
asymmetries (where parties do not have the same information) or imperfect competition, and
pursuing non-economic objectives, such as the protection of public health. NTMs such as export
subsidies and export taxes increase national income by exploiting market power in international
markets. While many NTMs are concerned with consumer protection, NTMs can also be utilized
by political incumbents to protect domestic producers. In some cases, the use of NTMs can promote
trade but in many other cases, they restrict it. In cases where the NTMs are meant to correct a
market failure, the trade effects are an inadvertent by-product of pursuing a public policy objective.
At other times, when NTMs are employed to manipulate the terms of trade or protect domestic
producers, adverse trade effects on partners are the means through which gains are captured. The
fact that the same NTM used to pursue a public policy objective can also be used for protectionist
purposes underlines the difficulty of distinguishing between “legitimate” and protectionist
Deardorff A and R. Stern (1997), Measurement of Non-Tariff Barriers, OECD Economics Department
Working Paper no. 179, Paris, OECD
17
18 Nicita,
A., Gourdon, J.,(2011) Preliminary Analysis of Newly Collected Data on Non-Tariff Measures, Policy
Issues in International Trade and Commodities Studies, United Nations
16
© 2013 Grant Thornton UK LLP. All rights reserved.
motivations for NTMs, and of identifying instances where NTMs create unnecessary trade
costs.”19
In a 2011 report, the European Commission acknowledged that "regulatory measures
perform important functions for societies and pursue legitimate public policy objectives. Compliance
often increases the cost of production of a good or service. But it is first and foremost intended to
increase the benefits that consumers and citizens derive from these goods and services, for example
achieving an appropriate level of protection of human health and safety, animal and plant life,
environmental conservation and safeguarding consumers from deceptive practices. For this reason
and unlike tariffs, NTMs cannot simply be scrapped. That would lead not only to considerable
welfare losses but also a loss in consumer confidence that may cause major trade disruptions.
However, without calling into question the right of countries to establish their own levels of health
and safety protection of citizens and consumers, NTMs have often been prepared with purely
domestic considerations in mind, without sufficient account being taken of their impact on
international trade or of the availability of more trade-friendly solutions." 20
Various surveys have confirmed that Governments and businesses view import tariffs as
less important and see non-tariff barriers in the form of internal, behind the border policies
that they need to comply with as the main barrier to exporting. The Organisation of
Economic Cooperation and Development (OECD) did a comparative analysis of 12
business surveys conducted in various countries on the topic of trade barriers. The study
revealed that across countries, businesses were most concerned about technical measures,
including health and phytosanitary regulations and customs rules and procedures.
A recent UNCTAD/World Bank research paper (Nicita & Gourdon 2011)21, which
analysed newly collected data on the use of NTMs across 26 countries found that the use
of NTMs is extensive and increasing, especially the use of technical measures. TBTs
affected 30% of the international trade analysed, while SPS affected 15% of trade, however
their use is limited to agri-food, which explains the lower incidence. When looking at
agri-food products, the study found that 60% of products are affected by SPS.
Chart 1.3.2.1 shows the number of notifications to the WTO and the number of notifying
countries since 1995 for both SPS and TBT measures across sectors. Both series exhibit
upward trends.
World Trade Organisation (2012), World Trade Report 2012: Trade and public policies: A closer look at
non-tariff measures in the 21st century
19
20
European Commission (2011), Trade as a driver of prosperity
Nicita, A., Gourdon, J.,(2011) Preliminary Analysis of Newly Collected Data on Non-Tariff Measures, Policy
Issues in International Trade and Commodities Studies, United Nations
21
© 2013 Grant Thornton UK LLP. All rights reserved.
17
1.3.2.1.
SPS and TBT notifications 1995-2010 (number of
notifying countries and number of notified measures
per year)
A) SPS
B) TBT
The UK Government (through BIS, UKTI and Defra) acts to remove market access
barriers for UK exports. On its website, BIS states that it "acknowledges the complexity of
trade barriers and has different approaches to overcome them from bilateral discussions to using
EU and WTO channels and tools." The support structures put in place by the UK
Government and industry as well as the best tools to adopt in removing barriers are the
objective of a current SERIO study22 commissioned by Defra. During the course of the
literature review, it has been noted that the UKTI website provides comprehensive
information and support aimed at exporters accessing international markets. The website
showcases several examples of bilateral negotiations which resulted in creating market
access for UK companies and features business opportunity alerts (a free online service
providing export sales leads, sent direct to the subscribers via UKTI‟s global
contacts network).
22
SERIO (2012), Obstacles to export growth for small and medium sized Agrifood companies, Defra
18
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 1.3.3. Trade barriers for the agri-food sector
Despite the forum set up by the WTO to promote free trade, Government intervention in
the agricultural sector is still more intrusive than in any other sector. Unlike industrial
products, agri-food products have higher tariffs applied. Most support received by
domestic producers is provided through trade-distorting instruments combined with
assistance to exports in the form of subsidies, which make the agri-food sector one of the
most affected by lack of market access.
TBT/SPS measures in particular, vary across sectors but are especially prevalent in
agriculture. Trade in agri-food products is also curtailed by sanitary and phytosanitary (SPS)
barriers but, since the introduction of the WTO Agreement on the Application of the
Sanitary and Phytosanitary Agreement in 1995 (which allows member states to impose
restrictions on health and safety grounds subject to scientific proof) there has been a
reduction in the conflict between countries in the areas of plant and animal health. An area
where the SPS Agreement was less successful was that of food safety, as was seen in the
case of the EU-US beef hormone dispute. The beef hormone dispute has affected trade
with US and Canada since 1988 when the EU imposed a ban on beef from animals treated
with growth promoting hormones. In 1996, the US and Canada challenged this decision at
the WTO and got the right to impose sanctions on EU agri-food products.23 It took until
2012 to unlock the stalemate.
Importing countries have imposed rules on health, safety and hygiene standards to deal
with the threat on domestic health and sanitation problems posed by these imports. The
enactment and application of these types of rules is governed by the WTO‟s SPS
Agreement. The SPS Agreement provides the framework for nations to impose trade
restrictive measures based on consideration for protecting the life or health of animals,
plants and humans. The SPS Agreement calls for the harmonisation of standards within
the guidelines and principles set by three international agencies: Codex Alimentarius
Commission (established by the Food and Agricultural Organisation (FAO) to promote
standards related to food and agriculture), the International Office of Epizootics and
organisations working within the framework of International Plant Protection Convention
and it instructs these three organisations to monitor the standards so that they can be
harmonised. Countries are free to exceed international standards, but if they do they need
to fulfil a number of requirements, including basing them on a scientific justification,
performing a risk assessment, minimising adverse trade effects, etc.
A recent WTO World Trade Report mentions that concerns about SPS measures
overwhelmingly affect the agriculture sector (251 of the 267 specific trade concerns for
which a Harmonized System (HS) code sector could be identified, that is 94%). However,
this is not surprising as SPS measures are largely limited to the agro-food products because
their control is essential in ensuring the health and well-being of consumers and the
protection of the environment. For TBT measures, out of the 283 specific trade concerns
for which an HS sector could be identified, 82 (29%) are in agriculture and 184 (65%) in
other sectors. However, econometric analysis shows that the coverage ratio and the
frequency index of TBT measures subject to specific trade concerns are higher in
agricultural sectors than non-agricultural ones.
"Specific trade concerns related to SPS measures overwhelmingly affect the agricultural sector (94
per cent). More unexpected is the fact that a large number of TBT concerns (29 per cent) also
relate to agriculture. Additionally, econometric analysis shows that TBTs as measured by specific
trade concerns are most important, in terms of numbers of tariff lines and trade value, in the
MacLaren, D. (2002), Trade Barriers and Food Safety Barriers, University of Melbourne available on
https://digitalcollections.anu.edu.au/bitstream/1885/41994/2/aciar_2002_mclaren.pdf
23
© 2013 Grant Thornton UK LLP. All rights reserved.
19
agricultural sector. If ITC survey responses are weighted by trade, the reported incidence of NTMs
among firms in the agricultural sector is 63 per cent, compared with 45 per cent in manufacturing.
Furthermore, TBT/SPS measures are far more prevalent among NTMs in agriculture (59 per
cent) than in manufacturing (34 per cent). Evidence from WTO disputes also shows a greater
number of citations of the SPS and TBT agreements in cases involving agricultural products. Both
agreements were cited in 28 per cent of disputes involving agricultural products (as defined in the
Agreement on Agriculture) between 2007 and 2011. Meanwhile, no disputes involving nonagricultural products cited the SPS Agreement and only 2.9 per cent cited the TBT Agreement."24
Section 1.3.4. Trade barriers as a response to the economic crisis
The current prolonged economic downturn increases the risk of protectionism and it is
important that countries refrain from protectionism, as trade openness remains a key
element to a sustainable and balanced economic recovery. The WTO publishes regular
reports on trade restrictive measures in which it monitors the measures adopted by G20
countries, their conformity with WTO rules and their impact on international trade.
According to the latest WTO report on G-20 trade measures25, "disappointingly weak growth
in some G-20 countries and continuing macroeconomic imbalances globally are testing the political
resolve of many governments to abide by the G-20 commitment to resist protectionism".
In the latest report covering May-mid-October 2011, the WTO reported that there is "a
growing perception that trade protectionism is gaining ground in some parts of the world as a
political reaction to current local economic difficulties – difficulties that trade restrictions are very
poorly equipped to resolve, such as the case of currency fluctuations and macroeconomic imbalances.
There are various signs of a revival in the use of industrial policy to promote national champions
and of import substitution measures to back up that policy. Unilateral actions to shield domestic
industries, although appealing from a narrow short-term perspective, will not solve global problems;
on the contrary, they may make things worse by triggering a spiral of tit-for-tat reactions in which
every country will lose."26
WTO (2012), World Trade Report 2012: Trade and public policies: A closer look at non-tariff measures in
the 21st century
24
25
WTO OMC (2011), Report in G-20 Trade Measures (May to Mid-October 2011)
26
ibid
20
© 2013 Grant Thornton UK LLP. All rights reserved.
Chart 1.3.4.1 quantifies and categorises the specific trade concerns (STCs) raised by the
WTO. It shows that food safety is slightly more prominent in STCs brought against G-20
members: 34% of STCs brought against G-20 members were on the subject of food safety,
whereas the corresponding figure across all member countries is 32%. The proportion of
animal health related concerns raised on the basis of measures maintained by G-20
members (34%), is less than that in STCs against all countries (38%).
1.3.4.1.
Specific Trade Concerns raised against G-20
countries vs. all WTO members (May-mid October
2011)
350
6%
300
250
200
24%
7%
25%
Plant Health
38%
150
100
50
Other concerns
Animal Health
34%
32%
34%
Food safety
0
STCs (G20 WTO members) - 231
Total STCs (across WTO members) - 330
© 2013 Grant Thornton UK LLP. All rights reserved.
21
Section 1.4. Market failure
According to economic theory, market failure occurs when resources are misallocated or
allocated inefficiently. The main sources of market failure are imperfect market structure or
non-competitive behaviour, the existence of public goods, the presence of externalities and
imperfect information. Public goods are goods or services that bestow collective benefits
on members of society and generally no one can be excluded from enjoying their benefits
e.g. national defence. Externalities are costs or benefits resulting from some activity or
transaction that is imposed on parties outside the activity or transaction. Externalities are
also called spill over effects. Imperfect information is the absence of full knowledge
regarding product characteristics or available prices for one or both parties of a transaction.
According to a Defra study27, market failures concerning export trade can be thought of in
terms of two broad categories:
 "Where the costs of overseas market entry are unnecessarily higher than their “real” economic
costs; this is most likely due to imperfect information. Information is needed for a market to
operate efficiently. However, exporters may not have access to, or an understanding of, complete
information about the market especially where the system is complex and varies greatly from
domestic markets. There may also be a skills gap particularly of individuals who have
knowledge and experience of working in these markets; and

Where the expected benefits from overseas market entry to individual firms is less than the full
social benefits of their activity. For example, beneficial knowledge spill overs, where other firms
may benefit from a UK firm's export success through awareness raising of opportunities
and through lessons learned from exporting, which filter through informal social and
business networks."
Given the scope of this project is to assess market access barriers (in the form of tariff and
non-tariff trade barriers) for the UK agri-food sector, in this section the focus will be on
examples of market failures created by trade barriers in the agri-food sector.
At a global level, countries apply a wide range of regulations in the agri-food sector. Some
regulations may be motivated by the desire to protect the domestic industry from
competition and may discriminate against imports by imposing harder conditions on
imports compared to domestic producers. Many regulations in areas such as safety, health,
marketing, labelling and packaging aim to protect consumers where markets do not
produce the desired outcome and result in market failure.
Section 1.4.1. Imperfect information
Economic theory describes two broad forms of imperfect information and these also apply
to market access situations. Information asymmetries are cases where one side of the
transaction has information that the other side does not possess. For example, a consumer
in an importing market may not have information about the type and quantity of chemicals
applied in the primary production of imported products. In the absence of measures
requiring a certain level of food safety, producers may not have the incentive to respect the
food safety standards. If consumers believe that they do not hold enough information to
consider a product safe, there will be reduced demand for the imported products. As the
exporting countries or exporting firms do not have a credible way to showcase the quality
of their products, the importing country Government may have to step in and impose
27
Defra Analytical Team, International Comparison of Exports to Emerging Markets
22
© 2013 Grant Thornton UK LLP. All rights reserved.
regulations that remove the safety doubt from consumers' minds.28 The other form of
imperfect information occurs when the information is imperfect for both parties e.g. a
food borne disease transmitted through meat without being apparent to either producer
or consumer.29
According to "Measuring Costs and Benefits of Non-Tariff Measures in Agri-Food Trade"
(Beghin et a. 2011)30 SPS and TBT measures are meant to be in place in order to address
the above types of imperfect information. SPS measures, for example, aim to provide a
certain level of food safety for consumers, as well as protecting human, animal and plant
health. Other quality aspects such as organic production or fair trade, for example, go
beyond safety aspects and are thus not considered SPS measures. On the other hand, TBT
measures refer to labelling and marketing standards, as well as norms for sizes, quality
classes and other physical attributes of products or groups of products, amongst other
factors. The distinct characteristics of SPS and TBT measures are hence given by the
objectives the measures attempt to achieve. Focusing on SPS measures, in order to attain
these goals, governments typically set minimum requirements for which no price premium
is obtained. Firms can obtain higher prices for specific quality characteristics beyond food
safety, given that the quality level is communicated to consumers (via labels) and that
consumers are willing to pay for quality. The price premium would represent additional
costs for providing a differentiated and potentially better quality product.
In general, the requirements for foreign products usually reflect the domestic requirements
in the importing country, and according to the international trade rules, the SPS Agreement
and the TBT Agreement of the World Trade Organisation (WTO) attempt to ensure that
standards are not misused as disguised protectionist measures in favour of domestic
producers. While maintaining the sovereign right and obligation of countries to set their
own regulations and standards, countries are encouraged to base their import requirements
on internationally agreed benchmarks, in the case of food safety, for example, these would
be the Codex Alimentarius standards and guidelines. The two agreements contain detailed
provisions on how the WTO Member States deal with possible SPS and TBT issues at a
multi-lateral level. However, when domestic standards are significantly different from
international standards, regulations that have been put in place to protect consumers from
dangerous imported goods turn into trade barriers. In this case, agricultural exporters and
investors are facing an increasing number of unjustifiable non-tariff barriers in the form of
product certification, labelling standards, import approval requirements and customs
clearance delays.
Section 1.4.2. Externalities and spill over effects
A study by Katherine Bayliss (2003)31 demonstrates the spill over effects of trade barriers
for agri-food products. The author examines the trade distortion effects of the 1996
Voluntary Export Restraint (VER) placed on tomato exports from Mexico to the US. The
VER was adopted by the US to protect its domestic tomato growers in Florida from
Mexican competition. As a result, Mexico exported more tomatoes to Canada during the
summer when the floor price imposed by the VER to the US was binding, while the US
MacLaren, D. (2002), Trade Barriers and Food Safety Barriers, University of Melbourne available on
https://digitalcollections.anu.edu.au/bitstream/1885/41994/2/aciar_2002_mclaren.pdf
28
Rama, I. and Harvey S. (2009), Market Failure and the Role of Government in the Food Supply Chain: an
Economic Framework, Department of Primary Industries, State Government Victoria, Australia
29
30 Beghin,
J., Disdier, A-C., Marette, S., van Tongeren F., "Measuring Costs and Benefits of Non-Tariff
Measures in Agri-Food Trade", Working Paper, Iowa State University
Bayliss K. (2003), Dispatches from the Tomato Wars: Spillover Effects of Trade Barriers, Working Paper
Number 2003-06, Food and Resource Economics, University of British Columbia
31
© 2013 Grant Thornton UK LLP. All rights reserved.
23
decreased its exports to Canada. This implies that the trade barrier was effective in keeping
US prices higher and making the domestic market attractive for local growers. The trade
effect of the VER was a reduction in NAFTA (Mexico & Canada) exports to the US of
120,000 metric tonnes with 10,000 tonnes being sold on the domestic US market instead
of being exported to Canada. Moreover, the Mexican tomatoes that could not enter the US
were turned into paste and resulted in an increase in tomato paste exports, which affected
the Californian producers of processed tomatoes.
Section 1.4.3. Environmental impact
As per "The Challenge of Subsidies and Trade Barriers" (Anderson et al. 2008)32, the
effects of trade reform on the environment have been the focus of much theoretical and
empirical analysis since the 1970s and especially in the past dozen or so years. Until
recently environmentalists have tended to focus mainly on the direct environmental costs
they perceive from trade reform, just as they have with other areas of economic change.
That approach does not acknowledge areas where the environment might have been
improved, albeit indirectly, as a result of trade reform (e.g. from less production by
pollutive industries that were previously protected). Nor does it weigh the costs of any net
worsening of the environment against the economic benefits of policy reform of the sort
already described.
"The reality is that while the environmental effects of reform will differ across sectors and regions of
the world, some positive and some negative, there are many examples where cuts to subsidies and
trade barriers would reduce environmental damage. For some time the OECD has been
encouraging analysis of these opportunities. More recently several major NGOs, together with the
OECD Secretariat, have begun to focus on providing better information about the wastefulness of
environmentally harmful subsidies that has already started to have an impact (e.g. in reducing coal
mining subsidies in Europe). Environmental NGOs have increasingly recognised them over the
past decade, with Greenpeace focusing on energy subsidies, WWF on fisheries subsidies (WWF
2001), and IISD and Friends of the Earth on subsidy reforms generally. They and the betterinformed development NGOs such as Oxfam have come to the view that the net social and
environmental benefits from reducing subsidies and at least some trade barriers may indeed be
positive rather than negative, and that the best hope of reducing environmentally harmful subsidies
and trade barriers is via the WTO’s multi-issue, multilateral trade negotiations process." 33
Gossner et al. (2009)34 show how agri-food imports can carry pathogens or pests that are
foreign to a country's ecology and, therefore, create environmental risks. In this case,
sanitary and phytosanitary measures imposed by the importing country can deal with the
market failure which is the risk of importing serious disease. These measures follow
international guidelines set in the WTO's SPS Agreement, but certain countries may have
higher standards which may act as trade barriers as they impose conditions on exporters
which restrict, slow down or increase the cost to access export markets.
Anderson, K., Winters, A., (2008), The Challenge of Subsidies and Trade Barriers, Copenhagen Consensus
2008 project
32
Anderson, K., Winters, A., (2008), The Challenge of Subsidies and Trade Barriers, Copenhagen Consensus
2008 project
33
Gossner, C.M. et al (2009), The Melamine Incident: Implications for International Food and Feed Safety,
Environmental Health Perspectives, 117(12)
34
24
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 1.5. Evidence at a global or European level of the
benefits of removing trade barriers
Despite the large number of economic papers on international trade and trade barriers, the
literature review found surprisingly few examples of quantified economic value from the
removal of trade barriers. 14 examples have been nonetheless collected, which are
presented as short case studies. The examples in this section are a mix of ex-ante and expost quantifications of benefits resulting from the conclusion of WTO negotiations and
bilateral free trade agreements. Also provided are theoretical estimates of the potential
benefits expected from a successful outcome in the latest WTO trade negotiations
(Doha round).
Example 1 – EU
The European Commission states that it carries out feasibility studies and (sustainability)
impact assessments to estimate the potential trade and economic growth effects of bilateral
and multilateral trade agreements by means of ex-ante economic simulations. Although the
European Commission is actively involved in monitoring and tackling trade barriers, most
publicly available literature produced by the European Commission only states the current
trade volume/value and the fact that the removal of the particular tariff or non-tariff
barrier will benefit EU exporters and consumers in importing markets. Very few examples
exist of the potential (ex-ante) or actual (ex-post) economic value for exporters if barriers
were to be removed. One of the cases where the EU quantified the benefits from
removing trade barriers was for the exports of beef in Malaysia where a Bovine
Spongiform Encephalopathy (BSE) ban for EU beef and beef products was lifted in 2010.
An indication of the economic value is given by looking at the value of EU beef exports to
Malaysia in 2000 before the introduction of the ban - over €1.2 million. Another example
of estimated economic value was that calculated by the European Commission in the case
of the BSE ban on beef and beef related products to the Philippines. The lifting of the ban
for products from the UK, Germany, Spain and Portugal in the Philippines was achieved
in 2010 and was expected to create opportunities for European exporters. In order to seize
the opportunity, the European Commission looked at historic trade data. In 2000, before
the introduction of the ban, exports of European beef to the Philippines exceeded 19,000
tonnes and were valued at over €24 million, giving an indication of the trade that could
potentially be generated through the lifting of restrictions in the Philippines. 35
According to the EU Commission's studies, the impact of individual bilateral FTAs on EU
GDP is generally small, in the range of a 0.1% to 0.2% increase, because the EU economy
is much larger than the economies of its bilateral FTA negotiating partners. However, the
increase in EU exports is estimated to be up to 2%. If all the on-going trade negotiations
that the EU is engaged with currently were to be successfully completed, it is estimated
that the EU's GDP would increase by 0.5%.
In a 2011 study, Copenhagen Economics36 examined whether EU Free Trade Agreements
(FTAs) have a measurable and statistically significant impact, both on EU exports and
imports. The study analysed six EU FTAs (ranked by size, year of entry into force in
brackets): South Africa (1999), Mexico (2000), Morocco (2000), Tunisia (1998), Chile
(2003) and Jordan (2002).
Commission Staff Working Document accompanying the EU Commission Report on Trade and Investment
Barriers Report 2011 (2011)
35
36 Copenhagen
Economics (February 2011), Ex-Post assessment of six EU Free Trade Agreements at
http://trade.ec.europa.eu/doclib/docs/2011/may/tradoc_147905.pdf
© 2013 Grant Thornton UK LLP. All rights reserved.
25
According to the econometric analysis performed by Copenhagen Economics, there was
strong evidence of an increase in EU exports in the cases where initial tariffs were high and
they were removed quickly and across all types of goods and services. For example, EU
exports to Tunisia increased by 80%, while those to Chile increased more than two fold.
Before the agreement, Chile imposed a flat rate of 6% tariff on almost all imported goods.
The EU-Chile FTA comprised a rapid reduction of these tariffs, with 92% of EU exports
to Chile becoming zero in the first year of the agreement and 98% becoming duty free
trade after five years. The trade weighted average tariff dropped from 6% in 2002 to less
than 0.1% in the first year of the agreement. The authors show that according to estimates,
EU exports to Chile can be said to have increased markedly as a result of the FTA. The
impact is an estimated 148% increase in exports as a result of the FTA and the result is
statistically significant.
However, this pattern did not repeat for the FTAs with Mexico, where tariff reductions
happened gradually, over a long period of time, and were still on-going in 2011. In 2000,
before signing the agreement Mexico imposed an average trade weighted tariff of 16% on
goods from the EU. Only 16% of EU exports to Mexico became duty free in year one of
the agreement and only one third of trade had been liberalised by 2006.
Example 2 – EU-Mexico FTA
In 2000, before the FTA Agreement was signed, the United States-Mexico Chamber of
Commerce (USMCOC) stated that agriculture had historically represented only 6% of
Mexico's total trade with the EU. Even though a significant number of important
agricultural products had been excluded from the Mexico-EU FTA, the expectation was
that there would be plenty of opportunities for investment in Mexican agriculture due to
the increase of exports to the EU. According to one of the estimates provided by
USMCOC in 2000, Mexican agricultural exports to the EU would increase 10-fold over the
following decade until 2010.
Using Trade Map37, this estimate was tested and found that the agri-food exports from
Mexico to EU 15 increased from $360m in 2001 to a record $805m in 2010. However, this
increase only represents 124% growth, which is far below the 10-fold increase originally
forecast by industry specialists back in 2000. Even when accounting for the 2008-2009
downturn, during which period Mexico's food exports remained stagnant, the growth
significantly undermines the original estimate. This highlights the large discrepancies that
can exist between modelled/forecast figures and actual outcomes.
Example 3 – EU-South Korea FTA
More recently, the EU signed a free-trade agreement with South Korea which was
expected to result in £1.4 billion savings in duty for EU exporters. According to
Copenhagen Economics, the agreement is estimated to increase revenues for EU firms by
€19 billion and €13 billion for South Korean firms. For the UK, the agreement is expected
to add £500 million additional trade per year based on 2010 trade volumes and according
to UKTI the agreement will result in new opportunities for UK companies in Korea,
particularly in legal and financial services, pharmaceuticals, advanced engineering and the
low carbon industry, including the renewables sector. However, as the agreement has only
been in place for a short period of time, it is not possible to test these estimates with
trade figures.
37 Trade
Map is a database developed by the International Trade Centre UNCTAD/WTO (ITC) and contains
international trade statistics
26
© 2013 Grant Thornton UK LLP. All rights reserved.
Example 4 – Washington State Apples
According to The Effects of Reducing Sanitary and Phytosanitary (SPS) Barriers to Trade
on the Washington State Apple Industry (2006)38, the US produced 4.2m metric tonnes of
apples in 2003, accounting for 11% of the estimated world apple production. Between
2002 and 2004 the US was one of the top five leading exporters by value and volume of
fresh apples with Washington State supplying approximately 85% of US exported apples.
According to the Northwest Horticultural Council (2004), the estimated potential increase
in exports to Australia, China, India, Japan, South Korea, Taiwan and Thailand, if the SPS
barrier was removed, would be $5 to $25 million in sales to each country each year and $25
to $50 million in sales to Mexico. This signifies the importance of SPS barriers whose role
is typically to protect consumers of the importing country, but which can also be used as a
trade barrier to protect domestic producers and which can really deter growth for
exporters with competitive advantage in a specific product.
Example 5 – Raw milk cheese
Recently, countries such as Canada, Australia and New Zealand have begun to consider
new legislations, or modifying existing ones, to allow the production and sale of a wider
range of raw milk cheeses in their territory. Since July 2001, Canada has provided a special
facility to import raw milk cheeses stored for less than 60 days for consumers in the
province of Quebec. Australia and New Zealand have followed similar approaches.
In Case Studies of Costs and Benefits of Non-Tariff Measures39, the first case study
focuses on Listeria, which is only one of a number of pathogens which can be present in
raw milk but are generally destroyed through pasteurisation. The analysis concentrates on
two raw milk cheeses (camembert and brie) in Canada's province of Quebec. Welfare
changes are estimated through a cost-benefit analysis, following the approach outlined in
OECD (2008). This provides a framework for a systematic accounting of economic costs
and benefits associated with each authorisation regime (ban or approval). The authors
compare the actual situation in 2006, which allows for French imports of raw milk cheese
stored for less than 60 days, to a counterfactual scenario assuming a ban for such young
raw milk cheese imports, reflecting the legal situation in Canada before 2001. The
framework incorporates two types of cheeses, young raw milk and pasteurised (including
aged raw milk) cheese, and two main types of consumers: those who belong to highly
vulnerable groups and those who do not. The vulnerable group is further divided into
informed persons about health risks associated with raw milk cheeses, and persons that are
not informed about the health risks. The costs of authorisation are assessed by including a
measure of consumers‟ willingness to pay for avoidance of risk. The benefits of
authorisation arise mainly through greater product variety. Cross-market effects on the
pasteurised segment arising from the allowance of young raw milk cheeses are also taken
into account.
The estimated economic impact of a hypothetical removal of the authorisation of raw milk
cheese stored for less than 60 days in Quebec was summarised as:

The combined consumer surplus declines by almost CAD 7.9 million in the market for
camembert and by some CAD 7.2 million in the market for brie;
Nogueira, L., Chouinard, H., (2006), The Effects of Reducing Sanitary and Phytosanitary (SPS) Barriers to
Trade on the Washington State Apple Industry, paper presented at the American Agricultural Economics
Association Annual Meeting
38
Van Tongeren, F. et al. (2010), “Case Studies of Costs and Benefits of Non-Tariff Measures: Cheese, Shrimp
and Flowers”, OECD Food, Agriculture and Fisheries Working Papers, No. 28, OECD Publishing
39
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27

The impact on producers‟ profits is different between domestic and foreign producers
due to the fact that the composition of cheese qualities varies: indeed, it is the (foreign)
producers of young raw milk cheese who lose all the profits related to the markets in
Quebec, whereas (domestic and foreign) producers of PORM (pasteurised and old raw
milk cheese stored for 60 days or more) cheese gain following the increase in demand
and hence prices. Retailers benefit from the ban too, as the losses on the young raw
milk cheese market are outweighed by gains on the PORM cheese market; and

The ban avoids additional costs for the society linked e.g. to public health care
expenditures and losses of work time. Assuming the same willingness to pay on the
side of the society as estimated for concerned consumers' preferences, these saved
costs amount to some CAD 44k and CAD 41k in the markets for camembert and
brie, respectively.
In total, and abstracting from the savings of additional costs for assuring safety in the
supply chain, a ban of young raw milk camembert and brie – equivalent to the regulations
before 2001 – would result in estimated costs at some CAD 6.1 million and
CAD 5.5 million (i.e. net welfare loss), respectively. Together with the profit losses of
foreign producers, the estimated total loss would sum up to CAD 6.7 million and
CAD 6.1 million, respectively.
Example 6 – Shrimp
According to the same research paper (Case Studies of Costs and Benefits of Non-Tariff
Measures), between 1996 and 2006, world imports of shrimps in terms of quantity
increased by 69%, from 1,037 to 1,752 thousand tonnes. The shrimp boom has brought up
some important issues. Among the most important are health costs as shrimps often
contain diseases (e.g. salmonella), pesticides and/or harmful drug and antibiotic residues
(such as chloramphenicol). Concerns are also related to the environment (e.g. destruction
of mangroves). Other issues are related to the illegal use of areas for shrimp aquaculture
and corruption of local authorities, as well as bad working conditions (employment of
children and of illegal immigrants).
This study is focused on health concerns. Over the last decade, some OECD countries
rejected several import shipments of shrimps on health and safety grounds, imposed
temporary import bans, and asked for stronger health and safety controls. OECD
countries‟ standards and requirements, which these countries have imposed, motivated by
consumer protection, obviously affect production and exports of shrimps by developing
countries and least developed countries. The report investigates the economic impacts of
such standards on farmed shrimp production. In particular, it examines whether these
standards, given the size of demand by OECD countries, could be an incentive for
exporting countries to adapt and improve their production methods. In the past, some
countries, e.g. Thailand, improved their production scheme by implementing Better
Management Practices (BMP) programmes and/or switching production from traditional
shrimp species to more disease-resistant species. The authors examine whether Thailand's
approach, if extended to three other exporting countries, namely India, Indonesia and
Vietnam, would bring positive welfare effects.
One of the scenarios the authors are investigating is this: improvement in the production
through the implementation of BMP programmes. The use of antibiotics in the production
is banned and Asian governments reinforce quality controls and inspection before exports.
OECD countries allow shrimp imports from Asian countries. However, production costs
are now higher (due to BMP programmes) and there are also inspection costs for
the government.
28
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The authors make use of the Cost-Benefit Analysis (CBA) framework. They analyse
exclusively the supply side, i.e. they do not consider consumer welfare effects induced by a
change in production. The basic CBA framework developed in OECD (2008) is extended
to account fully for the foreign producer side. In particular, foreign supply is augmented to
include variable costs related to the adoption of improved production methods following
health and safety standards imposed in importing countries.
As a result, under the scenario already presented, the increase in production costs is more
than compensated by the higher probability of entering the OECD markets, which results
in increased net revenues. Despite the lack of precise data, this result underlines the
incentive for farmers to improve their processes of production for complying with safety
rules, and for ensuring full access to the export markets. More specifically, the OECD is
now expected to import $4.1m, $3.3m and $3.3m more worth of shrimps from Vietnam,
Indonesia and India respectively.
Example 7 – US wine
The Wine Institute in the US (the administrator of the "Market Access Program", an
export promotion programme managed by the United States Department of Agriculture
(USDA) Foreign Agricultural Service), argues that the removal of trade barriers has helped
increase US wine exports. The Wine Institute expects that the recent ratification of the USSouth Korea free trade agreement and the 20% import tax on Californian wine that was
abolished in October 2011, are expected to support the growth of US wine exports.
However, the Institute estimates that in the regions where trade barriers are still in place,
such as "the Pacific Rim where wineries are burdened by protectionist tariffs and duplicative
regulations costing Asia-Pacific economies close to $1 billion per year".40
Example 8 – Hormone war
In the US/EU trade relationship, academics have investigated the impact that the various
technical trade barriers in agri-food have on both the consumers as well as exporters. One
significant case in the late '90s was the "hormone war" in which the EU banned the use of
five natural and artificial hormones in meat production. According to various studies this
impacted US beef exports by between $100-$250 million between 1989 and 1998. Other
studies have shown that the US would lose $1 to 3 billion per year when eliminating
hormone use because of reduced lean meat growth, weight gain, and feed efficiency. Some
studies looked at both the impact for the EU consumers as well as the US exporters. For
example, for offal which was the category most affected by the hormone ban, Peterson et
al. using a partial equilibrium model and assuming that the domestic supply of edible offal
in the EU was perfectly inelastic estimated that the ban increased the EU price for edible
offal by 34-45% and decreased world prices by at least 35%. They quantified the loss for
EU consumers at ECU 49.9-64.3 million, while under this model, the US exporters would
decrease exports by 56% or $148 million. 41 A recently proposed EU concession in the
beef hormone war should result in benefits for both EU and US/Canadian exporters. US
and Canada have already suspended import duties, amounting to almost $130 million,
imposed on "blacklisted" EU farm produce. Suspending these duties, which hit France,
Germany, Denmark and Italy hardest, will enable these and other Member States to sell
their chocolate, pork, Roquefort cheese, mustard, onions and truffles and other products
to the USA and Canada at competitive prices. In exchange, the EU will allow non-EU
Press release 12 February 2012 "2011 U.S. Wine Exports, 90 % From California, Reach New Record Of $1.4
Billion" on www.wineinstitute.org
40
Otsuki et al. (2001), " Saving two in a billion: quantifying the trade effect of European food safety standards
on African exports", Food Policy 26 (2001) 495–514
41
© 2013 Grant Thornton UK LLP. All rights reserved.
29
countries to sell the EU 48,200 tonnes of duty-free high-quality beef from animals not
treated with growth-promoting hormones.
Example 9 – USDA survey
According to a 1996 US Department of Agriculture (USDA) survey of technical barriers in
US agricultural products, the US was losing $4.97 billion in exports across the world due to
what respondents considered non-transparent and difficult to challenge regulations. The
EU's share of this estimated trade was $899.6 million, with many barriers referring to
animal products whose impact for US exporters was estimated at $477.3 million, followed
by processed foods and grains where questionable barriers exceeded $100 million.
Academics who commented on this study pointed out that the survey participants such as
FAS attaches and trade organisations may have been biased as their role is to promote US
agricultural exports. Due to confidentiality issues the authors of the survey could not
identify specific issues, therefore, the reliability of the figures cannot be confirmed.42
However, even if the export estimates are overstated, they do show that trade barriers can
have a significant impact on the country's agri-food exporters.43
Example 10 – Developing countries
Some trade barriers have a particularly strong impact on developing countries as they
cannot implement the changes in infrastructure and adhere to the requirements set by
developed countries. This issue has been the subject of many academic studies. A 2001
study looked at the impact of the effect of European sanitary and phytosanitary regulations
on African exports and found that if the EU were to implement its aflatoxin standard, this
would have a negative impact on African exports of cereals, dried fruits and nuts which the
study quantified at 64% or US$ 670 million.
A World Bank economist has estimated that a „typical‟ developing country must spend
$150 million to implement requirements under less than six WTO Agreements, e.g.
customs valuation, sanitary and phytosanitary measures and trade-related intellectual
property rights to name a few.44
Example 11 – UK breeding pigs
In November 2010 the UK signed an agreement with China‟s Administration of Quality
Supervision, Inspection and Quarantine (AQSIQ) which involves the export of UK
breeding pigs to China. This agreement which is the result of negotiations and concerted
effort by UKTI, Defra and the British Pig Association is expected to result in exports
worth £45 million over five years. At the time, UKTI reported that an agreement has also
been reached on health certification which will allow pig meat exports. According to The
British Pig Association, pig meat exports to China have the potential to rise to over £40
million per annum if all UK meat processing plants are approved.45
Weyerbrock, S. and Xia, T. (2000), "Technical Trade Barriers in US/EU Agricultural Trade", Agribusiness,
Vol. 16, No. 2, 235–251, quoting Thornsbury, S., Roberts, D., DeRemer, K., & Orden, D. (in press) "A first
step in understanding technical barriers to agricultural trade", International Association of Agricultural
Economists (IAAE), Occasional Papers, No. 8
42
Weyerbrock, S. and Xia, T. (2000), "Technical Trade Barriers in US/EU Agricultural Trade", Agribusiness,
Vol. 16, No. 2, 235–251, quoting various studies
43
OECS Trade Policy Facilitator, Market Access and Trade Policy: Theory and Practice in the Context of the
FTAA
44
UKTI press release 8 November 2010 on
http://www.ukti.gov.uk/pt_pt/uktihome/pressRelease/120402.html?null
45
30
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Example 12 – Scotch whisky
Another example of the successful promotion of UK agri-food and drink products is the
Scotch whisky registration as Geographic Identification (GI) in China in November 2010.
At the time the Scotch Whisky Association estimated that exports to China would grow by
100% in the next four to five years as a result of the GI recognition. Given that exports
were already growing rapidly46 prior to this, it is unlikely that just the GI recognition can be
the main driver of the growth. However, as the market will slowly mature the GI
recognition will certainly benefit consumers and exporters offering protection
from counterfeits.
Example 13 – Doha round
A number of recent studies have tried to assess the potential economic impact of the Doha
Round for the world in general and for developing countries in particular. As a 2006
economic analysis47 memo from the European Commission shows, the economic benefits
linked to services or trade facilitation are potentially the most important in the Doha
Round. For instance, the Centre d'Etudes Prospectives et d'Informations Internationales
(CEPII) found that agriculture would contribute 25% of the world income gains; industrial
products would contribute 32% and services 43%. The Australian Productivity
Commission found global gains of about $50bn from agricultural liberalisation, $80bn
from manufacturer liberalisation and around $130bn from services liberalisation. When
looking at merchandise only, tariff cuts in industrial products could generate the majority
of the gains (Carnegie, Swedish National Board of Trade, CEPII, etc.). CEPII found that
40% of the gains would come from agriculture, against 60% for industry. A substantial
tariff reduction for industrial products would offer, in relative terms, larger gains to
developing countries than to the developed countries. For Carnegie, the distribution of the
gains is very much in favour of Industrial products (90%) against 10% in agriculture.
However these results are based on a scenario which favours industrial liberalisation and
on a set of technical options.
On the other hand, according to a World Bank study, agricultural liberalisation (including
domestic support and cuts in export subsidies) could provide about two thirds of the total
income gains. These results come from a set of assumptions and underlying parameters
which are highly debatable. For instance, the tariffs in agriculture are assumed to be
reduced 10 times more than for industrial products for developing countries. In addition, it
is assumed that all crops can be grown on all kinds of soil, which is unrealistic for most
agricultural production, and that new arable lands are available at no cost.
For CEPII, a round restricted to liberalisation in agriculture would not favour developing
economies taken as a whole, notwithstanding the large gains to be expected by some of
them. In line with similar works, the study shows that liberalisation limited to agriculture
would have a very unbalanced impact across different countries: the gains would be limited
to those developed importers that liberalise their agricultural trade (European Free Trade
Association, Korea and Taiwan, and to a lesser extent the EU), and to a few, very
competitive exporters (Australia, New Zealand, Brazil, Argentina, Thailand).
Scottish whisky exports to China grew from £24.7 million in 2004 to £54.7 in 2010 and £66 million 2011 out
of a total market of £74.8 and £74.4 million in 2010 and 2011 respectively, indicating that Scottish whisky grew
its market share significantly in a market that was static
46
European Commission (2006), Doha Round: some recent economic analysis. Memo - Brussels, 23 June 2006
on http://trade.ec.europa.eu/doclib/docs/2006/september/tradoc_129213.pdf
47
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31
Another recent study on the real income effects of the Doha round48 shows the real
income effects that the market access proposal of the Doha round would have at a global
level. The authors use the LINKAGE model of the global economy, and estimate the gains
using detailed estimates of changes in tariffs at a fine level of disaggregation. The Doha
WTO negotiations propose to cut applied tariffs on agricultural market-access (AMA) and
non-agricultural market access (NAMA) in goods by around 20%. The agricultural
proposals also include the abolition of export subsidies and sharp reductions in maximum
levels of domestic support, especially in the EU and the United States. The authors state
that global gains are conservatively estimated to be around $160 billion per year from
AMA and NAMA agreements alone. However, they estimate that true gains would be
larger because the proposed cuts in bound tariffs (an average of 27% in agricultural and
46% in non-agricultural goods) would reduce the uncertainty associated with the current
large gaps between applied and bound tariffs.
Example 14 – Global benefits
In The Challenge of Reducing Trade Barriers and Subsidies, the author (Anderson 2004)49,
refers to various studies estimating global gains from removing trade barriers. For example,
a 2002 study (Anderson et al) estimated the impact of removing all countries' trade barriers
and agricultural subsidies and calculated the economic welfare gain at US$254 billion per
year in 1995 dollars as of 2005 (and hence slightly more each year thereafter as the global
economy expands). Of that, $108 billion per annum was estimated to accrue to developing
countries. This was amongst the lowest of the estimates from efforts to calculate the
impact of removing world trade barriers with the highest quoting up to $2.1 trillion.
Example 15 – FTAs
In "The Impact of Regional Trade Agreements on Trade in Agricultural Products", the
authors focus on assessing the effect of tariff preferences given by the partner countries.
The analysis is based on trade and tariff data at a detailed product level for 78 Free Trade
Agreements over the period 1998-2009.
Through their econometric analysis, the authors are able to prove the significant impact
that preferential agreements have on trade in agricultural products. They estimate the
impact both on pre-existing trade flows (the intensive margin) and on the probability of
new trade flows arising (the extensive margin).
A year after an FTA has been in force the impact on both the intensive and extensive
margin is positive and significant. On average a 1% preferential margin increases preexisting trade flows by 2% and increases the probability to export a given product to a
partner country by 0.1%. The analysis reveals significant differences depending on the
countries involved: the positive impact is found to be stronger for South exports
(developing countries) rather than for North exports (developed countries). The study
finds that: "the preferential margin for agricultural products is approximately 9% in agreements
between South countries, while for agreements between North and South (high-income OECD
and others) the preferential margins granted by the former are considerably higher (approximately
15% on average) than those granted by the latter (approximately 4% on average, eight years after
entry into force)."50
Laborde, D., Martin, W., Van Der Mensbrugghe, D., (2011), "Potential Real Income Effects of Doha
Reforms", in Unfinished Business, The WTO's Unfinished Agenda?, International Bank for Reconstruction
and Development/World Bank http://voxeu.org/sites/default/files/file/unfinished_business_web.pdf
48
Anderson, K., (2004), The Challenge of Removing Trade Barriers and Subsidies, World Bank Policy
Research Working Paper
49
OECD Joint Working Party on Agriculture and Trade THE (2012), The Impact of Regional Trade
Agreements on Trade in Agricultural Products
50
32
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 1.6. Quantifying the effect of trade barriers
There is extensive literature on the quantification and evaluation of the impact that tariff
and non-tariff measures have on trade. A number of different methodologies have been
historically used which vary according to the type of measure in place and the industry
being covered. This chapter, intends to simply provide an overview of the literature
available in this field that has been written by economists and is considered relevant to
calculating the value of the shortlisted opportunities later on in the project. In chapter 7,
these grounds are covered with more focus on the different parameters that should be
taken into consideration, the data to investigate, the analysis to conduct and the weightings
that should be applied to quantify the impact of trade barriers.
It is worth noting that most of the methodologies covered in the literature involve
extensive models that utilise large datasets, which in most cases will not be readily available
and would require a long period of time to collect. There is no generic, straightforward
approach being utilised by industry experts in order to assess, quickly and effectively, the
impact of removing trade barriers, especially for non-tariff measures such as SPSs and
TBTs (however, WITS, a software provided by World Bank, allows the calculation in a
relatively straightforward manner of the impact that tariff barriers have on certain aspects
of trade).
In terms of tariffs, the USA National Trade Estimate Report (NTE Report) states51 an
approximate impact of tariffs can be calculated by obtaining estimates of supply and
demand price elasticity‟s in the importing country where sufficient data is available.
Typically, the USA's share of imports is assumed to be constant. The reports continue by
stating that when calculated price elasticity‟s are unavailable, reasonable postulated values
are used. The resulting estimate of lost US exports is approximate, depends on the
assumed elasticity‟s, and does not necessarily reflect changes in trade patterns with third
countries. Similar procedures are followed to estimate the impact of subsidies that displace
US exports in third country markets. As mentioned above, WITS, the software provided
online by World Bank, based on a number of databases including UNCTAD's, WTO's and
other, allows the users to calculate the impact of tariff reductions or removals across
certain product categories and countries on trade values.
However, in terms of non-tariff measures, the USA NTE Report mentions that the task of
estimating the impact of such measures is far more difficult, since there is no readily
available estimate of the additional cost these restrictions impose. As per the report,
quantitative restrictions or import licenses limit (or discourage) imports and thus raise
domestic prices similarly to a tariff. The report states that without detailed information on
price differences between countries and on relevant supply and demand conditions, it is
difficult to derive the estimated effects of these measures on US exports. As per the report,
it is similarly difficult to quantify the impact on US exports (or commerce) of other foreign
practices, such as government procurement policies, non-transparent standards, or
inadequate intellectual property rights protection.
According to "Measuring Costs and Benefits of Non-Tariff Measures in Agri-Food
Trade"52, assessing the economic effects of NTMs poses significant challenges as the link
between trade, welfare and policy is tenuous. Many NTMs may restrict trade but can
improve welfare in the presence of negative externalities or informational asymmetries.
Other measures can expand trade as they enhance demand for a good, through better
51 (2012),
" The 2012 National Trade Estimate Report on Foreign Trade Barriers (NTE)" , Office of the United
States Trade Representative (USTR)
52 John
C. Beghin, Anne-Celia Disdier, Stephan Marette, Frank van Tongeren, (2011), "Measuring Costs And
Benefits Of Non-Tariff Measures In Agri-Food Trade", Iowa State University
© 2013 Grant Thornton UK LLP. All rights reserved.
33
information about the good, or by enhancing the good‟s characteristics (Maertens et al.,
2007; Maertens and Swinnen, 2009).
The report continues by stating that the efficiency costs of NTMs are hence much less
evident than the welfare losses associated with tariffs and quantity measures. They do not
necessarily embody the economic inefficiencies that are associated with classical trade
barriers, unless they discriminate between sources of supply; they may or may not be the
least trade-restrictive policies available to correct market imperfections and the least trade
restrictive policies may fail to maximise welfare inclusive of the externality. Furthermore, it
states that it is not clear a priori that the trade impacts of the concerned regulations are
inefficient, or that removal of associated NTMs that affect trade would achieve efficiency
gains relative to the welfare level under existing regulation.
Beyond the well-established trade impeding effects of many NTMs, trade expanding
effects also have been identified, often through harmonisation and shared standards, in
customs unions, and for some goods and policies (Moenius, 1999, 2006; Fontagné et al.,
2005; Henry de Frahan and Vancauteren, 2006; and Disdier et al., 2008).
Nevertheless, as per Quantifying the Trade and Economic Effects of Non-Tariff
Measures53, specific methods have been developed for the analysis of policies such as
tariff-rate quotas, standards (including SPS), trade facilitation, rules of origin and
government procurement. The broad similarities among the methods applied to these
various policies, as well as policy-specific features should be kept in mind. However, the
approach varies according to the question being asked (e.g. Are the models for illustrating
the benefits of liberalisation for a domestic audience? Identifying “winners and losers"?
Deciding which policies to pay more attention to?). Each question will require different
datasets, econometric analysis and research into specific measures.
According to the same study (Quantifying the Trade and Economic Effects of Non-Tariff
Measures), some of the methods being utilised to analyse non-tariff measures are:
i
The handicraft price gap method
This method estimates the degree to which NTMs raise domestic prices above
international prices in the countries imposing them. It estimates a “price gap”
between domestic prices and international prices by comparing prices of goods
affected by an NTM with goods unaffected by an NTM. According to the
report, in some sense this is an ideal method; it can be used to incorporate
detailed specific information about the workings of policies, and gives results
in terms of a “tariff equivalent” (ad valorem percentage change) that can be
compared with tariffs and used in simulation models. Price data is not always
readily available for all products and countries of interest. It is often difficult to
make two price measurements for the same good and be confident that one
fully reflects the effects of an NTM while the other is unaffected. Adjustments
need to be made for such factors as transport costs, wholesale and retail
margins. It is costly or difficult to make comparisons for many countries or
policies this way;
ii
Price-based econometric methods
These methods attempt to incorporate the intuition behind the price-gap
method and extend it to many countries and products simultaneously. They
take advantage of systematic reasons prices are higher in some countries than
others to identify the extent to which high prices for some countries and
products may be attributable to NTMs. Because these methods are capable of
53 Ferrantino,
M. (2006), “Quantifying the Trade and Economic Effects of Non-Tariff Measures”, OECD
Trade Policy Working Papers, No. 28, OECD Publishing. http://dx.doi.org/10.1787/837654407568
34
© 2013 Grant Thornton UK LLP. All rights reserved.
handling larger quantities of data than the “handicraft” price-gap method, they
offer the promise of being able to compare the effects of NTMs more broadly,
in order to identify which categories of goods they are most applicable to,
using a common method for all countries and products. Their results can also
be expressed as ad valorem tariff equivalents and used in simulation models.
Price data is not always readily available for all products and countries of
interest. A good deal of product- and policy-specific detail must be set aside
because a common method is used for all products and countries. Thus, results
for specific cases may diverge widely from those which would have been
obtained using a case-by-case analysis. Choices about the econometric
specification may influence the results obtained; and
iii Quantity-based econometric methods
These methods look for evidence that the presence of NTMs leads to lower
trade flows, or that the presence of trade facilitating policies or practices leads
to higher trade flows. Statistical analysis of trade data is employed, including
both gravity models (emphasising country size and economic distance between
countries as factors explaining trade), factor-content models (which emphasise
the differing availability of resources in different countries), and models
blending features of gravity models and factor-content models. Trade data on
quantities are much more abundant and more internationally standardised than
price data, so that in principle all products in all countries can be analysed.
Recent advances in methods offer hope for future progress. The effect on
trade flows may be of more direct interest to policymakers than the effect on
prices. The general limitations of econometric work (using common methods
may ignore product-specific information, choices about econometric
specification may affect results) apply to both price-based and quantity-based
methods and may be more severe for quantity-based methods. Results from
quantity-based methods can only be expressed as tariff equivalents or price
gaps by use of additional assumptions and information.
According to a study by UNCTAD, Quantification of Non-Tariff Measures54, there are
both a number of complications and limitations with the measurement and collection of
NTM data. Alan Deardorff and Robert Stern (1998) and the United Nations Economic
and Social Commission for Asia and the Pacific (2000) propose some guiding principles
for measuring NTMs:

Measures of NTMs should be constructed to reflect equivalence to tariffs in terms of
their effects on the domestic prices of the traded goods;

Only direct effects on domestic prices should be used to define tariff equivalence;

There is no single method that can be relied upon to measure the sizes of NTMs that
may be present in all sectors of the economy;

There is no substitute for NTM-specific measures;

Greatest reliance should be placed where possible on measures that derive their
information from market outcomes in preference to measures that seek to construct
estimates of the market outcomes from the quantitative data;

There are many NTMs in practice for which high quality measures are simply
not available;
54 Bora,
B. Kuwahara, A. and Laird, S. (2002), “Quantifying the Trade and Economic Effects of Non-Tariff
Measures”, UNCTAD
© 2013 Grant Thornton UK LLP. All rights reserved.
35

Given the uncertainty that surrounds the measurement of NTMs, it would be best to
construct approximate confidence intervals – upper and lower bounds that can be
assumed to include the size of the NTM being measured; and

Estimates of NTMs should be done at the most disaggregated levels possible.
The authors highlight that while the above are sensible suggestions there is some question
as to how practical they are to implement.
36
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 1.7. Trade barriers/Market access databases
There have been several attempts to collect data on agri-food tariffs and especially NTMs
and to make this information available for public use. The scarcity of databases on NTMs
may be explained by the difficulty in collecting such complex data in a consistent manner
across countries. International organisations such as the EU, WTO, UNCTAD have made
significant efforts to classify and collect data on NTMs. However, the picture is far from
clear or complete. The main limitations of these databases/data sources are:

The data is not centralised and can be found within different regulatory agencies within
a particular country;

Unlike tariffs, NTMs are not simple numbers, they can be difficult to identify as they
are often hidden in regulatory documents;

They are not always up-to-date and have many missing data points;

The data is often inconsistent suggesting inaccuracies;

Some allow a comparison in time, while others only provide a static picture;

They may not use consistent definitions and categorisations which makes comparisons
difficult; and

Some rely on self-reporting by member states or businesses, which means they are
unlikely to be comprehensive.
All of the above makes compiling and analysing NTMs a resource intensive task.
Nonetheless, much progress has been made in documenting trade barriers in the past
decade and the various sources available have been the base for studies by academics of
international organisations. Below is a short description of the main market access and
trade databases available. Some of them have been consulted to compile a longlist of
barriers, countries and products and they were revisited in subsequent chapters for a more
detailed analysis of shortlisted countries, barriers and products.
World Integrated Trade Solution (WITS)
World Integrated Trade Solution (WITS) is a software developed by the World Bank, in
collaboration and consultation with various international organisations including the
United Nations Conference on Trade and Development (UNCTAD), the International
Trade Centre (ITC), the United Nations Statistical Division (UNSD) and the World Trade
Organization (WTO). WITS provides access to information on international trade, tariff
and non-tariff barriers. WITS integrates the following databases:

The UN COMTRADE database maintained by the UNSD; (Exports and imports by
detailed commodity and partner country);

The TRAINS maintained by the UNCTAD; (Imports, Tariffs, Para-Tariffs & NonTariff Measures at national tariff level); and

The Integrated Database (IDB) and Consolidated Tariff Schedules (CTS) databases
maintained by the WTO (Most Favoured Nation Applied, Preferential & Bound
Tariffs at national tariff level).
The WTO plans to enrich WITS with MacMap, the database developed by the
International Trade Centre UNCTAD/WTO (ITC) and includes up-to-date tariffs and
trade information by country and product.
© 2013 Grant Thornton UK LLP. All rights reserved.
37
Despite being considered the most comprehensive public source available and being used
for research, the WITS Manual cautions that the information on non-tariff barriers is often
old and only partially reported; thus should be used with caution.
The Trade Analysis and Information System (TRAINS)
The Trade Analysis and Information System (TRAINS) database provided by UNCTAD is
a comprehensive source of publicly available information on NTMs implemented by
governments and has been frequently used in research. The TRAINS database records and
counts the frequency with which trade measures appear. However, it does not provide an
indication of economic impact or policy priorities. It records incidences of NTMs that are
reported to the WTO as well as changes and new regulations with regards to the measures
that apply to imports. However, it has not been consistently updated in the past 10 years.55
Market Access Database (MADB)
The European Commission has developed the Market Access Database (MADB), a portal
which aims to facilitate information exchange on international trade between members‟
states, businesses and European institutions. This portal includes three databases which
compile the tariff levels applied, the non-tariff measures applied by third countries to EU
members and a separate sanitary and phytosanitary barriers database, as a result of the
growing issues encountered by EU agri-food products. The NTM databases provide a
static picture of the barriers applied to EU exporters outside the EU at a particular point in
time. However, they do not track the barriers faced over time. MADB also provides
businesses with an interface to ask the European Commission to investigate unfair barriers
placed on their products and services abroad and the European Commission a systematic
way to monitor the behaviour of trade partners and ensure that they abide by international
commitments. The portal includes information on import formalities required by country
and product type and a statistical database of trade flows between EU and non-EU
countries by product type.
Although not exhaustive, MADB appears to be the most comprehensive and up to date
source for market access barriers faced by EU countries/businesses exporting
agri-food products.
In parallel, the EU provides information for non-EU firms looking to export to the EU.
For example, through its Export Help portal, the EU Commission offers a comprehensive
and up-to-date list of the EU import requirements by product category and Member State
(destination country) in order to support exporters from developing countries. (see
http://exporthelp.europa.eu).
EU’s FP7 project “NTM impact”
Another recent attempt to collect data on NTMs was undertaken within the EU‟s FP7
project “NTM impact”. Within that project, regulations and standards that prescribe the
import requirements for a selection of agri-food products, which are relevant to trade
between the EU and ten main trade partner countries, are compared across countries.
Looking only from the EU exporters‟ perspective, the project uses the EU import
requirements as the benchmark for comparison. Detailed information on the data and the
subsequent analysis can be found on the webpage of the “NTM impact” project at
http://www.ntm-impact.eu.
Gonzalez Mellado, A. Hélaine, S., Rau, M-L. and Tothov, M. (2010) Non-tariff measures affecting agro-food
trade between the EU and Africa, European Commission, Joint Research Centre
55
38
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National Trade Estimate Report on Foreign Trade Barriers (NTE)
The United States Trade Representative (USTR) produces a National Trade Estimate
Report on Foreign Trade Barriers (NTE), an annual report of barriers to US exports
organised by country or custom union.
WTO sources
The WTO's analysis of the completeness of its own data is: "WTO internal sources include
WTO members’ schedules of concessions/commitments, notifications, WTO trade policy reviews,
monitoring reports, and information on specific trade concerns (STCs) raised by WTO members
and disputes brought to the WTO. Most of these sources suffer from limitations and fail to provide
the level of transparency they are supposed to deliver. With WTO members’ notifications, for
example, the low compliance rate can be a serious limitation. Another problem is the accessibility
of data which are not always stored in databases and are scattered. The situation with regard to
the accessibility of NTM data should improve considerably with the WTO’s new Integrated Trade
Intelligence Portal (I-TIP), which is currently being deployed."56
As mentioned already, WTO compiles a regular Trade Policy Review (TPR). However,
these TPR reports do not contain readily extractable information on NTMs and require an
individual analysis and manual extracting of the information by country and product and,
therefore it is not the most 'user friendly' tool when analysing a large number of countries
and products. WTO also compiles complaint registers. At the international multilateral
level, the WTO Secretariat documents the member countries‟ trade concerns regarding
NTMs (notified and not notified) in regular summary reports. The International Portal on
Food Safety, Animal Plant Health (IPFSAPH) compiles reports on SPS trade concerns (for
more details refer to http://ipfsaph.org).
Other sources of NTM data include the Global Anti-Dumping Database, the CoRe NTMs
Database and the Global Trade Alert Database.
In conclusion, none of these data sources provides comprehensive coverage of NTMs.
However, each sheds light on a particular aspect, geography or product category and
collectively are useful to help build a view of NTMs for UK agri-food products.
World Trade Organisation (2012), World Trade Report 2012: Trade and public policies: A closer look at
non-tariff measures in the 21st century
56
© 2013 Grant Thornton UK LLP. All rights reserved.
39
Chapter 2. Longlist of target export countries,
agri-food products where the UK has
a comparative advantage and trade
barrier mapping
Section 2.1. Introduction and scope
This chapter presents the methodology and a high-level overview of the analysis
undertaken to derive a longlist of export target countries, products where the UK has a
comparative advantage and most frequent barriers. The chapter is structured as follows:

Section 2.2- Identification of longlist of target countries: following data collection and
analysis of trade and macroeconomic parameters across more than 100 countries, the
section identifies a list of 30 target countries for the UK agri-food exports. Two
scenarios accounting for variations of key parameters and sensitivity analyses have
been incorporated to ensure the robustness of the output;

Section 2.3- Identification of longlist of key product categories: by accounting for trade
statistics, identifies a longlist of 20 agri-food products (at the 4-code level of the HS
2007 classification system) where the UK has a 'comparative advantage' and should
focus on exporting. As above, two scenarios accounting for variations of key
parameters and sensitivity analyses have been incorporated to ensure the robustness of
the output. The basis for determining the areas where the UK has a 'comparative
advantage' was the absolute value of exports by the UK in 2011 worldwide (including
and excluding EU), as well as the Revealed Comparative Advantage as calculated by
the Balassa Index (for more details, refer to section 2.3). In addition, the world demand
for each product category as measured by the global level of imports was also
accounted for;

Section 2.4- Non-Tariff Measures (NTMs) analysis: presents a longlist of NTMs that
the 30 target markets (identified in Section 2.2) impose on imports from the
UK/European Union across the 20 product categories (identified in Section 2.3); and

Section 2.5- Tariff analysis: shows the tariff rates imposed by the 30 target on UK/EU
exports across the 20 product categories.
40
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 2.2. Identification of longlist of target countries
Section 2.2.1. Methodology
The following section of the analysis undertaken identified a longlist of countries that the
UK could target for its agri-food exports. The sample included 101 of the largest nonEU27 economies and excluded markets with which the UK already has strong trade
relationships within Europe and which are deemed as being out of scope for this
engagement (e.g. Switzerland, Norway, Croatia, etc.). This is because Defra‟s focus is on
identifying trade barriers and unlocking exports outside the region, where most of the
barriers exist. The primary research (refer to Chapter 3) confirmed that although there are
some issues within the EU, these are minor and it is outside the EU that British agri-food
exporters face difficulties. As such, only Eastern European non-EU27 countries were
captured by the analysis.
The analysis also excluded some small economies for which trade data was not available
across many of the parameters investigated (e.g. Mayotte, New Caledonia, Cook Islands,
etc.). This exclusion should not have any material impact on the analysis given the size of
those markets. In addition, the analysis has excluded: Libya, Afghanistan, Iran and North
Korea for which trade data was not abundantly available and where political instability and
the diplomatic relationships with the UK create a challenging environment for UK
exporters which is not likely to be easily resolved in the medium term.
Overall, 13 parameters were taken into consideration, with two different scenarios being
formulated and sensitivity analyses being carried out to validate the final longlist of
countries selected. A number of sources were used to compile the required inputs: Trade
Map (for trade data), International Monetary Fund (IMF; for GDP data), CIA (for the Gini
coefficient) and World Bank (for population data). The two main differences between the
two scenarios were:

Scenario 1 accounts for the growth rate in per capita income between 2012-2017 in
percentage terms, whilst Scenario 2 accounts for the absolute levels in the average
income between 2012- 2017; and

Scenario 1 accounts for the growth rate in the total local population between 2010 and
2030 in percentage terms, whilst Scenario 2 accounts for the absolute levels in the total
population between 2010 and 2030.
By formulating the two scenarios, the Grant Thornton team sought to test the different
outputs when accounting for future growth in percentage terms, versus absolute terms.
The parameters considered in each case, the two scenarios investigated, and the weight
assigned to each parameter are presented in the following table.
© 2013 Grant Thornton UK LLP. All rights reserved.
41
Table 2.2.1.1.
Scenarios investigated and weights assigned to the
individual parameters when ranking the target countries
Parameter
UK export growth to target market (excl. whisky), 2007 - 2011
UK exports to target market (excl. whisky), 2011
Population, 2010
Population, 2030
Population growth, 2010 - 2030
UK food market share of target country's total food imports (excl. whisky), 2010
Gini coefficient
GDP per capita, 2012
GDP per capita, 2017
Scenario 1
weights
Scenario 2
weights
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
(0.17)
(0.17)
0.06
0.06
0.11
0.11
0.11
GDP per capita growth, 2012-2017
EU top export markets, 2011
Food import growth in target country, 2006 - 2010
0.11
0.11
0.11
0.11
0.11
Food imports in target country, 2010
0.22
0.22
Total
1.00
1.00
2.2.1.1.
Parameters selected and weights assigned
The parameters chosen captured:

The historic performance of UK agri-food exports to the considered markets
(2007-2011). The analysis includes both the absolute levels of exports in 2011 as well
as their performance during 2007-2011. The analysis excludes the exports of whisky
which has proven a very successful export product for the UK and which as requested
by Defra is out of the engagement's scope. A relatively standard weight was assigned to
UK exports (0.11 for the 2011 levels and 0.11 for growth) because strong historic
export performance may be positive in the context of good trade relationships, but also
it was deemed negative in the context of the current engagement which aims to
identify markets with high trade barriers and strong growth potential;

The market share of UK agri-food exports as a percentage of total agri-food
imports in a certain market (2010). This factor was assigned a relatively high
negative weight (-0.17) to reflect the hypothesis that a high market share indicates a
healthy penetration of UK agri-food products in a specific market and should therefore
be excluded from the analysis. A high penetration most likely indicates relatively low
trade barriers and strong trade relationships between the UK and the importing
country. Even in the presence of high trade barriers, a high penetration would indicate
that the UK industry has found ways of penetrating the market and therefore this
engagement should choose to focus on other countries instead. As mentioned before,
the exports of whisky are excluded from the analysis;

Current population levels (2010) and forecast population in the longer term
(2030). Population was deemed an important parameter because (combined with the
average GDP per capita) it demonstrates the potential market size and total purchasing
power within a market. The current population level indicates the potential in the short
to medium-term as per the Defra requirement to focus on unlocking markets in the
short to medium term. In addition, the population levels for 2030 (long term) are
included in the analysis as an indication of the long term potential across markets. The
two parameters were assigned the same weight to population as with exports (0.22 in
total for both population parameters);
42
© 2013 Grant Thornton UK LLP. All rights reserved.

Current (2012) and forecast (2017) GDP per capita. The analysis incorporates both
current and forecast GDP per capita in the target markets. The two parameters were
assigned a similar weight to average income levels as with population and UK exports
(0.22 in total for both parameters). GDP per capita indicates the average purchasing
power of consumers and was deemed critical to include in the analysis as a proxy for
the demand for high-value Western products that the UK could export. By
incorporating GDP per capita forecast, the analysis captures the medium term outlook
for the target country's economy;

Given that certain nations have very unequal distributions of income, the average GDP
per capita does not effectively capture the average purchasing power of the average
buyer in that market or the size of the middle class population that could afford to buy
high-value Western products. As such, the models tested include the Gini coefficient
which demonstrates the extent of the equality in the income distribution 57. However,
as it is difficult to measure and is not regularly updated across countries, the Gini
coefficient was assigned the smallest weight among all parameters (0.06). As such, for
some countries, the latest available Gini coefficient dates back to the early 2000s and
even the late 1990s (the average year across all countries in the sample was 2006).
However, it was still important to include the Gini coefficient in the model given that
income distribution should not be as sensitive a measure that changes drastically from
year to year and that although out-dated, 10-year-old figures should still provide a
general picture of the present conditions;

EU top export markets (2011). Another input is the rank that each target country
occupied within the EU export markets in 2011. This parameter was assigned a
relatively small weight of 0.11. Given the geographic proximity, product portfolio
similarities and common trade policy with the rest of the EU, this measure should
provide another indication of where the UK is likely to face difficulties in exporting its
products and where it is likely to perform better; and

The historic performance of total agri-food imports at the target market (20072011). The data collected reflects both the absolute level of imports (2011) as well as
the growth of imports (2007-2011). The project team has assigned these factors a
heavier weight (0.33 in total for both parameters). The reason behind doing so is the
hypothesis that total agri-food imports indicate most effectively the potential value of
the opportunity in the medium term for UK agri-food exports. However, a country
might be producing a significant volume/value domestically, but not importing
significantly at present. This would indicate the existence of high trade barriers which
would be difficult to tackle in the short/medium term but may be addressable in the
longer term. The domestic size of the agri-food market for each of the 101 countries
would have been a useful addition to the analysis, as a proxy for the market
opportunity. However, this data is not publicly available.
The Gini coefficient measures the inequality among values of a frequency distribution (for example levels of
income). A Gini coefficient of zero expresses perfect equality where all values are the same (for example, where
everyone has an exactly equal income). A Gini coefficient of one (100 on the percentile scale) expresses
maximal inequality among values (for example where only one person has all the income). Gini coefficient is
commonly used as a measure of inequality of income or wealth and is measured both by the World Bank and
CIA
57
© 2013 Grant Thornton UK LLP. All rights reserved.
43
A sensitivity analysis was conducted to test the impact of each parameter and the weight
assigned to each. It should be noted that some of the parameters chosen may be closely
correlated (e.g. total agri-food imports and GDP per capita, total agri-food imports and
population, UK exports and UK market share as a percentage of total imports, etc.) and
therefore, the sensitivity analysis also tested the de-duplication of their effect on the
ranking of target countries. The results are shown in section 2.2.2.2. This section also
illustrates the different outputs as per the two models and which countries are consistently
excluded or included from the top 30.
2.2.1.2.
Rating system
Each country was then rated with a 1-9 score across each of the parameters discussed.
Given the high number of countries (101), the large scoring range should ensure greater
accuracy in the final rating of the countries and provide a clearer distinction between them.
Overall, three types of rating approaches were included:

Uniformly rating of some parameters across the values present in the sample as in the
case of GDP per capita growth, UK food market share, UK export growth;

Skewed rating according to the sample's distribution as in the case of population, food
imports and UK exports (e.g. for UK exports, rated with 1-5 for values between $0$60m and with 6-9 for values between $60m-$1.6bn. This was due to a small part of
the sample having very high export values therefore, undermining the rest of the
markets. In addition, in the context of the engagement, very large UK exports were not
necessarily a strong positive given that they may indicate lower trade barriers or better
trade relationships); and

Skewed rating to fit the project context. For example in the case of GDP per capita, in
order to account for a certain income threshold beyond which consumers do not
spend significantly more on food and drink products (given the predominantly staple
nature of the agri-food industry). For this purpose $25,000 was taken as the threshold
based on the income levels of some EU27 Eastern European nations. Based on this
approach, countries were rated 1-6 between $0-$25,000 average income and 6-9 above
$25,000. As such the model still captures wealthy and rich nations where consumers
will be focused on buying primarily premium food and drink products, which is
important and relevant to the engagement given that many of the UK agri-food
products exported will be priced higher than in the UK to take into account the
additional costs associated with exporting (e.g. customised packaging or recipe to meet
local regulations, transportation, listing fees, margin given to distributors for firms that
do not operate a direct sales model).
44
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 2.2.2. Analysis
2.2.2.1.
Scenario results
The table below presents the top 32 countries' ranking resulting from the rating system
developed under Scenarios 1 & 2. The aim of this exercise was to identify a final longlist of
30 countries. In both scenarios, Syria falls within the top 30. Given the political turmoil in
the country and the strained diplomatic relationships with the EU it was deemed
appropriate to replace it with one of the countries ranking below it.
Table 2.2.2.1.
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Country ranking under Scenarios 1 & 2
Scenario 1 - Country
Scenario 1 - Rating Scenario 2 - Country
China
USA
Japan
Brazil
Russia
Hong Kong
India
Saudi Arabia
Canada
Singapore
Turkey
Mexico
7.17
Indonesia
Malaysia
Rep. of Korea
4.81
UAE
South Africa
Thailand
Paraguay
Chile
Australia
4.53
Egypt
Kenya
Colombia
4.03
Algeria
Macao
Nigeria
Rwanda
Azerbaijan
Syria
3.89
Argentina
Lebanon
3.58
© 2013 Grant Thornton UK LLP. All rights reserved.
6.61
5.94
5.87
5.86
5.79
5.46
5.23
5.16
5.03
5.00
4.84
4.70
4.57
4.44
4.44
4.21
4.19
4.09
4.02
3.97
3.82
3.67
3.62
3.60
3.58
3.52
Scenario 2 - Rating
USA
Japan
China
Brazil
Russia
Canada
Hong Kong
Singapore
Saudi Arabia
India
Rep. of Korea
Mexico
7.72
Turkey
UAE
South Africa
5.00
Australia
Thailand
Malaysia
Indonesia
Chile
Colombia
4.64
Egypt
Algeria
Argentina
3.92
Israel
Nigeria
Paraguay
Oman
Macao
Syria
3.58
New Zealand
Pakistan
3.36
7.39
7.28
6.42
6.30
5.93
5.90
5.59
5.57
5.12
5.12
5.07
4.98
4.67
4.56
4.48
4.48
4.19
3.97
3.78
3.58
3.56
3.43
3.41
3.38
3.36
3.33
45
The two scenarios are very similar in terms of the countries they have captured. They
present a good mix of developed and emerging markets (they both capture the BRICs in
the top 10) and dispersed geographically around the world. The significant differences are
seen in the lower ranking countries in the lists, where Scenario 1 captures Kenya, Rwanda
and Azerbaijan, whilst Scenario 2 captures Argentina, Israel and Oman. In addition, given
Syria's rank at the 30th position, the country ranking below it replaced Syria in the top 30
markets, i.e. Argentina in Scenario 1 and New Zealand in Scenario 2 were chosen instead
of Syria.
Based on discussions with the Defra, it was agreed that Scenario 2 captured a more
appropriate set of countries than Scenario 1. Nevertheless, the team carried out a
sensitivity analysis to assess which Scenario was more robust and therefore better suited to
Defra's needs (as well as to assess the impact of the individual parameters and the weights
assigned to each).
2.2.2.2.
Sensitivity analysis
Sensitivity analyses were undertaken for both Scenarios for each group of parameters
presented in section 2.2.1.1 (e.g. for the UK exports overall by accounting for both historic
growth and absolute values in 2011, rather than each one individually) as shown below:
Table 2.2.2.2.1.
Sensitivity analysis - weights assigned to the individual
parameters on a case by case basis
3 - UK 4 - GDP
market
per
share
capita
5 - Food
6 - Food
imports
imports
(value (value and
only)
growth)
7 - Food
imports &
EU top
markets
1 - UK
exports
2Population
UK export growth to target
market (excl. whisky), 20072011
UK exports to target market
(excl. whisky), 2011
Population, 2010
0.00
0.14
0.10
0.15
0.14
0.17
0.20
0.00
0.14
0.10
0.15
0.14
0.17
0.20
0.14
0.00
0.10
0.15
0.14
0.17
0.20
Population, 2030 / Population
growth, 2010-2030
UK food market share of target
country's total food imports
(excl. whisky), 2010
Gini coefficient
0.14
0.00
0.10
0.15
0.14
0.17
0.20
(0.21)
(0.21)
0.00
(0.23)
(0.21)
(0.25)
(0.30)
0.07
0.07
0.05
0.00
0.07
0.08
0.10
GDP per capita, 2012
0.14
0.14
0.10
0.00
0.14
0.17
0.20
GDP per capita, 2017 / GDP
per capita growth, 2012-2017
EU top export markets, 2011
0.14
0.14
0.10
0.00
0.14
0.17
0.20
0.14
0.14
0.10
0.15
0.14
0.17
0.00
Food import growth at target
country, 2006-2010
Food imports at target country,
2010
0.14
0.14
0.10
0.15
0.14
0.00
0.00
0.29
0.29
0.19
0.31
0.00
0.00
0.00
Total
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Parameter
The weighting for each group of parameters was in turn switched to zero and the weight
that was previously allocated to these parameters (in Section 2.2.1.1.) was distributed
amongst the remaining parameters.
The two following tables attached highlight the major differences that occurred under the
sensitivity analysis for the top 30 countries.
46
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22
Lebanon
23
Israel
23
Guatemala
26
Cambodia
26
Cambodia
26
Cambodia
Rank
Country
added
7 - Food imports
& EU top markets
Rank
Country
added
Rank
Country
added
5 - Food imports 6 - Food imports
(value only)
(value and
growth)
Rank
Country
added
3 - UK
4 - GDP per
market share capita
Rank
Rank
Country
added
Rank
Country
added
Panama
Impact of sensitivity analysis on the top 30 under Scenario 1
2Population
1 - UK
exports
Country
added
Table 2.2.2.2.2.
12
30
Uganda
25
Peru
26
Lebanon
28
Nepal
26
Domin. Rep. 27
Pakistan
29
Madagascar
29
29
Uganda
30
Australia
21 Nigeria
27 Paraguay
19 Australia
21 Nigeria
Egypt
22 Rwanda
28 Chile
20 Macao
Algeria
25 Syria
30 Colombia
24 Azerbaijan
Macao
26
Rwanda
Nigeria
27
Syria
Rwanda
28
Azerbaijan
29
Syria
30
30 Australia
21
26
Egypt
22
29
Algeria
25
28
Nigeria
27
30
Syria
30
© 2013 Grant Thornton UK LLP. All rights reserved.
27 Syria
Rank
Sri Lanka
Rank
28
Country
removed
Costa Rica
Rank
27 Pakistan
Country
removed
28 Ukraine
Country
removed
25 Ukraine
Rank
Honduras
Country
removed
23
Rank
Bolivia
Country
removed
29
Rank
24 Argentina
Country
removed
26 Ghana
Rank
24 Costa Rica
Country
removed
Guatemala
47
Impact of sensitivity analysis on the top 30 under Scenario 2
25
Ukraine
25
Kenya
28
New
Zealand
27
Bahrain
27
Pakistan
26
Ukraine
29
Bahrain
27
22
Colombia
21
Israel
25
Paraguay
27
Nigeria
26
Argentina
24
Oman
28
Macao
29
Syria
30
Paraguay
27
Macao
29
Oman
28
Rank
Egypt
Rank
26
Rank
Nigeria
Syria
Syria
30
Rank
Country
added
Rank
Country
added
Rank
30
27
New
Zealand
25
Nepal
30
Rank
Lebanon
New
Zealand
Country
removed
25
30
Rank
Peru
New
Zealand
Country
removed
23
Rank
Pakistan
Country
removed
24
Country
removed
New
Zealand
Rank
23
Country
removed
New
Zealand
Country
removed
24
Country
removed
Pakistan
Country
added
5 - Food
6 - Food
7 - Food
imports (value imports (value imports & EU
top markets
only)
and growth)
Rank
4 - GDP per
capita
Country
added
3 - UK market
share
Rank
Rank
2 - Population
Country
added
Rank
Country
added
1 - UK exports
Country
added
Table 2.2.2.2.3.
Algeria
23
Syria
30
After running the sensitivity analysis, it became evident that Scenario 2 (which accounted
for absolute values versus growth rates for GDP per capita and population forecasts as in
Scenario 1) was more stable than Scenario 1. Under the sensitivity analysis for UK exports,
UK market share and Food imports & EU top markets, Scenario 2 remains less affected
than Scenario 1 where more changes are taking place in the top 30 ranking.
It was seen that the food imports parameters (both for absolute value and historic growth),
which had the biggest attributed weight, did not impact the analysis heavily, as only one
change occurred when food imports were taken out of the variables under both Scenarios.
Based on the results of the sensitivity analysis and the country ranking from section 2.2.2.1,
Scenario 2 was selected. It is worth noting that New Zealand, which was included in the
top 30 in section 2.2.2.1 (even though it ranked 31st) in order to replace Syria, was added
to the top 30 countries under six of the seven cases investigated by the sensitivity analysis.
No other country made such a consistent addition to the top 30 with Ukraine, Bahrain and
Pakistan each appearing only twice within the seven cases investigated. In terms of the
countries that were being removed from the top 30, Syria was the most consistent- in four
out of the seven cases. Argentina, Paraguay, Macao and Oman were eliminated twice but
this was not deemed frequent enough to exclude them from the original ranking.
Section 2.2.3. Final country longlist and justification
As mentioned in section 2.2.2.2, the results of the sensitivity analysis indicated that
Scenario 2 was the more appropriate in the selection of the top target countries. The
following table shows the final list of the 30 countries selected by Scenario 2, which
includes New Zealand but excludes Syria. It also includes a brief commentary as to each
country's 'strengths' and 'weaknesses' based on their performance as per Scenario 2. This
commentary provides the qualitative justification for why each country is seen as a
potential target market for UK agri-food exports.
48
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Table 2.2.3.1.
Final list of top 30 countries selected
Rank
Country
1
USA
2
Japan
3
China
4
Brazil
5
Russia
6
Canada
7
Hong Kong
8
Singapore
9
Saudi Arabia
10
India
11
Rep. of Korea
12
Mexico
13
Turkey
14
UAE
15
South Africa
16
Australia
17
Thailand
18
Malaysia
19
Indonesia
Comment
Large and wealthy market where the UK already exports large quantities of agri-food
products
The second largest food importing market, but in which the UK only has 0.3% share
of the total agri food imports, indicating under-penetration
Large and fast growing market with significant opportunities for agri-food exporters
around the world, where the UK only has 0.2% share of the total agri food imports.
Agri-food imports have been growing very strongly since 2006 indicating potential
for the UK to tap into
Brazil currently imports much less food than its peers, but is also a large market
where UK exports have been growing strongly over the last couple of years.
However, distribution of income remains very unequal. Agri-food imports have
been growing very strongly since 2006
A BRIC market located geographically close to the UK which is also the EU's
second largest export market. However, UK exports declined during the downturn
and the UK market share among imports indicates there is still room for further
penetration
A wealthy market with healthy income distribution and good growth prospects
Even though the goods sent to Hong Kong are very likely re-exported elsewhere,
there has been strong growth of UK agri-food exports over the last few years. In
addition, it's a wealthy, fast growing market and a top EU export destination (the
EU's 7th largest market)
Similarly with Hong Kong, the goods sent to Singapore are very likely re-exported
elsewhere. However, exports to Singapore have been growing strongly and so have
Singapore's global food imports. It is a small, but wealthy country
Despite exporting a significant value of agri-food products, the UK only has a very
small share of the total food imports of Saudi Arabia. In addition, the forecast large
population growth indicates further potential opportunities for agri-food exports
A difficult to enter market (the EU's 42nd largest market) with low average income
but vast population and fast growth projections, where the UK has not managed to
penetrate effectively yet. Agri food imports have been growing very strongly since
2006
The EU's 14th largest market has recently entered into an FTA with the EU which is
expected to further free and increase the value of bilateral agri-food trade. It is a
large market with good average income which is very equally distributed across its
population. Even though UK exports have been growing fast, they still account for
0.3% share of the total imports
A large market where UK exports have not been performing well during the
downturn and where the total share of agri food imports remains particularly small,
indicating under-penetration
The EU's 10th largest market, where average income is expected to grow annually by
8% over the next 5 years. Even though UK exports have been growing, they are
lagging the country's historic strong growth of total agri food imports and there is
still room for further penetration
A rich state where UK exports already have a 1.7% share of total agri food imports.
However, in the past 5 years, UK exports' performance has been far worse than the
overall UAE increase in agri food imports
A large Commonwealth country, with a 4% growth forecast in its average income
levels over the next 5 years, where the UK already has a 2% share of total agri food
imports despite the distant location. UK exports have also been growing faster than
the country's the total imports
The EU's 11th largest market is a very wealthy nation with strong population growth
forecast. However, UK exports already have a 2.1% share of total imports and have
been growing broadly in line with them
A large market with relatively small average income levels and large inequalities in
the distribution of income. The UK has a small share of agri food imports and UK
exports have been growing slower that the country's total imports
Smaller market than Thailand but with almost double the levels of average income.
Strong growth expected both for the population and income levels. UK exports only
have 0.4% share of the total imports and have been stagnant in the last few years
compared to the total imports which have been growing at 17% annually
A very large country with low average income which is expected to grow at a rate of
13% p.a. in the next 5 years. UK exports have a very small share and have been
suffering compared to the 21% annual growth experienced by the total agri food
imports
© 2013 Grant Thornton UK LLP. All rights reserved.
49
Rank
Country
20
Chile
21
Colombia
22
Egypt
23
Algeria
24
Argentina
25
Israel
26
Nigeria
27
Paraguay
28
Oman
29
Macao
30
New Zealand
50
Comment
One of the wealthiest Latin American markets which has been growing its imports
by 16% p.a. over the last 5 years whilst UK exports have been growing much more
slowly and still have a very small share of the imports
Large market with good population growth expected where the UK only has 0.1%
share of the total imports. UK exports to the country have been growing in line with
the agri food imports
Recent political turmoil may act as a deterrent to the growth forecast for the
medium term. However, Egypt remains a large market with strong forecast
population growth (but small average income). Since 2007, UK exports have been
growing strongly, above the average level of imports
The EU's 6th largest market with a relatively strong population growth forecast but
low average income. UK exports have still not penetrated the market strongly but
have been growing faster than the total agri food imports
A healthy growing market, but geographically distant. UK exports have outpaced
total imports, but UK products still have a very small share of the imports. Also,
strained political relationships may have to be taken into account in the medium
term
A small but wealthy market with good income distribution, where the UK already
has a 2.1% share of total imports. However, UK agri-food exports have been
growing at slower rates than the total Israeli imports
The EU's 22nd largest market has a very large population with a small GDP per
capita which is expected to grow at healthy rates in the next 5 years. The UK already
has 2.5% share of the total agri-food imports
A significantly underpenetrated market for the UK, where GDP per capita is
expected to grow at 8% in the next 5 years. Paraguay's imports have been growing at
a CAGR of 23% between 2006-2010; UK exports have grown at a faster rate
A small country with good population growth expected where UK goods have been
growing much slower than the fast growth of total imports and where the UK
products still have a small share of the total imports
A small but wealthy state where UK exports have been growing fast and which
already have 2.1% share of the total agri food imports. Good population growth is
expected but from a small base whilst agri-food imports have been growing strongly
since 2006
A small but wealthy Commonwealth market with good growth projections, but
located far from the UK. During the last 4 years UK exports have grown in line with
total New Zealand imports while UK exports have managed to penetrate 1.3% of
the agri-food market (average)
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 2.3. Identification of longlist of key product
categories
Section 2.3.1. Methodology
This section of the analysis identifies the key agri-food product categories that the UK
should focus on exporting. This analysis has been performed at the 4-code level HS
classification system, which breaks products down to 184 product categories and fall under
22 broad agri-food categories (at the 2-code HS level).
As mentioned previously, the analysis excluded whisky (and more specifically the 2208
Spirits category) as this falls outside of the scope set by Defra. This is because whisky is the
most successful UK export and the Scottish Whisky Association has already achieved
notable successes for its members. Defra is of course keen to protect the Scotch Whisky
brand through ensuring its authenticity.
The product category analysis evaluated two scenarios which included two different
parameters and aimed to compile the longlist of products that the UK should focus its
exports on. The table below highlights the two scenarios investigated, the parameters
considered in each case and the weight assigned to each parameter.
Table 2.3.1.1.
Scenarios investigated and weights assigned to the
individual parameters
Parameter
Agri-food RCA, 2011
Scenario 1
0.25
UK exports as % of world exports, 2011
Scenario 2
0.25
World imports, 2011
0.17
0.17
UK exports to EU27, 2011
0.25
0.25
UK worldwide exports (excl. EU27), 2011
0.33
0.33
Total
1.00
1.00
To ensure consistency the data was sourced from Trade Map.
The main difference between the two scenarios is that Scenario 1 calculates the
comparative advantage the UK has in a certain agri-food product category based on the
Revealed Comparative Advantage (RCA) measure as calculated by the Balassa index. In
contrast, Scenario 2 accounts for the share of the UK exports across that product category
as a percentage of the world exports of the specific product. The motivation for
formulating the two scenarios was to test the different outputs when different measures of
'comparative advantage' were used. For more details please refer to section 2.3.1.1.
© 2013 Grant Thornton UK LLP. All rights reserved.
51
2.3.1.1.
Parameters selected and weights assigned
The parameters chosen:

Revealed Comparative Advantage (RCA) across product category as calculated
by the Balassa Index. The Balassa Index is a widely accepted measure that has been
applied in numerous reports (e.g. World Bank, United Nations) and academic
publications (e.g. van Hulst et al., 1991; Lim, 1997) as a measure of international trade
specialisation. It is expressed as follows:
RCA = (Xij / Xit) / (Xnj / Xnt)
where X represents exports, is a country, j is a commodity (or industry), t is a set of
commodities (or industries) and n is a set of countries. RCA measures a country‟s
exports of a commodity (or industry) relative to its total exports and to the
corresponding exports of a set of countries. A comparative advantage is 'revealed', if
RCA >1. If RCA is less than unity, the country is said to have a comparative
disadvantage in the commodity / industry.58 In this engagement the RCA is calculated
by looking into the absolute 2011 values of exports across a certain agri-food product
category and comparing it with the total exports of all agri-food products at the UK
and world level. In the model, this factor has average 0.25 weight but a zero rating (on
a 0-10 scale) for all products with RCA<1. This way, despite the relatively small weight
assigned, the products where the UK has a comparative disadvantage are excluded.
This allows the isolation of most products with a comparative disadvantage and
distinguishes amongst products that have a 'revealed' comparative advantage based on
the remaining parameters investigated;

UK exports across products as a percentage of world exports of that product
(2011). This parameter is used in Scenario 2 as an alternative to RCA in calculating the
'comparative advantage' the UK has across products with the same 0.25 weight
assigned to RCA in Scenario 1;

World imports across product categories (2011). Despite not being a crucial
parameter (and therefore the reason for assigning it a small weight of 0.17), it was
important to include it as an indication of the world demand (in value terms) across the
different products, as it highlights the level of the opportunity for UK agri-food
products. As mentioned previously, world consumption across products would have
been a better measure of the world demand, but this data is not available via publicly
accessible sources; and

UK exports across different agri-food products (2011). Exports are split into
exports to the EU27 and exports outside the EU27 with 0.25 and 0.33 weights
respectively. In 2011, about 73% of UK agri-food exports were directed to EU27
countries in 2011. As such, the exports to EU27 nations should provide a good
indication of which UK products are in demand and which products should be able to
perform strongly outside the EU. However, given the long distances involved when
exporting outside the EU, the perishable and staple nature of agri-food products and
the different consumer needs and preferences outside the EU, a greater weight is
placed on the UK agri-food exports to non-EU markets.
Laursen K. (1998), Revealed Comparative Advantage and the Alternatives as Measures of International
Specialisation, December 1998, Danish Research Unit for Industrial Dynamics
58
Utkulu U., Seymen D. (2004), Revealed Comparative Advantage and Competitiveness: Evidence for Turkey
vis-à-vis the EU/15, Dokuz Eylül University, Economics Department, İzmir
52
© 2013 Grant Thornton UK LLP. All rights reserved.
As with the countries' longlist, a sensitivity analysis was conducted to test the impact of
each parameter and the weightings assigned. The results are shown in section 2.3.2.2.
2.3.1.2.
Rating system
Each product was rated with a 0-10 score across each of the parameters discussed. A large
scoring range ensured greater accuracy in the final rating of the countries and a better
distinction between them. Overall, there are three types of rating approaches:

Rate uniformly across values as in the case of UK exports as a percentage of
world exports;

Skew the rating according to the sample's distribution as in the case of world imports
across different products and for UK exports. In the case of world imports, 1-6 ratings
for values between $0-$8bn and with 7-10 for values between $8bn-$52bn. This was
because a small part of the products had very high world import values and therefore
undermined the rest of the products. In the case of UK exports, each product category
is first ranked by value and then rated between 0-10 according to its rank; and

Skew the rating according to the context of the analysis as in the case of RCAs. A
product category was rated with a zero if it had a comparative disadvantage and with 810 for value of 1 or above (i.e. 'revealed comparative advantage'). As a result, most of
the product categories with a comparative disadvantage are identified and a small
distinction is made amongst products with different degrees of comparative advantage
(e.g. a score of 8 for RCA between 1 and 2, a 9 for RCA between 2 and 4 and 10 for
RCA above 4 given that only a small sample of the product portfolio had RCA
above 4).
Section 2.3.2. Analysis
2.3.2.1.
Scenario results
The table below shows the top 20 product categories based on the analysis undertaken
under Scenarios 1 & 2 and the total rating of each product category:
Table 2.3.2.1.
Product ranking under Scenarios 1 & 2
Scenario 1
Scenario 2
Product code and label
'2208
'1905
Spirits, liqueurs, other spirit
beverages, alcoholic
preparations (excl. whisky)
Bread, biscuits, wafers,
cakes and pastries
Rating Product code and label
Rating
9.78
'2208
Spirits, liqueurs, other spirit
beverages, alcoholic preparations
(excl. whisky)
9.78
9.66
'2203
Beer made from malt
9.51
'2203
Beer made from malt
9.51
'1905
Bread, biscuits, wafers, cakes and
pastries
9.16
'2106
Food preparations, NES
9.45
'0302
Fish, fresh, whole
8.92
'2204
Wine of fresh grapes
9.25
'1904
Breakfast cereals & cereal bars
8.85
'1806
Chocolate and other food
preparations containing
cocoa
9.24
'2106
Food preparations, NES
8.70
'0302
Fish, fresh, whole
9.17
'0101
Live horses, asses, mules and
hinnies
8.62
'0207
Meat & edible offal of
poultry meat
9.12
'0204
Meat of sheep or goats - fresh,
chilled or frozen
8.56
'0406
Cheese and curd
9.06
'1806
Chocolate and other food
preparations containing cocoa
8.49
'2202
Non-alcoholic beverages
(excl. water, fruit or
8.87
'2204
Wine of fresh grapes
8.25
© 2013 Grant Thornton UK LLP. All rights reserved.
53
Scenario 1
Scenario 2
Product code and label
vegetable juices)
Breakfast cereals & cereal
'1904
bars
'0201
'0101
'0204
'1901
Meat of bovine animals,
fresh or chilled
Live horses, asses, mules
and hinnies
Meat of sheep or goats fresh, chilled or frozen
Malt extract; food
preparations of flour, meal,
starch or malt extract
Rating Product code and label
Rating
8.85
'2202
Non-alcoholic beverages (excl.
water, fruit or vegetable juices)
8.12
8.70
'2101
Extracts essences & concentrates
of coffee and tea
8.11
8.62
'0406
Cheese and curd
8.06
8.56
'0201
Meat of bovine animals, fresh or
chilled
7.95
8.53
'0902
Tea
7.88
'0306
Crustaceans
8.50
'0207
Meat & edible offal of poultry
meat
7.87
'2103
Sauces mixed condiments &
mixed seasonings
8.41
'0105
Live poultry
7.76
'0902
Tea
8.38
'0401
Milk and cream, not concentrated
nor sweetened
7.66
8.36
'2103
Sauces mixed condiments &
mixed seasonings
7.66
8.27
'0304
Fish fillets and pieces, fresh,
chilled or frozen
7.62
'2101
'2005
Extracts essences &
concentrates of coffee and
tea
Prepared or preserved
vegetables NES (excl.
frozen)
The two scenarios give largely similar results with three differences in the products
accounted for Scenario 1 (which is based on the RCA index rather than the UK exports'
share of world imports as in Scenario 2) adds in Malt extracts, Crustaceans and Prepared or
preserved vegetables not elsewhere specified, while it does not include Live poultry, Milk
and cream or Fish fillets and pieces.
Scenario 1 was the preferred option supported by:

The widely recognised use of the RCA index when trying to measure the comparative
advantage a country has across a certain product (compared to the use of a country's
exports' share of world imports);

The fact that using the UK exports' share of world imports as a measure of
comparative advantage was a direct duplication of other measures accounted for by in
the model (i.e. world imports and UK exports to EU27 and non-EU27 nations). RCA
also accounts for these parameters but includes other factors as well; and

There were relatively small differences in the outputs of the two scenarios.
54
© 2013 Grant Thornton UK LLP. All rights reserved.
2.3.2.2.
Sensitivity analysis
Having chosen Scenario 1, a sensitivity analysis was carried out for each parameter
presented in section 2.3.1.1 by switching weights as per the distribution shown below:
Table 2.3.2.2.1.
Sensitivity analysis on Scenario 1 - weights assigned to the
individual parameters on a case by case basis
1 - RCA
2 - World
imports
3 - EU27
exports
4 - Worldwide
exports (excl.
EU27)
5 - Worldwide
exports (incl.
EU27)
0.25
0.00
0.30
0.33
0.38
0.60
0.17
0.22
0.00
0.22
0.25
0.40
0.25
0.33
0.30
0.00
0.38
0.00
0.33
0.44
0.40
0.44
0.00
0.00
1.00
1.00
1.00
1.00
1.00
1.00
Basic/initial
scenario
Agri-food RCA
World imports
Parameter
UK exports to
EU27
UK worldwide
exports (excl.
EU27)
Total
The weight of each parameter was in turn reduced to zero and its weight reallocated to the
remaining parameters based on the weight assigned to them at the beginning (i.e. the
'basic/initial scenario').
The following table highlights the major differences that occurred through the sensitivity
analysis in the ranking of the top 20 product categories:
© 2013 Grant Thornton UK LLP. All rights reserved.
55
Rank
Products
added
Milk and cream,
not
concentrated
nor sweetened
Prepared or
preserved meat,
meat offal or
blood, NES
Milk and cream,
not
15
concentrated
nor sweetened
Prepared or
preserved meat,
17
meat offal or
blood, NES
Molluscs
18 Molluscs
11
Meat of bovine
animals
Extracts essences
12 & concentrates
of coffee and tea
Live horses,
19 asses, mules and
hinnies
Sauces mixed
condiments &
mixed
seasonings
Live horses,
asses, mules and
hinnies
13 Crustaceans
Meat of sheep
or goats
14
Tea
Sauces mixed
condiments &
mixed
seasonings
17
Prepared or
preserved
vegetables NES
(excl. frozen)
Tea
18
16
15
18
19
Rank
Products
removed
Rank
Products
removed
Rank
Rank
17
56
Rank
Products
added
Rank
Products
added
Rank
20
12
or not broken
14
Coffee
Extracts
essences &
concentrates of
coffee and tea
Prepared or
preserved
vegetables NES
(excl. frozen)
Rape or colza
12 seeds, whether
or not broken
13
15
Products
removed
Rape or colza
20 seeds, whether
12
Meat of swine,
fresh, chilled or
frozen
Breakfast
cereals & cereal
bars
Sugar
confectionery
18 (incl. white
choc), not
containing cocoa
Products
removed
Cane or beet
sugar and
chemically pure
sucrose
Fish, frozen,
whole
Milk and cream,
concentrated or
sweetened
11 Live poultry
4 - Worldwide exports 5 - Worldwide exports
(incl. EU27)
(excl. EU27)
3 - EU27 exports
Rank
Fish fillets and
pieces
10 Potatoes
Products
removed
Wheat and
meslin
2 - World imports
Rank
Products
added
1 - RCA
Impact of sensitivity analysis on the top 20 under Scenario 1
Products
added
Table 2.3.2.2.2.
Live horses,
13 asses, mules
13
and hinnies
Sauces mixed
condiments &
17
mixed
seasonings
Extracts
essences &
18
concentrates of
coffee and tea
Prepared or
preserved
20
vegetables NES
(excl. frozen)
17
19
20
19
20
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Post the sensitivity analysis, it became evident that the model was particularly sensitive to
RCA, without which seven product categories were eliminated from the top 20. These are
primarily areas where the UK has a very strong comparative advantage, but for which the
world imports are not as large (e.g. breakfast cereals, live horses) or that the UK does not
currently export as heavily in absolute value terms (e.g. extracts essences & concentrates of
coffee and tea, prepared or preserved vegetables).
With the exception of RCA, the model does not appear to be as sensitive to the rest of the
parameters. However, what stood out from the sensitivity analysis was the re-appearance
of 'Milk and cream, concentrated or sweetened' products in three out of the five cases
investigated; primarily at the expense of 'Prepared or preserved vegetables NES (excl.
frozen)'. As such, 'Milk and cream, concentrated or sweetened' products was added to the
top 20 and 'Prepared or preserved vegetables NES (excl. frozen)' products were removed
although they ranked 20th under Scenario 1.
Section 2.3.3. Final product longlist
Based on the analysis carried out across the two different scenarios and the sensitivity
analysis on Scenario 1, the final list of top 20 target products was compiled and is
presented in the table below.
Table 2.3.3.1.
Final list of top 20 products selected
Product
category
code Degree of processing
Product category label
Rating
in terms
of EU27
exports
Rating in
terms of
worldwide
Rating
exports (excl. for world
EU27) imports
UK
RCA
rating
'2208
Highly processed
Spirits, liqueurs, other spirit
beverages, alcoholic
preparations (EXCLUDING
WHISKY)
9.8
10.0
9.0
10.0
'1905
Highly processed
Bread, biscuits, wafers, cakes
and pastries
10.0
9.7
10.0
9.0
'2203
Highly processed
Beer made from malt
9.7
9.8
8.0
10.0
'2106
Highly processed
Food preparations, NES
9.9
9.9
10.0
8.0
'2204
Highly processed
Wine of fresh grapes
9.1
9.9
10.0
8.0
'1806
Highly processed
Chocolate and other food
preparations containing cocoa
9.4
9.7
10.0
8.0
'0302
Unprocessed
Fish, fresh, whole
9.2
9.8
8.0
9.0
'0207
Lightly processed
Meat & edible offal of poultry
meat
9.2
9.5
10.0
8.0
'0406
Lightly processed
Cheese and curd
9.6
9.0
10.0
8.0
'2202
Lightly processed
Non-alcoholic beverages (excl.
water, fruit or vegetable juices
and mineral water)
9.6
8.7
8.0
9.0
'1904
Highly processed
Breakfast cereals & cereal bars
9.5
9.4
5.0
10.0
'0201
Lightly processed
Meat of bovine animals, fresh
or chilled
9.8
7.7
10.0
8.0
'0101
Unprocessed
Live horses, asses, mules and
hinnies
9.0
9.6
4.0
10.0
'0204
Lightly processed
Meat of sheep or goats - fresh,
chilled or frozen
9.7
7.9
6.0
10.0
'1901
Highly processed
Malt extract; food preparations
of flour, meal, starch or malt
extract
8.5
9.2
8.0
8.0
© 2013 Grant Thornton UK LLP. All rights reserved.
57
Product
category
code Degree of processing
Rating
in terms
of EU27
exports
Product category label
Rating in
terms of
worldwide
Rating
exports (excl. for world
EU27) imports
UK
RCA
rating
'0306
Lightly processed
Crustaceans
9.3
8.0
9.0
8.0
'2103
Highly processed
Sauces mixed condiments &
mixed seasonings
8.8
9.1
7.0
8.0
'0902
Lightly processed
Tea
7.8
9.5
6.0
9.0
'2101
Highly processed
Extracts essences &
concentrates of coffee and tea
9.1
8.5
6.0
9.0
'0401
Lightly processed
Milk and cream, not
concentrated nor sweetened
9.5
5.7
7.0
9.0
Overall, the top 20 rank of products is a broad mixture, with high RCA products, products
which are heavily exported by the UK in absolute terms and products which are heavily in
demand as measured by world imports. Out of the 20 product categories, 10 are highly
processed, 8 lightly processed and 2 unprocessed.
58
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Section 2.4. Non-Tariff Measures (NTMs) analysis
This section covers an analysis of the NTMs that apply to the selected 30 target countries
and 20 key product categories. The data source used to identify NTMs was the European
Commission Market Access Database (MADB), which based on discussions with the
WTO holds the most holistic information on NTMs that the European Union exporters
are facing around the world. This research returned 157 barriers applied on the EU by 26
of the 30 key countries with regards to agri-food products and horizontally (i.e. across
industries, including goods and services); the 4 countries left out from the database were
Macao, Oman, Singapore and UAE. Most of these 157 barriers apply to more than one
4-code level food category with some applying to all agri-food products, some applying at
the 2-code level and others being across different categories. All of these barriers are
currently still 'open' and have not been addressed yet, or the EU is currently monitoring
their resolution.
The NTMs from MADB were supplemented with additional ones from the US
International Trade Commission. To do so, WITS, a database provided by World Bank,
was used. However, WITS data appears to be out of date for a number of countries (e.g.
Canada's and USA's data was last collected in 2006, whilst for Russia it was collected in
1997), and it is limited in scope for several countries (e.g. it only includes price control
measures for Canada and Turkey with no data on SPS, TBT or other measures). In
addition, where data is available, WITS only provides a short, generic description per
NTM, which did not provide a clear understanding of the measure in place. For these
reasons, WITS was disregarded in the compilation process.
The mapping of barriers was also based on investigating the various databases provided by
WTO on TBT, SPS, safeguard measures, etc. These databases appeared to be very narrow
in focus and also could not provide a view as to whether a barrier has been removed or
whether it remained in place. For example, only 4 SPS barriers and 1 TBT barrier across
the 30 key countries were obtained with an unknown resolution status. From discussions
with WTO, it appeared that members rarely report such issues to the WTO and do not
update the WTO on the progress made regarding their resolution. For these reasons, a
decision was made to disregard these databases.
Separately to the above databases, the WTO also publishes Trade Policy Reviews (TPRs)
on each country. These are typically long reports that contain detailed information on the
trade profile of each country and the measures they have recently been taking. The US
International Trade Commission (USITC) published in 2009 the Compilation of Reported
Non-Tariff Measures (CoRe NTMs) Database where it compiled all the information from
these TPRs in addition to the information provided by MADB in order to build up a
comprehensive view of the NTMs applied by countries around the world. Given the
resource intensive nature of analysing all the reports and the impact it would have had on
the timeline to deliver the project to Defra, it was decided to make use of USITC's NTMs
identified through WTO's TPRs in 2009 for the key 30 countries.
Following this compilation, another 141 NTMs were added and the country coverage
extended for all 30 of the key countries with regards to agri-food products and horizontally
(bringing the total number of agri-food barriers for the 30 countries to 298). As mentioned
already, these NTMs may apply across several 4-code level product categories rather than
on a single one. Whilst a direct country comparison based on the number of NTMs
applied is not possible (given the difficulty of evaluating the impact of each NTM in a
straightforward manner), it is clear that SPS measures are by far the most widely used ones,
which was not surprising given the SPS measures apply mostly to agri-food products.
Other measures that appear frequently were export and import related measures,
bureaucratic measures (e.g. registration, documentation and customs procedures) and
© 2013 Grant Thornton UK LLP. All rights reserved.
59
TBTs (e.g. standards, technical requirements, testing, labelling, certification). These results
are in line with the Nicita & Gourdon study mentioned in the literature review which
found that 60% of agri-food trade were affected by SPS, while across all sectors c. 30% of
trade was affected by technical barriers.
60
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Section 2.5. Tariff analysis
In order to map the tariff barriers the MacMap database was used to download the latest
tariff barriers applied by the 30 key target countries to the 20 product categories where the
UK has a comparative advantage. An analysis of the tariff levels applied showed that on
average, across all countries and product categories, the tariff level applied is 32.0%. HS
code 0101 "Live horses, asses, mules and hinnies" had the lowest tariff level of 4.7%,
followed by HS code 0306 "Crustaceans" with 9.1% while the highest levels of tariffs were
applied to alcoholic beverages ranging from 74.9% (for beer) to 130.0% (for spirits).
Alcoholic beverage tariffs tend to be at the higher end of the spectrum for Muslim
countries, while New Zealand, Canada and US had tariffs between 0-5%.
Across countries, nations such as Canada and Turkey had a mix of very high and very low
tariffs. For example, Canada applies a 305.4% tariff to products in HS code 0401 "milk and
cream not concentrated or sweetened" and 335.1% to products in HS code 0406 "cheese
and curd", while five of the 20 products categories had no tariffs. (0101 "live horses, asses,
mules and hinnies", 0302 "fresh fish whole", 0902 "tea", 2101 " extracts essences &
concentrates of coffee and tea" and 2203 "beer made from malt"). Similarly Turkey, applies
179.2% tariff on products in HS code 0204 "Meat of sheep or goats".
In contrast, countries like Algeria and India apply a consistent tariff of c. 30% across
products (with the exception of a few products), while Macao, Hong Kong and Singapore
did not apply tariffs, with the exception of beer in Singapore which had an import tariff of
87.2%.
Historically, the average tariff rate had been used to indicate a country's degree of
protectionism. At present, this may only show an incomplete picture, as after many rounds
of GATT and WTO negotiations, tariff levels have decreased considerably, although less
so in agri-food products. Therefore, a comparison of average tariff levels among the 30
countries provided an indication of how protective these countries were. Within the
sample of key target countries, Canada, Egypt and India had the highest average tariff level
of 63%, 361% (driven mainly by very high tariffs for alcohol up to 2,832%) and 57%
respectively, followed by Turkey with 53%.
The following table highlights the average tariff levels applied by all markets on each
product category individually and the average tariffs applied by each country across
product categories.
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61
Table 2.5.1.
Average tariff by product
Average tariff
Product code Product label
0101 Live horses, asses, mules and hinnies
0201 Meat of bovine animals, fresh or chilled
26.4%
0204 Meat of sheep or goats - fresh, chilled or frozen
18.0%
0207 Meat & edible offal of poultry meat
35.3%
0302 Fish, fresh, whole
9.3%
0306 Crustaceans
9.1%
0401 Milk and cream, not concentrated nor sweetened
31.9%
0406 Cheese and curd
32.1%
0902 Tea
16.3%
1806 Chocolate and other food preparations containing cocoa
15.0%
1901 Malt extract; food preparations of flour, meal, starch or malt extract
14.3%
1904 Breakfast cereals & cereal bars
12.3%
1905 Bread, biscuits, wafers, cakes and pastries
12.3%
2101 Extracts essences & concentrates of coffee and tea
16.2%
2103 Sauces mixed condiments & mixed seasonings
12.7%
2106 Food preparations, nes
51.4%
2202 Non-alcoholic beverages (excl. water, fruit or vegetable juices and mineral water)
16.0%
2203 Beer made from malt
74.9%
2204 Wine of fresh grapes
100.6%
2208 Spirits, liqueurs, other spirit beverages, alcoholic preparations (excl. whisky)
130.0%
Table 2.5.2.
Country
4.7%
Average tariff by country
Average tariff Country
Average tariff
Algeria
28.4% Malaysia
24.2%
Argentina
14.5% Mexico
36.8%
Australia
2.4% New Zealand
2.3%
Brazil
14.7% Nigeria
17.4%
Canada
62.7% Oman
17.4%
Chile
6.5% Paraguay
13.3%
China
13.9% Republic of Korea
*
Colombia
21.9% Russian Federation
27.4%
Egypt
Hong Kong
360.9% Saudi Arabia
2.8%
0.0% Singapore
4.5%
India
57.0% South Africa
13.9%
Indonesia
30.1% Thailand
30.9%
Israel
32.2% Turkey
53.2%
Japan
22.1% United Arab Emirates
10.1%
Macao
0.0% United States of America
5.9%
Note: South Korea's tariffs levels are blank given the latest FTA signed with the EU, which is expected to bring
down the current tariffs applied by South Korea on UK agri-food products
62
© 2013 Grant Thornton UK LLP. All rights reserved.
Chapter 3. Address any evidence gaps in the
longlist of countries, products and
barriers through primary research
Section 3.1. Introduction and scope
In order to support the findings from the desktop research conducted in Chapter 2 and to
assist with the shortlisting decisions made in Chapter 6, there was a primary research
element built in the engagement. Interviews took place with UK-based agri-food
businesses as well as policymakers and industry associations. This chapter is structured as
follows:

Section 3.2- Methodology and primary research sample: introduces the methodology
followed and the interview sample (in an anonymised format); and

Section 3.3- Key findings from interviews: presents the interview findings supported
by quotes. More specifically, the section consists of:
–
the countries targeted by the interview sample;
–
the type of barriers met by country (SPS, TBT, tariffs, etc);
–
the degree of restrictiveness by type of barrier.
The scope of work did not include testing the outputs from Chapters 2 and 6 with retailers,
distributors or consumers in target markets. However, this would be a useful exercise to
undertake in future projects.
© 2013 Grant Thornton UK LLP. All rights reserved.
63
Section 3.2. Methodology and primary research sample
This stage of the report required 35 interviews (25 company interviews and 10 industry
association and policymaker interviews) to be conducted. However, in order to capture a
wider sector and trade barrier coverage, 44 interviews were completed (29 companies, six
industry associations and nine policy makers).
The primary research element of this report was designed to complement the findings
from the comprehensive analysis on trade barriers conducted based on desktop sources.
Therefore, the interview sample was not designed to be statistically representative, but to
complement the desktop analysis and bring real life examples into the project (the
approach UK agri-food businesses take when exporting as well as the issues they face
because of trade barriers).
The sample interviewed was comprehensive, involving policymakers from four ministries,
various industry associations and food and drink manufacturers with a combined turnover
of circa £5.5bn.
Over 50 food and drink companies were contacted by Grant Thornton from among its
contact base. In addition, the Food and Drink Federation (FDF) introduced interviews
with some of its members. Circa 75 companies were approached for an interview and
several were removed from the sample as they did not have export activities. In total, 29
corporate interviews were conducted.
Eight industry associations were also contacted who represented manufacturers and
exporters of food and drink products. Six industry associations responded favourably to
the interview request, while the other two considered they were not well placed to
comment on trade/export issues as they did not deal with exports on a regular basis.
Over 20 policymakers were also contacted, within Defra, BIS, UKTI, DH and FCO, to
introduce the project and request participation in interviews. Of these, nine policymakers
with relevant insights/experience were available to participate in the interview programme
during the set timeframe (July-August 2012).
The following table summarises the characteristics of the corporate and industry
association sample, showing the agri-food sector they operate in, if they are in a sector
where the UK has comparative advantage and if they are among the top 20 sectors
shortlisted in Chapter 2. The following charts also show the characteristics of the interview
sample (turnover and number of employees as per the latest financial accounts).
64
© 2013 Grant Thornton UK LLP. All rights reserved.
Table 3.2.1.
Primary research coverage by product category
HS code
(sector) Product label (sector)
Number of Sector with UK
companies/ comparative advantage Top 20 sectors
(shortlist)
associations (i.e. RCA > 1)
Bread, biscuits, wafers, cakes and
1905 pastries
6 Yes
Yes
1904 Breakfast cereals & cereal bars
5 Yes
Yes
0902 Tea
Chocolate and other food
1806 preparations containing cocoa
2 Yes
Yes
2 Yes
Yes
2106 Food preparations, nes
All food & non-alcoholic
02-'21 beverages
Non-alcoholic beverages (excl.
water, fruit or vegetable juices
2202 and milk
2 Yes
Yes
2 Yes
Yes
2 Yes
Yes
0406 Cheese and curd
Sauces, mixed condiments &
2103 mixed seasonings
Spirits, liqueurs, other spirit
beverages, alcoholic preparations
2208 (excl. whisky)
1 Yes
Yes
1 Yes
Yes
1 Yes
Yes
0302 Fish, fresh, whole
Edible vegetables and certain
07 roots and tubers
1 Yes
Yes
1 Yes
No
0210 Meat & edible meat offal
1 Yes
No
1 Yes
No
1 Yes
Yes
1 Yes
Yes
1 Yes
Yes
1 Yes
Excluded
1 No
No
1 No
No
1 No
No
1 Yes
Yes
Fish, cured or smoked and fish
0305 meal fit for human consumption
Meat of bovine animals, fresh or
0201 chilled
Meat of sheep or goats - fresh,
0204 chilled or frozen
Milk and cream, not concentrated
0401 nor sweetened
Spirits, liqueurs, other spirit
beverages, alcoholic preparations
2208 (incl. whisky)
0904 Pepper, peppers and capsicum
Cane or beet sugar and chemically
1701 pure sucrose, in solid form
Meat of swine, fresh, chilled or
0203 frozen
'0306 Crustaceans
Total
36 Yes (19/22)
Yes (15/22)
As illustrated in the table above, the companies and industry associations interviewed
represented a wide spectrum of agri-food sectors, with 22 HS codes represented and some
associations operating across the whole food and non-alcoholic beverages sectors.
29 agri-food companies active across 15 sectors were interviewed for this project. In
addition, interviews were conducted with six industry associations, two of which include
members across the whole food and drink spectrum and four of which were sector-specific
associations. As interviews were anonymous, no company or association names
are revealed.
© 2013 Grant Thornton UK LLP. All rights reserved.
65
Bakery products and breakfast cereals have a strong representation, with the remaining
sectors being represented by one or two companies/industry associations. 19 out of the 22
sectors in the sample are sectors where the UK has a comparative advantage (i.e. RCA >
1). 15 out of the 22 sectors are also among the top 20 sectors in the longlist created
through the analysis in chapter 2. The sample is not statistically representative, but it
includes representatives of most sectors of interest for this project and it serves to gather
real-life examples of the approaches UK agri-food businesses take when exporting as well
as the issues they face.
Chart 3.2.1.
£0.1-5M
2
Number of companies surveyed by business turnover and
number of employees
£500-£750M
3
£5-10M
4
4,000-5,000
2
2,000-3,999
3
0-49
6
£250-500M
5
1,000-1,999
5
£10-25M
4
£100-250M
4
£25-50M
4
£50-100M
2
By business turnover
50-249
7
500-999
2
250-499
3
By number of employees
The sample includes eight large companies with revenues between £250-750M, while the
majority of the sample is made up of micro, small and medium sized companies. This is in
line with Defra's request to concentrate on SMEs (as multinationals are likely to have the
financial resources and local production facilities to help them overcome trade barriers).
66
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 3.3. Key findings from interviews
Section 3.3.1. Target countries
All the companies interviewed had export activities, although for some, export markets
represented a large proportion of turnover, while for others exports have only become a
focus recently. However, all the companies interviewed pointed out that exports have
become a strategic priority as they were exploring ways to counter the difficult economic
climate in the UK.
The companies interviewed identified 32 countries as target markets in the short to
medium term time horizon; USA, China, Australia, Canada, Russia and Japan where most
frequently quoted by interviewees (refer to Chart 3.3.1.1 for more details). As per the
interviews, some companies may already be present in these markets, but see further
growth opportunities there, while other companies in the interview sample intend to target
these markets, but may not currently be present in all of them. Based on the discussions
with UK agri-food companies, the target countries were divided into three priority groups.
As such, the key target markets were rated as priority 1, the markets with some
opportunities in the short to medium term are rated as priority 2, whilst the countries
where companies see potential opportunities, but did not consider that they will represent
a major revenue uplift in the short-to-medium term were rated as priority 3. Based on these
ratings, 15 countries were considered as top priority (i.e. priority 1) by the companies in the
sample, with USA and China being the most frequently mentioned as being the main
countries that UK agri-food companies plan to target.
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67
20
18
16
14
12
10
8
6
4
2
0
Target countries by number of references
18
15
13 12
12 6
4
6
8
3
1
3
3
9
2
1
10 9
5
5
4
4
1
7
6
3
2
2
5
2
4
4
4
4
2
1
2
2
2
2
2
2
11
4
1
3
3
2
1
3
11
1
2
11
2
11
2
11
2
101
2
11
2
11
2
11
1
10
1
1
1
1
1
1
1
1
USA
China
Australia
Canada
Russian…
Japan
UAE
South Africa
India
Brazil
Saudi Arabia
Other EU
Republic of Korea
New Zealand
Singapore
Other non-EU…
Hong Kong
Nigeria
Colombia
Israel
Thailand
Turkey
Oman
Egypt
Indonesia
Mexico
Chile
Number of mentions
Chart 3.3.1.1.
Priority 1
Priority 2
Priority 3
When considering the export markets that were most frequently mentioned as priorities,
the top 10 countries' (excluding 'Other EU' countries which are out of the scope of this
engagement) attributes can be broadly categorized into:

English speaking countries (USA, Canada, Australia, South Africa) where the shared
language and historic/cultural ties facilitate the penetration of British products and
building of British brands;

developed/affluent countries characterised by consumer demand for high-quality,
high-value products (Japan, UAE); and

high-growth emerging markets, where socio-economic conditions are increasing the
demand for Western products and creating an opportunity for UK firms to tap into
these markets (China, Russia, India, Brazil).
The current project is focused on unlocking barriers to growth outside the EU as it is
assumed that the EU is an open market where there should not be trade barriers for UK
food exporters. Therefore, the focus of the interview programme was on identifying trade
barriers outside the EU. However, many of the companies interviewed acknowledged that
the EU is a core export geography for them because of the unified legislation, geographic
proximity, a more similar cost base and consumer purchasing power, all of which allow
them to compete successfully against other EU products. In contrast, they acknowledged
that although many target emerging markets for the economic growth and burgeoning
middle class, these countries will not be core to their business in the short to medium term.
That is because British products cannot compete on price with local manufacturers in
order to capture significant market share. Also due to differences in consumer preferences
and habits, some of the product categories which are popular in the Western world (e.g.
breakfast cereals, dairy products, etc) may require significant investment and time to
educate consumers in emerging markets and change their eating habits. Therefore,
significant time may pass before UK exporters can export significant volumes to these
countries.
Interview quotes
 "Non-EU will never be core to our business as we will not be able to complete to provide the commercial back up."
 "The importance of emerging markets depends on what sort of business you are talking to. We produce a mainstream
product and compete in a category with strong local manufacturers that can produce more cheaply. Regardless of tariff
levels, when shipped to a market like Brazil or China our product becomes a premium product targeting affluent
consumers. There are opportunities in these markets because of the burgeoning middle class, but it would never be
enormous for a European manufacturer of mass market food product."
 "African nations are not a key target as the vast majority of consumers cannot afford high-value Western products."
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3.3.1.1.
Why they target certain countries?
Although frequently companies may react to requests from overseas markets to source
their products, many take a structured/strategic approach to exports. One of the
approaches used to select potentially attractive export target markets was to
undertake/commission market research to quantify and rank the domestic
consumption/demand of the product they manufacture. Focusing on markets where there
is an established demand, facilitates a quicker penetration and acceptance by consumers
and minimises the marketing budgets spent on consumer education. This is then refined by
undertaking more detailed consumer studies, followed by other commercial considerations
(retail structure, competitor market shares, presence of local manufacturers,
distribution etc.)
Interview quotes
 "We determine the market attractive potential by identifying the counties with the largest consumption of tea".
 "The way we do validation of opportunity is the number of consumers in our target group, what we know about the
consumption and what reasonably we can expect to gain as a share of their consumption and then estimated the sales
value. When we enter a market we look at the opportunity from a consumer perspective."
 "The first step is to research the market, to source data on the growth and maturity level as well as the consumer
requirements and how our product could fit within the market. The second step is understanding how we physically
operate, we research local manufacturers and distributors and assess the costs of these two distribution options."
 "You would have to go through distributors who take a margin and you have duties. Therefore, your products will be
more expensive compared to local alternatives. Therefore, to be successful, consumer understanding is critical, namely
understanding what format, what packaging or tastes consumers want. Your products will be more expensive gram per
gram, but they do not have to be more expensive on a pack basis."
 "Looking at the high growth economies, we distinguish a strong demand and consumer appetite for premium fish and
seafood products in countries like Russia and China. This creates exciting opportunities for our company."
 "In Asia, in particular China, they take the fifth quarter of the animal. Consumers eat heads, tails, feet, various parts not
eaten in the UK. This is an opportunity as we are able to sell what otherwise we would have to discard it at a cost."
Once the opportunity is validated, some companies focus on export markets where the
consumer eating habits and the consumer profile are similar to the ones they serve in the
UK. They undertake market studies to identify consumer behaviours and understand what
product categories they might have to compete against.
Interview quotes
 "English-speaking countries also have similar eating habits, they eat biscuits and they also use bread alternatives such as
crackers – it is a similar profile. All the markets‟ primary consumer groups are the same two. One is the foodie, who is
interested in good high quality food and something that looks a bit different. The other is the healthy eater who wants
to eat good quality food but who is interested in natural and health claims. Those two consumer groups are present in
all our current markets."
 "The markets that were traditionally strong for us were English speaking markets (US, Canada, Australia, New
Zealand), partly because of the language, but also because taste types within chocolate are important and those markets
had developed over the years a liking for British style chocolate."
 "The market is in its infancy in Russia, the concept of snacking is new. They don‟t use our cereal bars for the same
reason that we use them in the West. There it is almost in addition to a meal versus in the UK where it is almost a
substitute for a meal. The usage points are a bit different, so you don‟t know where competition comes from and,
therefore, you have to understand how consumers use the products before you sell to a market."
 "If we try selling our cereal bars in Brazil for example, we are going to have a lot of issues because the price points will
be huge and the income will lower, plus there will be enormous local competition and competition doesn‟t come from
other bars, but from widely available fresh fruits and juices/smoothies. It is the same in India, you walk down the street
and you will be assaulted by street vendors selling you the most delicious local food, so why would you eat a bar from a
packet instead of something freshly made?"
However, some companies were taking the view that markets with well-established product
categories are close to saturation and therefore were focusing their efforts on tapping into
countries where the product category is emerging and where competition is not as strong
as the well established markets/product categories.
© 2013 Grant Thornton UK LLP. All rights reserved.
69
Interview quote
 "We are also looking at untapped markets. US may the biggest cheddar importer, but it is quite saturated. That is why
we decided to go Japan as they are starting to develop a taste for dairy products through the Westernisation of the
diets."
3.3.1.2.
Focus on key markets or export in many countries?
The primary research consensus was that identifying the most appropriate markets and
focusing on key opportunities was seen as a more rewarding strategy for SMEs as they may
not have large resources to allocate to their export sales and marketing functions.
Interview quotes
 "The key thing for a business like us is to remain focussed. You could go after the whole world. But we have
established brands in certain markets and we get more return by looking to grow and leverage those positions and
make them stronger than going for many of smaller opportunities around the world."
 "We concentrate our efforts and investments on markets where there is a bigger consumer propensity to buy our
products. In the other countries, we will have a basic strategy and market information and leave these countries in the
responsibility of the importer."
 "In the last year we have chosen to take international more seriously and have developed a strategy of the markets we
plan to take forward over the next 3-5 years. We will target countries in a more targeted manner and we split them in 3
tiers tier 1 being those that we were are going to actively pursue in 2012/2013, tier 2 being those we will start
investigating and tier 3 longer term based on the challenges that we think we will have."
 "15 years back if we had an enquiry from Russia and they told these are all the documents they needed, we would have
walked away to concentrate on countries where the documentation was not so complex. It is similar when supplying
UK customers, you wouldn't supply to a supermarket if you couldn't cope with the volume requirements."
3.3.1.3.
Key success factors
Despite globalisation, cultural differences persist and therefore establishing a UK agri-food
product/brand in foreign markets requires consumer study, insights into distribution
channels and time. In addition, each country has different business practices and decisionmaking styles which UK exporters need to prepare for and adapt to. Exporters also need
to consider payment options carefully in order to minimise risk. When dealing with new
business partners in new geographies, UK exporters can reduce the risk by asking for cash
in advance or partial payments or securing the ownership for the goods through letters of
credit or documentary collections.
Interview quotes
 "In countries where business practices are considered risky, we restrict our exposure. We tend to work cash in advance
with the local distributor/retailer for the first year or two. Afterward we can offer them some level of credit."
 "Due diligence on the local partners is important. Before we started exporting to China regularly, we got an order from
a firm in Shenzhen for a quarter million pounds and sent the shipment but then realised that it was a scam. We have
definitely become more aware and savvy about those we do business with."
 "The best way to be successful is to manufacture in the market you are going into. But that obviously involves
significant capital and investment."
An ambitious, proactive export team with experience in dealing with the regulatory and
paperwork complexity is essential to targeting export markets in a meaningful way.
Interview quotes
 "If we were a very small business we wouldn't be able to cope with the work involved with exporting, but we have an
export team whose job is to liaise with local partners/customers to understand the requirements and obtain the
paperwork to comply with the legislation. and once you know about these issues it's self-perpetuating."
 "Our export market is a team of three one of whom is based in the United States so it does give us challenges with
regards to going and looking for emerging markets. Therefore, for now we are focusing on the markets we already
supply as we do not have the resources to look at emerging markets."
 "It was the impact of the strengthening of the pound in the middle part of last decade; it became more and more
difficult to. We took our cost base down; by removing the sales export manager and the structure that was supporting
him. Once you dismantle something like it is very difficult to build it back up again, you take cost out more quickly
than you put cost in. As a consequence the share of turnover from exports has declined compared to what it was then
despite the fact that the exchange rate is more favourable now."
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3.3.1.4.
The role of distributors/importers/consolidators/
export management
Although some companies may sign direct agreements with local retailers, usually UK agrifood companies use intermediaries such as consolidators, export management companies,
agents and distributors/importers to enter an export market. These partners often have
established channels of distribution and product knowledge as well as experience in
navigating the import/export legal requirements. They are responsible for many of the
administrative steps associated with exporting and they are the main source of information
on the legal requirements their products need to comply with. Therefore, for SMEs they
offer a viable route to gain brand recognition and capture market share. This explains why
many of the companies interviewed emphasised that finding the right partner was crucial
to the success of their export operation.
Interview quotes
 "We have a capable distributor partner who makes sure that all the administrative processes are carried out with a high
degree of detail in the receiving market."
 "The main sources of information on legislation changes are the distributors. They usually represent a number of
international brands. When we enter a market we're very considered in our choice of who gets to represent our brand,
we look at what other brands they have in their portfolio, how long they've had them, the success they've had, we talk
to the brand owners to understand if they are a good distributor, if they have an understanding of the legislation, all the
requirements for certification of origin, the relationship with key government departments."
 "When there are proposed changes in legislation, it is important for the distributors to be well connected so they can
lobby on our behalf and influence things whilst complying with the laws."
 "Distributors deal with bureaucracy, customs, and government bodies as that is their expertise. In a way that is a barrier
to entering a market, as if you do not have reputable, respectable distributors you may not enter the market for fear of
corruption, malpractice and selling the brand in the wrong place at the wrong price."
 "We do not deal with custom procedures or fees. Importers are the experts and deal with these. We do the shipping
and aim to give it to the importers to a very low price and the importers do the rest."
 "Our distributors are very good at managing importation challenges and paying the relevant duties."
 "It is the importer's job to ensure our products are legally compliant in that country and they will give us all the help we
need to get that done."
 "We currently use a consolidation business in the UK and they work with the Nigerian distributors and facilitate our
product getting into Nigeria. We just supply the products ready for shipping. As I understand it they ask for a vast
number of different documentation, but the consolidation business in the UK does all the administration and gets the
product through customs. Initially we considered dealing with Nigeria directly, but when we realised how complex the
process is, we were quite happy to use the consolidator. They get a fee for their service, but they deal with the
distributors but they manage the paperwork flow."
 "As a small business, the level of pro-activeness you can put into exports is quite limited. Therefore, we are very reliant
on partners. We've had successes in certain markets and have been less successful in others and it was mainly to with
whether the local partner gets behind our product or not."
3.3.1.5.
Commercial considerations/other things to consider
when exporting
Outside of the trade barriers, UK agri-food exporters must take into account a complex
range of commercial issues when exporting. Although, these issues are not in scope for this
report, a short overview of the issues that manufacturers highlighted during the interview
programme is presented below:

59
The depreciation of the sterling was of great help to UK exporters in recent years, as it
made the high quality, high value British products affordable abroad. The recent trade
statistics indicating a 15% CAGR between 2009-201159 growth in UK agri-food
exports are the proof of the increased competitiveness of British products;
UK agri-food export statistics, Trade Map
© 2013 Grant Thornton UK LLP. All rights reserved.
71

Interview quotes
 "Until relatively recently, we did not regard exporting as very important. It was a minor part of our business, but that
changed dramatically in the last few years. One of the main reasons for this is that the pound collapsed. We have always
been a high-priced ingredient company at the top-end of the market and that probably made a difference. We were too
expensive for the rest of the world and they did not necessarily know what we were offering. So when the pound fell
we became not a cheap producer, but a reasonably-priced one."
 "At the moment the pound is making up for any import duties that we historically faced."

The decision to target a market and the success of the exporting activities are greatly
influenced by the general food trends and consumer preferences in the local market.
Despite a Westernisation of diets in developing markets, many established food and
drink categories do not exist, or are only incipient in these markets and take significant
marketing resources to be developed. Consumer education and creating demand for a
product is usually a role that multinationals fulfil as they have the resources to invest
behind such initiatives. This can benefit smaller companies who can enter the market,
once it is more established.
Interview quotes
 "In Asia consumer habits are different and in our category, breakfast cereals are not the typical thing that a Chinese
consumer for example would eat in the morning, because they do not necessarily eat dairy. However, that trend is
changing and is being driven by the multinational breakfast cereal players. We have thought, well let other people
develop the habit and we can come along with our product at a later date once we have established the right way of
going into that market place. However, now we are reviewing our strategy for China and will visit our current partner
to look at other ways of doing business."
 "There is a different eating ethos, a different consumer and there is a lot of development to do to educate the
consumer about the products and that sort of thing. It‟s a long-term project and it is not going to set the world alight
immediately."

The companies interviewed were concerned with the price of their product on shelves,
as it is to a great extent the key to their being successful in a local market. Therefore,
for many of them considerable time is spent developing a pricing model that ensures
all parties in the supply chain can develop a sustainable relationship whilst achieving an
attractive end-price for the local consumer.
Interview quotes
 "We have to ensure we have a competitive price. The big issue is price on shelf versus local competitors."
 "There are some strong local players in our product category and consequently by the time we have shipped it there,
the distributor puts their margin on it and it goes on shelf, it ends up being very expensive. We are exploring if there is
a way of us deliver directly to a retailer [in this country] and that way have a better on shelf price."

Shelf life is also an important consideration. The further afield the market, the longer it
will take for the product to reach the consumer. This combined with minimum shelflife imposed by retailers in certain countries limits the export opportunities for fresh
produce or products with a short shelf life.
Interview quotes
 "Logistics and the associated issue of shelf life is also an important consideration when developing an export strategy
for food and drink products. The further afield the market, the longer it takes for the product to reach the consumer.
This combined with minimum shelf life requirements put in place by local retailers limit the attraction of some
countries for more perishable product categories."
 "None of our UK products is exportable because of the shelf life. Therefore we've had to change our products to be
able to export them."
 "…Then there is the logistics side; how long it takes to ship the product around the world as with food you have shelf
life to consider. We supply the Taiwanese market and it takes six weeks for the product to get into the country. For a
product that has a six month shelf life, that puts more and more pressure on the product unless you use air travel
which is much more expensive."
 "Another issue we have is the fact that biscuits have a relatively short shelf life, from nine to 12 months, if you are
lucky. But it normally takes two months to get a product somewhere. A lot of retailers have quite strict policies on the
percentage of life they accept on a product. Mostly it is easier to do it closer to home. It is the nature of the business."
72
© 2013 Grant Thornton UK LLP. All rights reserved.

Although the companies that agreed to participate in the study were all enthusiastic
about the opportunities offered by exports, some of the industry associations and
consulting companies interviewed mentioned that the attitude within British firms is
not always supportive of exports. Many UK manufacturers are set up to fulfil the
requirements of the UK retailers; sometimes UK manufacturers have entire plants
dedicated to servicing one retailer. The attitude within such companies can be one of
focusing on large runs for UK supermarkets rather than deal with the complexity
associated with small runs for export markets. Sometimes the largest obstacles to
exports are not trade barriers or the market structure in the target country, but the
company's internal attitude.
Interview quotes
 "One of the main barriers is the attitude to exports, it is difficult to convince finance and manufacturing departments
about the pros of exports, as UK manufacturers are locked into the UK retailers."
 "In my previous role as an export manager I found that the hardest customers to win over are the internal ones because
the UK market is orientated towards retail service. A production manager would much rather do a large run for
supermarkets."
 "In my previous role as an export manager I found that the hardest customers to win over are the internal ones because
the UK market is orientated towards retail service. A production manager would much rather do a large run for
supermarkets."
 "Highlight internally in the company that there is an opportunity and they have to start small (small runs, added
complexity), but there is the potential to grow the business. Show them the good examples, the companies that
succeeded and despite the barriers have been successful abroad e.g. Walkers shortbread."
Section 3.3.2. Trade barriers
The companies and associations interviewed identified a total of 157 barriers, of which
14% were tariff barriers and 86% were non-tariff barriers. This is in line with the desktop
analysis which indicates that although tariffs remain an issue for the agri-food sector, nontariff barriers are the most prevalent ones affecting international trade.
Chart 3.3.2.1.
Tariff and non-tariff barriers by number of references
Tariff
22
14%
Non-tariff
135
86%
TBT and SPS barriers are the most prevalent non-tariff barriers that companies in the
sample faced when exporting, followed by complex registration/documentation
procedures and customs procedures. This is also in line with the literature review, which
indicated that the EU and WTO report a large number of TBT and SPS barriers for EU
products in international markets.
3.3.2.1.
How prohibitive are these requirements?
As seen in the previous section, the interviews uncovered 157 issues that the UK agri-food
exporters faced across a variety of product categories and countries. Many of the issues
that UK exporters faced are complex, require time and financial resources to tackle and
© 2013 Grant Thornton UK LLP. All rights reserved.
73
therefore may discourage some companies from actively pursuing exports. However, these
issues experienced by the UK manufacturers interviewed and do not necessarily fulfil the
WTO definition of a trade barrier. In addition, they did not all appear prohibitive. Only 18
of the issues mentioned by companies during the interview programme could be
considered to be prohibitive barriers (i.e. companies cannot overcome the issue by
investing more resources into, for example, the manufacturing, marketing or exporting
departments). These prohibitive barriers were mainly due to:

Quota systems imposed by the importing country for certain product categories:
 e.g. Canada operates a quota system for cheese (273 tonnes of EU cheese);
 e.g. Turkey has a quota for tea imports (200 tonnes of EU tea);

Import bans or hangover effect of BSE which act as a barrier for EU meat products;

Legislation which has been introduced by importing countries and which has resulted
in UK agri-food export shipments being stopped as the products do not comply with
the new requirements; and

Tariffs/duties/taxes are so high that they make UK products inaccessible to the
local consumers.
Chart 3.3.2.1.1 shows the categorisation of barriers compiled through the primary research.
Barriers have also been categorised based on degree of prohibition by interpreting the
information supplied from the interviewees.
Interview quote
 "We experience market access barriers in Russia, Kenya and India. But nothing that hasn't been overcome because we
have already made shipments to all countries. They difficulties were all food import regulations. In most countries they
need additional documents such as proof of origin, proof of manufacturing, making sure that we comply with trading
standards, certificate for quality control, but these are not problematic. The problem is making sure the importer
communicates exactly what he needs and then you go out and do it. So, all the documents are available, sometimes you
have to pay for them and have to go and get hold of them."
74
Type of barriers by number of references and degree of
prohibition
37
29
Regular
8
2
9
2
7
3
Strong
2
1
State trading
10
Competition issues,
subsidies, etc
5
13
2
11
3
Quotas, import
restrictions
18
7
15
Other
17
22
2
Intellectual Property
(enforcement
problems,…
11
Customs
2
7
Taxes, tariffs, duties
24
31
Registration,
documentation,
procedures
11
SPS
40
35
30
25
20
15
10
5
0
Standards and other
technical
requirements (incl…
Number of mentions
Chart 3.3.2.1.1.
Prohibitive
© 2013 Grant Thornton UK LLP. All rights reserved.
Issue
Product
Category
Interview quote
Quota
Tea
"Turkey's a large producing and consumer nation of tea and has a large middle class
population, particularly around Istanbul, which makes it a very attractive market for us.
However, there are both a quota and tariffs. The quota for tea in Turkey is very limited, 200
tonnes of tea of EU origin per year. Even within the quota there is a tariff level, which is
around 70%. And then you can bring tea in outside the quota, but the tariff level goes up to
140 %."
Health
claims
Breakfast
cereals
"We have terrible problems in Saudi Arabia at the moment. They say our health claims do not
form part of their legislation despite the fact that they are fully acceptable under EU law. So
we have to go through a process of justifying the health claims and if they are accepted we
have to change the packaging or put on a sticker. We haven't been able to supply the market
for months."
Quota
Cheese
"The quota for cheese in Canada is c. 273 tonnes of European licence that is available for
European dairy products. That can go for anything depending on what the current demand is
from $6 (Canadian) a kilo to $10 or more, so your imports have to factor that into their price
if they are considering importing your product and it does make it very expensive. Now that
hasn‟t changed since 1973 that volume hasn't changed and that is the Canadian authorities
protecting their own dairy industry."
3.3.2.2.
Trade barriers by type and country
The split of barriers by country is shown in the graph below.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
3
1
1
1
2
2
12 3
6
21
3
4
5
3
4
2
1
2
1
1
1
1
1
1
1
1
6
5
3
6
3
2
1
2
1
1
1
1
1
2
5
5
Type of barriers by country
6
4
1
1
1
2
1
1
1
1
1
3
2
1
2
1
1
1
1
1
1
3
1
1
1
1
1
China
Russia
USA
Japan
India
Saudi Arabia
Australia
Canada
UAE
Turkey
Israel
Nigeria
Latin America
Brazil
Oman
Qatar
South Korea
Argentina
Egypt
Mexico
Other non-EU
Other EU
Number of mentions
Chart 3.3.2.2.1.
3.3.2.3.
Standards and other technical requirements (TBT
barriers)
As mentioned already, TBTs (also referred to as standards and other technical
requirements) were the most frequent barriers encountered by the companies in the
sample. The majority of issues arose because there were no harmonised standards
internationally on packaging, labelling etc. This creates complexity and adds cost for UK
manufacturers, as the product packaging needs to comply with the labelling and packaging
requirements of each export country. For example, in the UK, products must show the
best before date, while in the Middle East and North Africa, the packaging must contain
the production date and expiry date. Similarly, ingredients may have to be listed in a
different order depending on the export country.
The countries where companies most frequently encountered TBT restrictive measures
were UAE, Saudi Arabia and China. According to feedback from interviews, Saudi Arabia
and UAE recently became more active in imposing and enforcing regulations, which may
explain the higher incidence of barriers reported for these countries.
There was also a high incidence of restrictive TBT measures reported in the USA, however
this is most likely due to the fact that it is the key export market for the majority of the
companies in the sample. Therefore, companies commented on the issues they
encountered in the markets they are familiar with and which represent a large share of their
© 2013 Grant Thornton UK LLP. All rights reserved.
75
export revenues. However, the fact that they export to the USA indicates that the UK
products can enter the US market. Therefore, the TBT measures imposed by the USA are
not blocking access to the market, despite making the process more complex/costly for
UK agri-food firms. The EU and US have very well defined standards, although these are
not usually aligned and they need to comply with both sets of standards to supply their key
markets. For example, nutritional information and ingredient requirements are different in
the EU and US and manufacturers need to obtain FDA certifications before being able to
supply to the US market.
The prohibitive TBT barriers collected in the interview programme mainly referred to
alcohol-filled chocolate which do not meet the legal requirements in USA and Australia.
However, it is likely that they will usually be able to export small volumes without
complying with local labelling/packaging requirements. However, an increase in the value
of exports translates in increased scrutiny at customs. Therefore, SMEs should be able to
test a market before making the investment in customised packaging.
Chart 3.3.2.3.1.
TBTs by country and degree of prohibition
1
1
1
1
1
1
Other EU
Latin…
Qatar
South…
Canada
India
Prohibitive
2
Oman
1
Australia
Strong
1
2
2
2
Israel
Japan
China
1
1
1
1
USA
Regular
2
2
3
Saudi…
3
4
UAE
0
1
2
2
3
4
Number of mentions
5
6
7
Country
TBT issue
Interview quote
Saudi Arabia
Packaging/
marketing claims
 "We've got to develop new packaging for Saudi Arabia, not because of health
claims as we comply with all those regulations, but because of the marketing
and brand communication we do through our packaging. The authorities have
told us this is not information, it is "marketing speak", so we have to remove
it from the packaging. This is a barrier as in the absence of advertising, which
is very expensive, then one of the only ways in which you can communicate
with your consumers about the brand values is on the packaging."
US
FDA requirements
vs. EU standards
vs. China
 "The company required FDA certification to export to the US. Moreover, the
requirements of the different health boards are not harmonised in the EU,
USA and China, for example. Having to meet so many certification
requirements is costly."
 "The FDA has different standards for ingredients, quality checks and health &
safety checks. It is not so much a trade barrier, but it causes problems because
you need to comply with UK, EU, US and other 3rd party standards and they
are not harmonised."
 "There are simple little things, like the order of nutrients being different in
America. Even though there are the same nutrients and they are calculated the
same way, the order is different and that adds quite a burden on industry to
re-order the nutrients."
 "We have to produce separate labels for the US as the nutritional information
has to be listed differently and the volume of product must be shown in the
front label rather than the back label which is in the norm in Europe."
China
China vs. EU
moisture level
standards & testing
 "The other issue in China with our cereal bars is that they regularly test for
moisture levels and our bars fall outside of the moisture content allowance.
It's a challenge for us as without having that level of moisture we can't
manufacture the bars to the highest quality. We've been involved with the
British High Commission to help us talk to the Chinese authorities about the
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Country
TBT issue
Interview quote
testing and supply them with more documentation to convince them that
there is no safety issue and we were successful."
 "But things are erratic and every time we import we can have a similar issue. It
gets frustrating that the standards between the EU and 3rd countries aren‟t the
same."
UAE
Packaging (best
before vs. expiry
date)
 "In the UK we go for a best before date, in Dubai you are required to have a
production and an expiry date, so that is different from our standard process.
So we use a contractor that has to unpack everything, re-date it and then repackage and that is costing us 15% of sales."
General
Market testing with
low volumes
 "When you start and your exports are small you go with English packaging
because you are under the radar but as you grow the importer puts pressure
on you to write in the local language and gradually you comply."
 "The customs controls increases when you become a larger exporter, but
initially for small volumes you will be allowed to enter."
General
Nutrition labelling
standards
 "Over the last 10 y the requirements to put nutrition labelling on packs have
both increased and been stringently enforced. We are now in situation where
there is a nutritional labelling standard for Europe, a separate one for the US,
a separate one for Canada, a combined one for Australia & New Zealand,
China and Japan have their own requirements."
USA
Australia
Alcohol filled
chocolate
 " One of our brands, which is liquor filled chocolates falls fowl of alcohol
legislation. There are only 18 states in the US where our product is legal. We
discovered a few years ago that in Queensland in Australia, that legislation had
been passed 12 years ago, that nobody took notice of, which suddenly was
used to remove us from the shelf space in Target because of one customer
complaint. The way the legislation was drafted in Queensland would mean
that Christmas pudding is illegal."
3.3.2.4.
SPS barriers
SPS measures were the second most prevalent barrier mentioned by the sample of
companies and industry associations interviewed. USA, Japan, China and Australia were
the countries where UK companies most frequently encountered SPS issues. However,
there is a spread of over 13 countries where UK agri-food manufacturers have
encountered obstacles because of phytosanitary regulations, indicating the crucial role they
play in safeguarding food safety and animal and plant health.
Although SPS regulations apply across all agri-food categories and countries demand
certifications, products of animal origin (meat, milk and egg based) appear to encounter the
main prohibitive barriers outside the EU as a result of the Bovine Spongiform
Encephalopathy (BSE) legacy.
The barriers encountered in the US relate to various FDA requirements for health
certification. The main obstacle in addressing SPS measures is the different approach that
the US and EU take on scientific evidence on plant and animal health issues, which results
in different legislation and created trade barriers. The evidence from interviews with agrifood industry participants and policy makers indicates however, that the US approach was
more open as it will only raise objections where there is scientific evidence, while the EU
tends to be more protectionist (e.g. EU does not allow US meat carcases treated with lactic
acid on the EU market, EU bans food containing genetically modified organisms).
One of the measures most frequently identified during the interview process was food
legislation that requires recipe changes. For example, companies using flour in their
products have to comply with the flour enrichment regulations adopted by some countries.
Certain countries such as Brazil, Mexico, Canada and Norway demand that flour is
enriched with specific levels of vitamins and minerals, but these are different to the flour
enrichment used in the UK, while others such as France and Denmark have a strong antienrichment stance and do not accept products containing enriched flour. Therefore, for a
UK manufacturer to target that specific market, it has to decide whether the opportunity is
big enough to justify additional capital investment to manage the complexities in the
production process by running small batch sizes to meet the requirements of a single
© 2013 Grant Thornton UK LLP. All rights reserved.
77
country. One of the companies interviewed acknowledged that the flour enrichment
regulations have stopped it from pursuing opportunities in Brazil and Mexico as it was not
viable to produce unique recipes and still compete with local products.
Another example is the definition of chocolate (more specifically the proportion of cocoa,
fat and whey powder), which according to confectionery and bakery companies
interviewed, varies around the world. One manufacturer mentioned the company has three
different variants of chocolate they use in their chocolate coated biscuits to comply with
local laws.
Country
SPS issue
Interview quote
Several
countries
Recipe
 "The legislation around what is and what it is not chocolate and what is allowed to put
in chocolate and what it is not varies enormously around the world. So we have three
different variants of [brand name] chocolate that we put on different products and we
have to vary which chocolate we put on to apply to local laws. In a lot of markets
around the world, what we call chocolate in the UK, so [brand name], you could not
call chocolate. It is not viable to produce unique recipes for some smaller markets."
Another issue for UK firms is understanding the certificates required by the importing
country and obtaining the relevant veterinary certificates from UK authorities. This is
particularly complex/time consuming when there are no export certificates already
developed or when the importing country requires EU certificates.
Chart 3.3.2.4.1.
SPS barriers by country and degree of prohibition
1
1
1
1
1
1
1
1
1
1
Other EU
Other…
South…
Qatar
Canada
Brazil
Mexico
Saudi…
Russia
Australia
Prohibitive
Strong
Regular
1
2
3
China
2
4
Japan
2
5
USA
0
1
2
1
3
4
Number of mentions
5
6
7
Country
SPS issue
Interview quote
General
Foot and
mouth
 "People find it hard to understand the legacy of foot and mouth given the progress we‟ve
made in the UK and the standards we produce to. UK manufacturers find it frustrating
that these barriers still exist for food products."
USA
Medicine in
salmon
farming
 "The USA has some bizarre specifications on phytosanitary measures (around the
medicines used in salmon farming which are not the same in Europe and USA)."
 "Discussions between the EU and US are very tense on a lot of these science-based issues.
The US approach is more science-based, while the EU approach is a lot more
precautionary. This causes all sorts of problems in trade discussions. I do not think I am
overreacting to say it could be one of the biggest trade issues in the whole EU-US
negotiations. Science based issues are a major issue in trade negotiations between US and
EU."
 "Health certification has to be obtained 7-10 days prior to shipment declaring the exact
quantities and types of cheese, which is cumbersome."
Sciencebased trade
negotiation
Health
certification
Japan
78
Stricter
requirements
vs.
international
SPS rules
 "Japan has very strict ingredient requirements. Japan is a nightmare because of the level of
detail they require. e.g. they require a lot of details about the ingredients that go into icing
sugar."
 "Japan has very high hygiene standards and feels that they use regulation to protect internal
manufacturers as international standards are not as strict."
 "Japan has very strict rules on products derived from bovine origin because of the BSE
scare"
© 2013 Grant Thornton UK LLP. All rights reserved.
Country
Interview quote
SPS issue
 "Japan has a strict system of standards and safety modelling which goes beyond the EU or
internally accepted standards."
China
BSE legacy
 "The hangover from BSE and foot and mouth are significant barriers as we have to get a
lot of certification to make sure we can enter the product in China."
 "There is a question about the use of eggs as an ingredient in China which given the
opportunity for bakery products could be a challenge, so we are trying to understand
whether it relates to using raw or processed eggs as there are a few dessert companies who
are very keen to develop the Chinese market."
 "Chocolate is a dairy product and the hangover from BSE and foot and mouth are
significant barriers to China."
Australia
Stringent
certification
 "In Australia we had an odd situation. They requested that sunflower seeds be processed
or chemically treated because they had an issue about sunflower seeds germinating in store
in other manufacturers' products. It took a lot of time to get the authorities to resolve this
and stop the requirements."
 "In Australia it is difficult to obtain phytosanitary certifications. They have stringent phyto
requirements for fruit, plant and animal products due to the risk of importing diseases that
do not exist in Australia."
 "We sell our cereal bars in Australia and it is a difficult country to deal with on
phytosanitary regulations."
Chile
Veterinary
certificate
 "The other biggest challenge is in understanding what the requirements are and when the
EU takes responsibility for certificates vs. Defra. For example, to get an export certificate
for Chile we had to find out what the requirements to Chile are. We had to get Chile to
talk to the UK Veterinary Authority to inform them what the requirements are so that the
UK can develop a certificate which they give to Defra and Defra gives to the Annual
Health and Veterinary Laboratory Services. When I contacted Defra about the export
certificate for Chile, they told me that Chile is being managed by the EU Commission
(Directorate General For Health & Consumers, DG Sanco). I had to get contact DG
Sanco and manage the process from the outside and inform Defra of what DG Sanco was
doing. The whole system took too long by which time we lost a couple of business
partners."
3.3.2.5.
Registration, documentation, procedures
China and Russia are considered as having the most complex registration, documentation
and procedures requirements. The main complaints gathered during the interview
programme highlighted that companies had to deal with bureaucratic systems, complicated
by the need to comply with authorities at various levels (national, regional, local). In
addition, regulations in these countries are complex, confusing and constantly changing,
making it difficult to know what requirement must be met at any given time without the
use of a reliable and well informed local importer/distributor.
Chart 3.3.2.5.1.
Other non-…
Canada
Japan
Saudi Arabia
Nigeria
India
USA
Russia
China
Registration, documentation and procedural barriers by
country and degree of prohibition
1
2
1
1
Prohibitive
1
1
1
Strong
1
1
Regular
2
4
1
8
0
2
4
4
6
8
10
12
14
Number of mentions
© 2013 Grant Thornton UK LLP. All rights reserved.
79
Country
Registration,
documentation,
procedures issue
Interview quote
China
Changing
legislation
 "Our company sent a cheese shipment to China and while the boat was on the
water the Chinese authorities changed the regulations and we had to ultimately
bring the products back."
 "The label on each pack must be photographed, sent to our agent in China to
obtain the relevant authorisations before the products are shipped. This is very
time consuming."
 "China has complex rules, it takes time to understand the regulations and
sometimes even local distributors do not know all the intricacies."
 "In China it is unclear where to go and what documentation needs to be obtained.
Different people say different things locally and you can't trust anyone. It is all a bit
hit and miss."
Cumbersome
Procedure
Unclear
requirements
Russia
Bureaucracy and
corruption
Audit for export
list
Changing
requirements
Nigeria
Changing
requirements
3.3.2.6.
 "In Russia, administrative and bureaucratic challenges are quite difficult. And it can
vary right down to the level of which particular customs officer can resolve that at
a particular point in time."
 "In order to be on the export list, Russia requires an in-depth audit of your
production facility. If you are on the list and not exporting they still want to this indepth audit which for us is very time consuming and costly, as Russia is not a key
market at present."
 "In Russia, requirements change very frequently, but it's worth complying with
them due to the value of the orders. Also a lot of documentation is asked for proof
of origin, proof of manufacturing, health certificates, quality control certificates,
etc."
 "From the consolidator we use in order to export to Nigeria, I understand that they
keep changing requirements and the paperwork we must produce.. So the
legislation, documentation and approval process keep changing."
Taxes, tariffs, duties
Although the interviews did not highlight tariffs as the most frequent or significant
problem encountered by the industry, tariffs are still considered a barrier to trade outside
the EU for the UK agri-food industry and in some cases they can be prohibitive. The
countries where tariffs were most frequently indicated as a trade barrier were: India,
Turkey, China and Russia.
In India and Turkey, tariffs and duties are high across agri-food categories indicating the
closed nature of the market and the use of protectionist tariff measures. Despite being one
of the EU's main trading partners, Turkey applies high tariffs/duties to EU agri-food
products and is viewed as highly protectionist country by the sample of companies
interviewed. This is in line with the tariff data collected in chapter 2, which indicates that
on average across agri-food products (i.e. the 20 product categories longlisted), Turkey
applied 53.2% tariffs. Similarly, India applies on average 57.0% tariffs on food products.
In contrast, interviewees mentioned that China's import duties are not necessarily very high
across product categories (the average is 13.9% as per the analysis performed in chapter 2),
but tariffs are applied differentially, i.e. EU producers are discriminated against as they
have to pay higher duties compared to other regions/countries entering a market. For
example interviewees reported, China applied differential tariffs for fish products
depending on the country of origin: the UK fish is taxed at 10% compared to 3% for
Chilean fish and 0% for fish originating from New Zealand.
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© 2013 Grant Thornton UK LLP. All rights reserved.
Chart 3.3.2.6.1.
Taxes, tariffs, duties barriers by country and degree of
prohibition
Latin…
1
Other non-…
1
Other EU
1
Israel
1
Nigeria
1
Prohibitive
Strong
Russia
Regular
3
China
4
Turkey
3
India
1
1
4
0
1
2
3
4
5
6
Number of mentions
Country
Interview quote
India
 "I have worked across several sectors and India imposes duties across many product categories, whether it
is tea, alcohol or food. The duty tends to be around 30%. But if you are selling from another Asian
country, then the duty drops to 20%. So, in my opinion they are just using duties as a barrier."
 "India may be a market we were discouraged to pursue as they make it harder to enter the market. There
are very high tariffs."
 "We've always toyed with the idea of India because there is a lot of British influence and desire for British
products, but I am quite put off by it as when I go to conferences people tell me the product can get stuck
at customs and there are high import duties."
Turkey
 "Many product categories in Turkey have large duties. They are protecting their own production."
 "Turkey is a large tea producing nation and it is attractive to us because of the consumption levels and also
the middle class population particularly around Istanbul. However, there are both quota and tariffs,
because as Turkey has its own tea production, clearly they're quite protectionist; and the quota's very
limited: it's 200 tonnes of tea from EU origin. So it's very limited in terms of how much tea can come in.
And even within that quota there's a tariff level, which I think is something like 70%. And then you can
bring tea in outside the quota, but the tariff level goes up to 140%."
China
 "China applied differential import tariffs for fish products(for EU suppliers it's 10% while for New
Zealand and Chile 0% and 3% respectively)."
Russia
 "There is an import tariff of 24% on imported tea, although Russia does not grow any tea. In addition,
Russia has a lot of agricultural and food safety documentation as they do not recognise the UK
documentation. They have their own certificates. Just to give you an idea, one certificate can cost you to
£30,000."
3.3.2.7.
Customs
Based on the feedback from the interview programme, China and Russia have the most
challenging customs procedures. The agri-food companies interviewed also mentioned
USA and Japan. However, the nature of the issues encountered at customs was different
for these two groups of countries. In China and Russia, shipments or product samples can
be blocked at customs and refused entry without explanation. In addition, in China the
requirements differ from port to port. In contrast, the USA and Japan have strict quality
controls (e.g. for meat products in the US, while Japan checks the products' weight, with
low tolerance for products weighing more/less than the stated weight). Furthermore, long
shelf-life shipments may take up to three months to clear customs compared to the average
one month, if no delays were experienced.
© 2013 Grant Thornton UK LLP. All rights reserved.
81
Chart 3.3.2.7.1.
Customs barriers by country and degree of prohibition
Nig…
1
1
Aust…
1
1
India
1
1
USA
1
Japan
1
2
Rus…
2
2
2
China
Prohibitive
Strong
Regular
1
3
3
0
1
3
2
Number of mentions
3
4
Country Customs
issue
Interview quote
China
Tariff
description
 "The standards depend of which port you go into. We try to manage that by changing ports.
They follow very strict guidelines which are very black and white and they do not seem to be
interested in the fact that your product is acceptable under EU law. Recently we had to classify
our products into different tariff descriptions in order to be able to get them through. We still
have a problem getting muesli through on the import tariff."
 " We have tried sending samples to people in China and they would end up going missing,
whereas if you send them to Hong Kong they will be there within a matter of days."
Russia
Product
refused
entry
 "The last samples we sent to retailers in Russia were refused entry and when we investigated
they were not willing/able to give us a reason. Therefore, we're shipping our products through
Finland."
 "It is not a major issue, but sometimes we have difficulties getting the products through
customs. We steer clear of corruption and follow the Bribery Act."
Japan
Product
refused
entry
 "When we heard about our shipment, it had been pulled off the regular line and they ended up
measuring every single bag weight. Literally opening the boxes and measuring every single bag
weight and if every single bag was not almost exactly what was on front of the bag say 40 g or
150 g, they would dismiss it I think they have different rules on different rules about the emark, the sensitivity of the amount in every bag. In Europe, it is about 5 to 10%."
3.3.2.8.
Intellectual Property
During the course of the interviews conducted for this report, companies and trade
associations acknowledged that many countries do not respect or enforce intellectual
property. The countries represented in the following graph are not a complete list of
countries where there are IP issues for UK agri-food companies, but those mentioned by
interviewees following a request to name a country where they had experienced issues with
the protection of trademarks or geographic identification (GI).
The intellectual property barriers mentioned fall into two main categories: trademarks and
geographic identification. Both aim to solve the same problem. They act as source
identifiers and a guarantee of quality (through ingredients and manufacturing processes)
and help increase consumer confidence in the product. This increase in confidence can
enhance consumers' willingness to pay for a product. Therefore, having a trademark or GI
has a commercial value and can be a valuable business asset, explaining why companies are
interested in their protection.
It is worth mentioning that the EU takes a different view compared to countries such as
USA with regards to GIs. The US approach is to rely on trademarks and certification
marks which are considered to provide adequate protection for individual producers. In
contrast, the EU has proposed to strengthen the international protection of GIs, but has
found it difficult to find international support for its propositions with WTO.
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Nevertheless, the EU has negotiated the recognition of some GIs with countries in Asia
and Latin America and some progress has been made in recognising certain EU products
with an international reputation, such as Scotch whisky.
Feedback from interviews also reveals that trademarks are not always protected, as local
companies copy brand or denomination of origin names, creating difficulties for the
original product when it attempts to enter the market.
Chart 3.3.2.8.1.
Intellectual property barriers by country and degree of
prohibition
Latin…
1
Other…
1
1
Argentina
1
1
Australia
1
1
India
1
1
USA
1
1
China
1
1
Brazil
1
0
Prohibitive
Strong
Regular
1
1
1
2
3
Number of mentions
Country
Intellectual property Interview quote
issue
China
Geographic
identification
 "China has not respected GIs in the past. There is some progress being
made, as China has recognised 10 EU GIs and protected them legally in
China."
Latin America
(Brazil,
Argentina)
Geographic
identification
 "Some South American countries have not respected GIs (Scotch Whisky
etc.) in the past. Negotiations for GI protection are on-going with South
and Central American countries (incl. Brazil."
Ukraine
Trademark
 "In Ukraine, trademarks are not protected (locals just steal the trademark
before the company even enters the market and it is too hard to change the
situation)."
General
Trademark
 "When you have a massively famous brand, you get your IP or trademark
back. But the problem is in these middle level brands, and I would put our
brands in that category. They are well-known enough that someone has
taken or put a registration for the trademark. We have not had any presence
in the country, but when we decide to enter we realise that someone else
already has the trademark. They are not doing anything with it, they are just
holding the trademark. So we cannot register our trademark and it is then
difficult to build a brand when you actually do not hold the trademark. But
it is also difficult to engage in legal battles with locals, so the opportunity
has to be large enough to warrant the effort."
3.3.2.9.
Remaining barrier types
Outside of the most prevalent trade barriers already described, UK companies face a
number of others:

Despite trade liberalisation some countries impose import quotas. For example,
Canada applies a quota for cheese from the EU and Turkey has a quota on the
quantities of tea imported from the EU. In addition, recently in an attempt to solve
domestic economic problems some Latin American countries such as Argentina and
Brazil have imposed import bans;

The major economic 'blocks' such as the EU and large countries such as the US and
Australia have different support mechanisms for their agricultural sectors, creating
disadvantages for those receiving fewer subsidies. Therefore in the absence of a level
© 2013 Grant Thornton UK LLP. All rights reserved.
83
playing field, UK companies in sectors such as milk, perceive subsidies received by
Canadian and US famers/manufacturers as a commercial barrier; and

Many countries do not offer adequate business conditions, as the ease of doing
business is affected by contract enforcement and corruption control problems.
Country
Tax issue
Interview quote
Russia
Due diligence
 "Russia was a huge opportunity for [alcoholic beverage brand] and we were starting
to do a little bit of work to the point where we would find two or three
importers/distributors that was the first thing. Now the first thing we encountered
was when we were talking to these important distributors trying to understand who
owned those business was extremely difficult. Trying to understand the financial
wellbeing of the business was now impossible because they are just so complex and
very secretive about that so you don‟t really know who you are actually trying to
deal with. What we were doing is we were working with people in the UK who had
worked with these people before so we only had their credibility to tell us they are
okay people but when we tried to find out, we found it very difficult."
Turkey
Quota
 "Many product categories in Turkey have large duties. They are protecting their own
production."
 "Turkey is a large tea producing nation and it is attractive to us because of the
consumption levels and also the middle class population particularly around
Istanbul. However, there are both quota and tariffs, because as Turkey has its own
tea production, clearly they're quite protectionist; and the quota's very limited: it's
200 tonnes of tea from EU origin. So it's very limited in terms of how much tea can
come in. And even within that quota there's a tariff level, which I think is something
like 70%. And then you can bring tea in outside the quota, but the tariff level goes
up to 140%."
84
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Chapter 4. Areas for Government support based
on primary research outputs
Section 4.1. Introduction and scope
A separate project that has been carried out by SERIO and was commissioned by Defra
aimed to look more specifically at how Government can support agri-food SMEs with
their exporting efforts. Therefore, mapping the available resources and making suggestions
for Government support are not key deliverables for this project although these areas were
covered at a high-level during the interviews conducted.
This chapter highlights areas where the Government can improve its support to the
industry and includes quotes from the interviews carried out. The chapter is structured as
follows:

Section 4.2- Business interviews output: presents the views of the businesses'
stakeholders interviewed; and

Section 4.3- Policymakers/industry associations interview output: presents the views of
policymakers and industry associations.
© 2013 Grant Thornton UK LLP. All rights reserved.
85
Section 4.2. Business interviews output
19 out of 29 businesses/corporates interviewed expressed their views on areas where
government could improve its support to reinforce the industry's efforts in exporting. The
areas identified are summarised below:
8
6
4
4
2
2
High level support and
engagement
Other
Bureaucracy, paperwork,
speed of service
NTMs negotiation
Funding, subsidies, trade fair
support
3
Information database
9
8
7
6
5
4
3
2
1
0
Areas for improvement of government support by number of
references
General export advice, indepth market insight
Number of mentions
Chart 4.2.1.
During the interviews, businesses mostly mentioned that they would appreciate the
provision of general export advice as well as more in-depth, practical market insights and
commercial solutions (e.g. reliable potential partners and suppliers by country and product
category, transportation costs, pricing strategy, retail structure by country, consumer
preferences in target countries). In addition, businesses would appreciate the existence of a
centralised source of current information (either in the form of an online database or a call
centre) which would pull together the different requirements, procedures and contacts in
order to export to a specific country. Some of the interviewees understood the size of the
challenge in achieving this for all countries and clarified that the effort should focus on 1020 strategic markets. They also emphasised that this centralised source of information may
have to be delivered in partnership between the Government and industry, provided that
the Government offers the required financial support to set up and maintain the resources.
Beyond these areas, some businesses would like to see greater support in trade fair funding
assistance, faster speed of service and greater efficiency in bureaucracy as well as greater
engagement from the higher ranks of the political scene (e.g. ministers) that could showcase the UK food and drink industry abroad and move it up the government agenda.
Companies acknowledged Defra's support in negotiating and drafting export certificates,
an essential document for companies that export. However, some companies also
mentioned the complications/delays that are sometimes associated with this process,
potentially due to the limited resources available within Defra.
Overall, many of the interviewees acknowledged UKTI's contribution and its on-going
support to their exporting efforts but highlighted the need for more specialised support
across each product and market.
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Area for support
Interview quote
General export
advice, in-depth
market insight
 "There is no one body within the UK to look after export support. There is a range of different
players that all have fingers in this pie. And also we have different requirements to satisfy the
local market. So it gets pretty complex."
 "We would benefit from more government facilitation in the area of exports. But not blind
facilitation. It needs to take into account the objectives of a particular business or a particular
business area."
 "Our view of UKTI is that their expertise is more appropriate for first time exporters and small
businesses, but we know the basics on documentation, letters of credit, health certificates,
certificates of export, etc."
 "UK exporters need research into new opportunities. Not top line research that, but very specific
practical research on how to sell, where are the opportunities e.g. premium food service, top end
retailing in emerging markets."
 "You can get very good information on exports from British embassies and UKTI if you know
where to ask."
 "First, provide with us with basic details about the economy and what is working with key
countries. Second, help us identify who are the right people to work with. Thirdly, help us
understand the exercise duty legal and the cost implications in order for to us to cost through the
products. We have something we call a price tree. What you want to do is understand how much
the product needs to be to the consumer in its competitor set. How much does the retailer need
to make, how much does the distributor need to make. What is the cost of getting it product
there with all the administration etc. so you can work out whether it's a viable market. If someone
could help us get to those elements quite quickly I am sure we could certainly speed the process
up"
 "Multinationals have the resources to invest in a new market and become number 1 market
player in up to 5 years, but SMEs don't and need the Government's support on basic research to
identify the opportunity and do a market opportunity assessment."
Information
database
 "A one stop shop on the regulations for various markets would be ideal."
 "What would be very useful is if the Government had a country-specific hot-desk, which is
something like the Post Office has for applications, a check list. For instance, if I am shipping a
packaged shipment to Australia I would know what to do, but a smaller manufacturer would not.
He would fill two packs of paperwork and then dispatch it and the shipment would get stuck at
customs. He would end up spending all this money without knowing what he had to do."
 "One stop shop for getting information and paperwork would be a quicker way of getting
product out of the country."
 "The challenge is not selling the product, but making sure that the product is legal for that
country. There is not an easy source where we can go to check all the requirements for a country
because there is a lot of interpretation about what is and is not legal. We went to 2
agencies/companies that help with export activities and got conflicting advice."
Funding,
subsidies, trade
fair support
 "UKTI offers small subsidies to UK businesses wishing to attend large international trade fairs
where they are up against Italian, French and German businesses, which are heavily subsidised by
their governments who take their food businesses very seriously."
 "Presence at trade shows is very important as a small business as other participants, such as
distributors start taking you seriously after seeing you at the fairs for several years. That is why it
is important for the Government to incentivise firms to participate."
 "We obtained funding towards the cost of travel to China through the EMRS scheme, (Export
Marketing Research Scheme), a programme set up for exporters to do preliminary research on an
export market."
NTMs negotiation
 "If we all worked on the same set of rules, life would be a lot easier. We know it's a difficult one,
but we'd like to see to what extent the government can help with standardising the rules across
regions."
 "They could seek to harmonise Chinese requirements with the current EU requirements. And get
them to take the EU health stamps as a standard. In some areas, they had history of disease, you
might add on a few extra layers. But it would be very useful to start from a base cause and then
really understand why the extra controls are needed. It is going to be difficult, but if we are
serious about exporting, it has to be done. I think going around the problem is not good. Then
you just leave it to every single company to try to find a way around the regulations."
Bureaucracy,
paperwork, speed
of service
 "The whole process of getting information and paperwork done is slow."
High level support
 "The annual trade show in Germany is of major importance for UK confectionery and
Government presence at that would be very useful. Other countries have senior political
delegations and I don‟t think we, as a country, do enough to go and bang the drum about what
we are doing in the industry. It sometimes feels very lonely to be there as part of a nonsupported, primarily privately funded British pavilion."
 It would be to recognise that non-tariff barriers are worthy of some attempt to harmonise. A
trade show such as ISN in Germany is of major importance for UK confectionery, so
Government presence at that would be very useful. Other countries have senior political
delegations and, I don‟t think we as a country do enough to go and bang the drum about what
© 2013 Grant Thornton UK LLP. All rights reserved.
87
Area for support
Interview quote
we're doing in the industry. It sometimes feels very lonely to be there as part of a non-supported,
privately funded British pavilion."
Government and
industry
association
support for
promotion
88
 "The Norwegian salmon industry in niche markets, such as China, has been there since mid-90s
and also they have sold a lot of salmon to Russia over the last 2 years. Through their own
government and the Norwegian industry bodies, they are very active in these markets in terms of
promotions. They are actually spending money in these areas and these countries. They have very
detailed well thought and resourced campaigns to promote their products. Whereas the Scottish
development agency, SDI and others, to be honest, I do not know what they do. They seem to
have some money but it is never very targeted. It is not very market addressed, it is not
promotional. It is more of a, they have a presence on the ground and they go around give you a
bit of market insights. Which you could also find out from someone else anyway. They may be
helpful perhaps with some of the documents that… which local agencies types you have to jump
through. But in terms of market development, they are pretty ineffectual."
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 4.3. Policymakers/industry associations interview
output
Similarly, 8 out of 13 policymakers and industry associations interviewed expressed their
view on areas for further government support. The areas identified are summarised below.
Chart 4.3.1.
6
6
5
4
3
2
1
1
1
1
NTMs negotiation
2
2
High level support and
engagement
3
Bureaucracy, paperwork,
speed of service
Number of mentions
7
Areas for improvement of government support by number of
references
Funding, subsidies, trade fair
support
Information database
General export advice, in-depth
market insight
Other
0
Whilst the feedback is very similar to the corporates' outputs, the policymakers and
industry associations have also highlighted a number of different areas where the
government should focus its efforts. Such areas included (under 'Other' in the chart
above):

Better communication and raising awareness in the industry about the existence
of various bodies available to provide export support and the area they are
responsible for;

Better communication and joined up strategy with subcommittees across the EU to
allow a more effective strategy to access new markets; and

Insisting on a more scientific approach when assessing and imposing SPS barriers at
the EU level rather than a precautionary approach that may also cause retaliation
measures from the other party and result in limiting/blocking access for UK products
to the markets.
Area for support
Other
Interview quote
 "I think one of the real challenges we have in opening up trade negotiations is that the EU is
taking a very precautionary approach. Whether it is on GMOs or lactic washing, this is a
particular issue that comes up time and time again in the European Parliament, where MEPs
are very quick to jump on populist policies, ignoring the science behind them."
 "Even as far as publicity goes, that is an issue. Last year, we went through quite a big
promotion to raise awareness amongst businesses, but recently we have not had that much
time to stand by it and not that many resources to support it either."
General export advice,
in-depth market insight
 "Not top line research, but very specific practical research on how to sell, where are the
opportunities e.g. premium food service, retailing in emerging markets, etc."
Information database
 "Helpdesk for people to quickly address issues that arise. People often don't know what they
know until it becomes a problem."
Funding, subsidies,
trade fair support
 "We've got a food trade fair programme that we could enhance because if you provide some
basic research on the market and run a trade mission, arrange to meet buyers, you can
provide the stimulus to do it. Grants are available towards the cost of going to a trade fair,
but to be effective they need to be increased."
© 2013 Grant Thornton UK LLP. All rights reserved.
89
Area for support
Interview quote
Central export
documentation office
 "Each piece of documentation we need for exports comes from a different agency. The
heath certificate, the export certificate, the proof of manufacturing come from different
places, but they are not unobtainable. There is no central body that you can go to get it
done, so you just have to go to the right place. It is time consuming and it would be easier
for exporters if there was more centralisation."
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Chapter 5. Case studies
Section 5.1. Introduction and scope
During the interviews that were conducted with UK agri-food businesses (the outputs of
which were presented in chapters 3 and 4), various success stories across different food
and drink sectors were discussed and noted. This section presents six case studies which
represent example initiatives taken both by small and larger businesses and ways in which
they dealt with barriers met, highlighting the importance of expanding to markets beyond
the EU and the expectations businesses have across markets. The example case studies are:

Dorset Cereal – Muesli manufacturer;

Eat Natural – Cereal bars manufacturer;

Halewood – Producer and importer of wines and spirits;

Belvoir Fruit Farms – Soft drinks producer;

Nairn's Oatcakes – Oatcakes producer; and

First Milk – Dairy co-operative.
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Section 5.2. Case studies
1
Dorset Cereal – Muesli manufacturer
A medium-sized Dorset-based company manufacturing premium breakfast cereals, such as
Mueslis, Granola, porridge and cereal bars. The EU nations only account for a portion of
the company's exports with Asia-Pacific, North America and other non-EU nations
accounting for a significant portion of the exports.
The company's export strategy has been to first focus on markets with large cereal markets,
secondly on markets with demand for muesli and lastly on markets where Dorset Cereal
has had some traction (in terms of working with a good distributor and selling through the
'right' retailers, and a positive brand image amongst consumers of Dorset Cereal as a
British product).
In the short term, the company is focusing on growing the North-American markets.
However, they are also currently targeting China, India, Australia and Russia as they see
many opportunities across these nations in the long-run. While the company has been in
Russia for longer than 10 years, they first entered Australia and India five years ago. The
company did not meet any particular difficulties in entering the Chinese market primarily
because of establishing relationships with the right distributor. The largest challenge the
company sees in China is the large duty applied on their product (25%) which is a premium
one and already expensive for Chinese consumers. In addition, other difficulties the
company has faced in their trade relationships with certain emerging markets are frequent
changes in regulations without prior consultation. It is therefore vital that businesses
establish a close working relationship with local distributors to minimise these issues.
Dorset Cereal works primarily with distributors in the foreign markets as the scale of the
business does not yet justify setting up any local operations. However, the company does
deliver directly to some of its customers. The company believes however that the further
the distance from their home market, the more complex it becomes to directly manage and
service the market.
2
Eat Natural – Cereal bars manufacturer
Eat Natural is a medium-sized UK firm primarily producing cereal bars and breakfast
cereals. The company exports to almost all EU countries but also to Canada, USA, UAE,
China, India, Russia and other smaller markets outside the EU. Despite the fast growing
middle classes across emerging markets, Eat Natural continues seeing most of the
opportunities for exports arising within the EU and North America. This is primarily due
to different consumer tastes and preferences for their product. However, Praveen Vijh, Eat
Natural's co-founder, recognises that USA may be a challenge to break into due to the
structure of the retail market.
Praveen emphasised that "every single country we have tried to enter has an issue, but
most of the issues are in terms of the paperwork needed and communication with local
authorities. It is very important for someone to have a clear understanding of all the
regulations they need to comply with and how to obtain all the necessary paperwork".
Even though Praveen recognises that a small business may struggle to deal with all the
work needed to export outside the EU, he states that the above issues are not really
prohibitive if a company has the resources and time to deal with them. From Praveen's
experience, Kenya, India and Russia were the most challenging markets to enter in terms
of complex requirements and communication issues. However, as Praveen stated, "if the
opportunities are there, market barriers can be overcome with a can-do attitude".
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Overall, as a response to the different labelling requirements around the world, Eat Natural
makes use of 5 different types of packaging across different markets to ensure its products
meet local regulatory requirements.
3
Halewood – Producer and importer of wines and spirits
Halewood is a UK-based alcoholic drinks distributor and manufacturer with a portfolio of
more than 600 products. Halewood's Director Sales - International, Graham Gibson, states
that the company recently reviewed and re-focused its export strategy resulting in exiting
certain markets and rationalising their export product portfolio. Instead, Halewood decided
to concentrate on a few key products in which they saw export potential and supply them
to markets where they already had a strong footprint and good contacts. In addition, the
company developed a new international price strategy to ensure its products were
competitive.
As a result, the company has placed most of its efforts on exporting Crabbie's, an alcoholic
ginger beer, which has proven very successful with the UK market. However, due to the
particular ginger ingredient, the company had to target markets with similar tastes to the
UK, which are familiar with and consume ginger beer. As such, the company identified
Australia, Canada and USA and these also have large UK expatriate populations and by
establishing relationships with key distributors for UK holiday resorts, the company has
been very successful in developing all of these markets.
Specifically to USA, it took six months for Halewood to identify a suitable partner and
another six months to obtain TTB (Alcohol and Tobacco Tax and Trade Bureau) approval
for its liquid and labels before being able to distribute it across 16 states. Moreover, in the
case of the US, a requirement for either a beer base or Malt liquid was required to meet the
TTB approval and Halewood had to change the manufacturing process for its ginger beer
and increase the alcohol content while keeping the same smell and taste in order to obtain
the approval for distribution.
Going forward, the company plans to expand its presence in the markets above and
develop new markets in South America and in Asia (e.g. Indonesia, Singapore and Hong
Kong), where consumers may be familiar with ginger as a cooking ingredient, but may not
enjoy it yet as a drink component. However, as Graham Gibson mentioned, before
attempting to enter these markets, the company must first develop an understanding of
these markets and the commercial parameters behind them (i.e. consumer tastes and
preferences, market structure and size, taxation pricing, distributors and retailers, etc.) to
mitigate risks and ensure there will be sufficient demand for the company's product.
4
Belvoir Fruit Farms – Soft drinks producer
A small Lincolnshire-based soft-drinks company manufacturing cordials, pressés and still
fruit drinks. The company's main export product has been their elderflower drinks which
are exported to 21 countries including Germany, Sweden, Denmark and Finland but also
outside the EU: Canada, USA, Japan, Russia, Singapore, Malaysia, Hong Kong, Indonesia,
Australia, New Zealand and others. So far the company's strategy has been targeting
markets where the locals are familiar with elderflower, which is the drink's main ingredient.
As Pev Manners, the Managing Director at Belvoir Fruit Farms stated, "We are not seeking
to make exports our core activity but we have discovered that our delicious drinks are
popular overseas as well and these markets offer a great breadth of opportunity."
The company currently sees most of current export growth coming from Canada, a market
with high average income per capita and where the currency has been very strong over the
last few years, which favours UK exports. Pev Manners, their MD, has found difficulties in
penetrating the US market primarily due to difficulties in finding the right distributor but
this may now be changing after a meeting at the ANUGA show in Germany last year
© 2013 Grant Thornton UK LLP. All rights reserved.
93
In the long term, the company is seeking new business most actively outside the EU,
focusing on developing their exports to the Middle East, which as Pev states "has a whole
series of different rules". Whilst as a small volume exporter, products with English labels
are accepted by the local authorities, as the volume of exports grows larger and larger,
Arabic labels are required. However, the company does not see that as a significant barrier
to entry as the commercial opportunity is higher than the cost associated with creating
customised labels for the region. Last but not least, Pev highlights the South-East Asian
region as another opportunity area for the long-run due to the region's population and
economic growth as well as consumers' preferences for sweetened soft drinks.
5
Nairn's Oatcakes – Oatcakes producer
An Edinburgh-based medium-sized firm manufacturing cereal snacks out of wholegrain
oats. The company's exports are mainly sold to the North American market (the company
has been present in USA for more than 12 years) but it also sells to EU and non-EU
nations, Africa, Asia, Middle East, Australia and New Zealand.
The company's short to medium term focus is on English-speaking, westernised markets
with long historic links to the UK such as USA, Canada, Australia, New Zealand and
South Africa. These countries also have similar eating habits to the UK. However, over the
next three to five years, the firm plans to focus on the fast growing emerging markets of
China and India as well as UAE which is a wealthy nation with a lot of UK expatriates. So
far, the company has not had sufficient resources to investigate and assess these markets
but it intends to dedicate resources for this purpose going forward. In terms of China and
India, the company understands that consumers in these countries do not eat cereals like
they do in the UK and it will take some time before they become aware of the benefits that
cereals have and before their diets become more westernised.
According to Katie Birrell, the company's Export Sales Manager, when trying to enter a
new market, the company will first make use of personal networks to get in touch with
local distributors. Alternatively, they will use contacts they meet at trade shows or
companies and organisations that have market knowledge and distributor databases.
In terms of market access challenges confronted, Katie highlights UAE's requirement that
all imports are registered prior to entering the country. However, as per Katie, "our
importer takes care of it. If we had to deal with this issue ourselves, it would be much
more complicated and would be seen as a barrier to entry".
6
First Milk – Dairy co-operative
First Milk is the UK‟s only major dairy company owned by British dairy farmers. Over the
last few years, the company has taken a different path to diversify its business through
embarking on new opportunities to access greater added value routes – with the key aim of
driving the best possible returns for its farmer shareholders.
As well as growing its customer base and opportunities in the UK, First Milk is fast
developing its export business and today, the company exports to a wide variety of
countries around the world.
First Milk currently has 2000 farmers supplying milk to its sites across the UK, it is driven
by a passion for innovation and sustainability and is growing its brands and diversifying its
product base by taking advantage of global market opportunities.
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Chapter 6. Shortlisting target countries and
products
Section 6.1. Introduction and scope
Following the identification of the longlist of target countries and products (Chapter 2) and
after having carried out interviews with UK businesses and policymakers (Chapter 3), the
next step was to proceed with shortlisting target countries and product categories for the
UK to focus on exporting. The process detailed in Chapter 6 was based on the collection
and analysis of new parameters and data, but also took into consideration the interview
findings. In order to obtain the final shortlisting of six country and product combinations
from a starting longlist of 600, this chapter is structured as follows:

Section 6.2- Methodology overview: provides a high-level overview of the
methodology followed in order to shortlist the original 600 inputs to this stage (from
the 30 countries and 20 products identified in Chapter 2) down to six specific
opportunities, which will be evaluated in Chapter 7;

Section 6.3- Step 1 of the analysis: having built a logic tree and having collected data
across a number of parameters (across countries and products), this step first reduces
the opportunities from 600 down to 118 (across 20 countries and 19 product
categories) based on quantitative criteria. It then qualitatively reduces the 118
opportunities down to 78 (across 11 countries and 12 product categories);

Section 6.4- Step 2 of the analysis: a separate country analysis is being undertaken and
by accounting for interview findings as well, this step qualitatively and quantitatively
reduces the opportunities from 78 to 56 (across seven countries and 11 product
categories); and

Section 6.5- Step 3 of the analysis: finally, after accounting for supply and demand
parameters, six specific opportunities are being shortlisted (across four countries and
six product categories) to evaluate in Chapter 7.
Overall, the final six products were chosen following a rigorous analytical research process
involving a wide range of economic and trade indicators, including the target country's
market size, the relative openness of that market and the forecast growth in the particular
product category under investigation amongst others. Although the six products resulted
from an extensive quantitative and qualitative analysis, they represent a good spread across
emerging and developed markets and across highly processed and lightly processed goods.
It is important to note that not being in the final shortlist does not signify that there is no
opportunity for a specific product. However, given the timeline of this project, not all
opportunities could be sized and therefore the options available had to be prioritised.
© 2013 Grant Thornton UK LLP. All rights reserved.
95
Section 6.2. Methodology overview
Taking into account the longlists from Chapter 2, Grant Thornton undertook an extensive
shortlisting process to identify key products across countries which entail the greatest
potential for the UK agri-food industry if the market access barriers around them were to
be removed. This process was divided into three main steps; the outputs of these three
steps and the methodology behind them are shown at a summary level below and
explained in more detail in the sections that follow:
Chart 6.2.1.
Methodology followed in shortlisting countries and products
Similarly to Chapter 2, the analysis in Chapter 6 has been conducted for products at the 4code HS level (please note that the whole Food and Drink sector is divided into 184 4code HS categories) due to lack of market data for all 6-code HS categories and countries.
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© 2013 Grant Thornton UK LLP. All rights reserved.
Section 6.3. Step 1 of the analysis
Given the need to assess and shortlist 600 possible combinations (i.e. 20 products across
30 countries) within a short timeframe, the parameters attached below were deemed to be
the most relevant and most easily measurable in assessing the degree of openness of a
market for a specific product as well as assessing the size of the opportunity for that
product at a high level. This allowed the effective determination of which products and
countries are relevant to the scope of this project and to select a shortlist. The parameters
used at this stage of the analysis were:
Table 6.3.1.
Parameters used to drive Step 1 of the analysis
Parameter
Source
Total imports by country and product (value and volume), 2006-2011
Trade Map
UK exports by product and country (value and volume), 2011
Trade Map
EU exports by product and country (value), 2011
Trade Map
Domestic retail market size (volume and value), 2011-2016
Euromonitor
Tariff levels imposed on UK exports by product and country
Trade Map
Non-tariff measures imposed by product and country on EU exports
MADB & WTO
Open Markets Index by country
International Chamber of Commerce
(ICC)
After collecting and processing the data on the parameters above across the 20 products
and the 30 countries, three main conditions were applied, all of which had to be met in
order to shortlist a specific product across a certain market. These conditions were
related to:
1
1st condition – market access: The relative 'openness' of a certain market and the
barriers that appear to be imposed across a certain product (as measured by the open
markets index);
2
2nd condition – market size: The market size for a certain product across a market
(as measured by Euromonitor's retail value of a food/drink segment or where this data
was not available, the value of imports of that particular food/drink category); and
3
3rd condition – market growth: The growth prospects for the product and market
(as measured by the retail size value and volume forecast for a particular product
category in a country provided by Euromonitor).
Overall, the products that remained in the list at the end of this filtering stage are
characterised by the following:

The UK exports have not adequately penetrated the target market;

There are high trade barriers in place (tariff or non-tariff ones); and

The domestic market for the target product is sizeable and has healthy
growth prospects.
© 2013 Grant Thornton UK LLP. All rights reserved.
97
The flow chart below presents a 'logic tree' of the three conditions applied at Step 1 of the
analysis by product and country including the sub-conditions for each (I – VII):
Chart 6.3.1.
Shortlisting 'logic tree' at Step 1 of the analysis
For the categories and countries where Euromonitor did not have data on the retail market
size (all countries across product categories 0101, 1901, 2101, 2106), this was replaced with
the absolute value of imports (2006-2011). This data was used for the 2nd and 3rd
conditions. Also, Euromonitor could not provide market sizes in value terms for meat and
seafood products and, as such, volume terms were solely used for these products. In
addition, for soft drinks and alcoholic drinks, Euromonitor reports value in 'total value'
terms (which includes retail channels as well as restaurants, bars, hotels, etc.) rather than
'retail value' (which only includes retail channels) as with the rest of the products.
The sub-conditions above were divided into 'guiding' and 'determining', which indicates
that the guiding ones do not have any direct impact on the shortlisting, or not, of a specific
product across a country. The role of the guiding ones is rather indirect in assessing and
diverting a product across a country to the most relevant 'determining' sub-condition,
which determines whether a product should be shortlisted or not. In some cases, it may
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© 2013 Grant Thornton UK LLP. All rights reserved.
appear that 'guiding' and 'determining' sub-conditions are assessing similar criteria,
however it should be noted that the role of the assessment in each case did have a different
purpose and that the outcome from these assessments was also different. This becomes
clearer in the descriptions of each sub-condition below.
Throughout the 'logic tree' parameters are benchmarked against a number of measures (e.g.
median, average, average excluding outliers, EU average, etc.). In every case stringency was
tested against measures, which were deemed to be conservative as well as stringent enough.
The aim was to progressively shortlist countries/products throughout each sub-condition
(rather than exclude a large number of countries/products in a single subcondition/filtering stage and almost zero at the following one) in order to provide a
reasonable number of shortlisted products and countries (indicatively, from the original
600 product/country combinations, aiming for c.100 at the end of this process.
The rationale and the approach followed for each sub-condition in the 'logic tree' is
as follows:
1st condition – market access
i
Does the target nation import enough of the product (either in absolute terms
or as a % of domestic market size)? This 'guiding' sub-condition was applied to
ensure that markets which do not import heavily were not taken into consideration
in the following sub-condition because even if the UK market share had turned out
to be large enough (which is being assessed by sub-condition II), it may have been
on a considerably small import base (and therefore moved to sub-condition III).
Therefore, it did not represent a major opportunity in the short to medium term and
would thus not support the purpose of this project. To address this, the approach
looked into both the absolute levels of imports of a product category (in value
terms) and the share of imports of that product as a percentage of the total domestic
market. In the first case (i.e. absolute import levels), the import value was compared
against the 30-country average for that product after removing the top two and
bottom two values (to control for outliers that may distort the average value, such as
in the case of USA and China), whilst in the latter case (i.e. for import share), the
share of imports was checked against the 30-country average for that product.
ii
Is the market share of UK exports smaller than the market share of UK
exports within EU27? The UK's export market share within the EU27 was used as
a benchmark, and if in any of the 30 markets, the UK had a share equal or above
that in the EU27 for a product, the country/product was removed from the
shortlist. This was a conservative approach as the EU is an open market for UK
products and the UK is expected to have significantly higher market share within
the EU than outside (even if barriers were removed, it would be ambitious to
assume that the UK can achieve similar-to-EU penetration rates at these non-EU
markets). This ensures that the approach is not too stringent from the beginning
and reduces the risk of eliminating markets that could offer a potential
growth opportunity.
iii
Does the ICC rank the target country below average in terms of trade
openness and trade policy? This is also a 'guiding' sub-condition, which assessed
whether the UK or any EU market exported effectively to a specific market. This
sub-condition assessed the 'market openness' ranks of counties as measured by the
ICC. The ICC measures 'market openness' both in terms of trade openness
(accounting for trade-to-GDP-ratio, merchandise imports per capital ratio, trade per
capital ratio and real merchandise import growth) and trade policy (accounting for
average applied tariff levels, complexity of tariff profile, number of anti-dumping
actions and efficiency of import procedures). If the ICC deemed a market to be
© 2013 Grant Thornton UK LLP. All rights reserved.
99
below average in terms of trade openness sub-condition IV was ignored (and moved
to sub-condition V).
iv
Do the UK or the EU export effectively to this market (i.e. do the UK or the
EU rank well in exports?)? If a country ranked above average in market openness,
this sub-condition then checked whether the UK or any other EU market exports
effectively to it. This was because in some cases the UK may not have a significant
market share, but another EU market may rank highly due to a strong export
performance. In this case, the UK's weak export performance may not be associated
with trade barriers, but more likely with other cultural and commercial issues, which
are not in scope for this project.
v
This sub-condition aimed to check the market openness at the product level for
each country (unlike the 'guiding' sub-condition III, which assessed market
openness at the country level). This was done in three stages:

Is the share of imports as a % of the total domestic retail market size
smaller than the product average? The first check of market access for a
specific product involved assessing the share of imports of a product as a
percentage of the total domestic market and benchmarking against the 30country average. This step was taken into consideration because all NTM
databases expressed concerns around the exhaustiveness of the data collected
across countries and products and since it was not possible to assess the
severity of each NTM. As such, additional measures to assess the relative
closeness of a country across products were necessary.

Is the number of NTMs applied by the target market on EU exports
above average for the product category? The Step 2 involved compiling the
number of NTMs applied by each target market on EU imports using a WTO
database from 2009 and the European Market Access Database. Then
benchmarking them against the 30-country average imposed across a product
category.

Is the tariff rate applied by the target market on UK exports above
average (excluding outliers) for the product category? The final stage
looked into the level of tariffs imposed on UK exports and benchmarked them
against the 30-country average excluding outliers (i.e. top two and bottom two
values).
Tariffs were benchmarked against the 30-country average excluding outliers in
order to account for some countries that apply particularly high tariff rates
across certain products (e.g. Egypt applying c.1,000%-3,000% tariff on
alcoholic drinks).
All parameters (including tariffs) had an impact and when applied all together
reduced the number of products/countries from 495 to 284.
2nd condition – market size
vi
Is the domestic retail market size (in terms of volume) larger than the
average (excluding outliers) of the sample population? This sub-condition
checked indicatively the size of the opportunity by assessing the size of the domestic
market in volume terms and benchmarking against the 30-country average excluding
the outliers (i.e. by removing the top two and bottom two values). This eliminated
any small markets from the shortlist (addressing the short to medium-term scope of
this engagement). However, even if a country was small overall, but generated
sufficient demand for a specific product, then it passed this test.
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3rd condition – market growth
vii The last step before shortlisting a product included testing for its future potential.
This was done in two stages:

Is the CAGR for the domestic retail market size (in terms of volume)
projected to be above the 33rd percentile during 2011-2016? The analysis
compared the CAGR forecast for its domestic market size between 2011 and
2016 against the 30-country 33rd percentile. The 33 percentile benchmark was
used
rather than the median or average because it was deemed flexible yet
conservative
enough; and

Is the domestic retail market size (in terms of volume) expected to be
sizeable (i.e. above the median) in 2016? This tested a country's forecast
market size in 2016 against the 30-country median (which was more relaxed
than the 30-country average excluding the outliers used in the 2nd condition).
This approach ensured that the selection did not discriminate against developed
countries that may not offer high growth prospects (and are therefore rejected
under the CAGR test above), but are large markets for high-value food and
drink products (e.g. Japan).
Both parameters had an impact on the shortlisting and eventually reduced the
total remaining products/countries from 124 to 118.
As a result of this filtering process, out of the 600 original options from the longlist (across
20 products and 30 countries), the logic tree reduced the combinations to 118 (across 19
products and 20 countries) through an extensive analytical process.
This list of 118 combinations was qualitatively reduced to 78 (across 12 products and 11
countries) based on incidence by product and country. 11 countries had five or more
shortlisted products (out of 20 originally) and, out of these 11 countries, 12 product
categories had five or more countries shortlisted. This set of 78 options was then taken
forward to Step 2 of the analysis. The reason behind following this 'prevalence' approach
was justified based on the consideration that it was more appropriate to pursue trade
negotiations in a more targeted manner with a smaller number of countries than otherwise.
Similarly, removing the barriers for one product (e.g. meat or dairy) with one country,
might have a domino effect to remove barriers for that specific product across other
countries. As such, please see below the shortlist at the end of Step 1 of the analysis:
© 2013 Grant Thornton UK LLP. All rights reserved.
101
'0204
'0207
'0302
'0306
'0401
'0406
'0902
'1806
'1905
'2103
'2202
102
Total
USA
Turkey
Russia
Mexico
Japan
Indonesia
India
Egypt
China
Brazil
Argentina
Product code
'0201
Shortlist of countries and products at the end of Step 1 of the
analysis
Product label
Table 6.3.2.
Meat of bovine
animals, fresh or
chilled
Meat of sheep or
goats - fresh,
chilled or frozen
Meat & edible
offal of poultry
meat
Fish, fresh,
whole
1
1
1
1
-
-
1
1
1
-
1
8
-
1
1
1
1
-
-
1
-
1
-
6
1
1
1
-
1
-
1
1
1
-
1
8
-
1
-
1
1
1
1
-
1
-
-
6
Crustaceans
Milk and cream,
not concentrated
nor sweetened
-
1
1
-
1
1
1
1
-
-
1
7
-
1
1
-
1
-
-
1
1
-
-
5
Cheese and curd
Tea
Chocolate and
other food
preparations
containing cocoa
Bread, biscuits,
wafers, cakes
and pastries
Sauces mixed
condiments &
mixed
seasonings
Non-alcoholic
beverages (excl.
water, fruit or
vegetable juices
and mineral
water)
1
1
-
1
-
-
-
1
1
1
-
6
-
-
1
-
1
1
1
-
1
1
1
7
1
1
1
-
1
-
-
1
1
1
-
7
-
1
1
1
1
-
-
1
1
1
1
8
-
1
1
-
-
1
-
1
1
-
-
5
1
1
1
-
-
-
-
1
1
-
-
5
Total
5
11
10
5
8
4
5
10
10
5
5
78
© 2013 Grant Thornton UK LLP. All rights reserved.
Section 6.4. Step 2 of the analysis
As presented in the methodology diagram (chart 6.2.1), as part of Step 2, a separate
country analysis was first undertaken. This analysis ranked the 11 countries identified from
Step 1 based on the overall size of the food and non-alcoholic drinks market, its growth
prospects, as well as the 'ease of doing business' in these markets based on indicators
provided by World Bank, as shown in the table below:
Table 6.4.1.
Parameters used and weighting applied in Step 2 of the
analysis
Weight
Parameter
Source
Doing Business - Enforcing Contracts
World Bank
0.10
Control of Corruption Indicator
World Bank
0.10
Logistics Performance Index
World Bank
0.10
Total consumer expenditure on food and non- alcoholic drinks (value), 2011
Euromonitor
0.50
CAGR of consumer expenditure on food and non-alcoholic drinks, 2011-2016
Euromonitor
0.20
The weightings above were selected and agreed with Defra because it was deemed most
appropriate to place most of the focus on the size of the market and its prospects rather
than the ease of doing business in these markets. Please note that the consumer
expenditure on the food and non-alcoholic drinks refers to the whole agri-food industry of
each country rather than the individual product categories that were examined during Step
1 of the analysis.
In the following table, each of the 11 shortlisted countries' performance has been
highlighted in green and indicatively ranked amongst the initial longlist of the 30 countries
for comparative purposes:
© 2013 Grant Thornton UK LLP. All rights reserved.
103
Table 6.4.2.
Country ranking for Step 2 of the analysis
Country
Ranking
Score
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
United States of America
Russian Federation
China
Brazil
Japan
India
Turkey
Mexico
Australia
Indonesia
Canada
Thailand
Republic of Korea
Argentina
Egypt
Oman
South Africa
Nigeria
Macao
Hong Kong
8.70
8.60
8.40
8.00
7.90
7.80
7.20
7.10
7.00
6.90
6.30
6.10
6.00
5.80
5.70
5.67
5.50
5.30
5.00
4.90
21
22
23
Chile
Paraguay
Saudi Arabia
4.70
4.67
4.60
24
25
26
27
28
29
Singapore
Algeria
New Zealand
Colombia
Malaysia
Israel
4.50
4.50
4.40
4.40
4.20
4.10
30
United Arab Emirates
3.80
In order to validate that not too much weight was assigned to market size at the expense of
the World Bank indicators, a sensitivity analysis was conducted by assigning collectively
0.50 to the three World Bank indicators (rather than 0.30 as done in the analysis above),
0.40 on the current market size and 0.10 on the market growth (rather than 0.50 and 0.20
respectively). As a result, there were no significant differences in the outputs, especially in
relation to the top 10 countries ranked above. It is worth nothing that Russia moved down
to 4th position, Japan moved up to 2nd, Australia moved up to 5th and Indonesia was the
only country that left the top 10 countries and moved to 13th position.
Based on the country ranking above, the 11 countries (from Step 1) were further
shortlisted. At this stage the number of products shortlisted within each country (from
Step 1) were accounted for as well as the industry/policymakers interview outputs. As
such, the following countries were excluded:

Argentina ranked low in the country ranking, had limited number of products
shortlisted and none of the interviewees expressed interest in exporting to Argentina;

Egypt ranked the lowest (amongst the 11 countries) in the country ranking, had limited
number of products shortlisted and only one interviewee was targeting Egypt;
104
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
Indonesia ranked ninth(amongst the 11 countries) in the country ranking, had only
four products shortlisted (the fewest amongst the 11 countries) and only one
interviewee was targeting Indonesia; and

Turkey even though it ranked 7th above Mexico, it had much fewer products
shortlisted. Moreover, Turkey is a country that the EU is closely negotiating with so it
was deemed more appropriate to focus on another country instead.
Product '0406 – Cheese and curd' was removed from the shortlist because, once the above
four countries had been removed, it was shortlisted only across three countries. As such, at
the end of the Step 1, there were 78 options shortlisted (across 12 products and 11
countries) and at the end of the Step 2, there were 56 options shortlisted (across 11
products and 7 countries). Table 6.4.3 shows these 56 options, with '1' indicating a product
has been successfully shortlisted across a specific market and '0' means it has
been excluded:
Total
USA
Russia
Mexico
Japan
India
Brazil
China
Shortlist of countries and products at the end of Step 2 of the
analysis
Product
label
Product
code
Table 6.4.3.
'0201
Meat of bovine
animals, fresh or
chilled
1
1
0
1
1
1
1
6
'0204
Meat of sheep or
goats - fresh,
chilled or frozen
1
1
1
0
1
0
0
4
'0207
Meat & edible offal
of poultry meat
1
1
1
1
1
1
1
7
'0302
Fish, fresh, whole
1
0
1
1
0
1
0
4
'0306
Crustaceans
1
1
1
1
1
0
1
6
'0401
Milk and cream,
not concentrated
nor sweetened
1
1
1
0
1
1
0
5
'0902
Tea
0
1
1
1
0
1
1
5
'1806
Chocolate and
other food
preparations
containing cocoa
1
1
1
0
1
1
0
5
'1905
Bread, biscuits,
wafers, cakes and
pastries
1
1
1
0
1
1
1
6
'2103
Sauces mixed
condiments &
mixed seasonings
1
1
0
0
1
1
0
4
'2202
Non-alcoholic
beverages (excl.
water, fruit or
vegetable juices)
1
1
0
0
1
1
0
4
Total
10
10
8
5
9
9
5
56
© 2013 Grant Thornton UK LLP. All rights reserved.
105
Section 6.5. Step 3 of the analysis
As presented in the methodology diagram (chart 6.2.1), Step 3 of the analysis evaluates the
56 product/country combinations in order to select six of them for the last stage of the
engagement. This was undertaken taking into account the following considerations:

Supply side considerations: what the UK has to offer and what it is exporting
effectively to the EU as well as globally; this indicates the likelihood of success and acts
as a binding tool to the final shortlist; and

Demand side considerations: what are the local demand characteristics and which
markets are the most attractive to pursue?
The supply and demand considerations have been expressed through a range of parameters
which are detailed below. All parameters for each country/product category were assessed
in order to select the final six product/country combinations. Please note that although the
recommendations are based on a qualitative analysis, they are grounded in data/evidence
provided by the various parameters and nuanced by insights from the primary research.
Section 6.5.1. Supply side considerations
At this stage, each of the 11 products' worldwide RCA and their current value of UK
exports within the EU27 market were accounted for. These two parameters indicate at a
high level what the UK is exporting effectively to an open market (i.e. the EU27) and its
comparative advantage relative to the rest of the world, highlighting to an extent the
opportunity across each product.
The prioritisation below does not demonstrate where the largest opportunity is across the
seven shortlisted countries, it only indicates where the UK appears to be more successful
in exporting these products in the open EU market and at a worldwide level. Based on this
reasoning, amongst the 11 product categories, the UK may be more successful (in absolute
value terms) in exporting 'breads and biscuits' and 'sheep meat' than 'sauces' and 'tea'. The
following table illustrates the output and ranking when the two parameters were applied.
Table 6.5.1.1.
Product prioritisation for Step 3 of the analysis
Product label
Rank
Export value
to EU27, 2011
Agri-food
RCA, 2011
1
Bread, biscuits, wafers, cakes and pastries
$802m
2.47
2
Meat of sheep or goats - fresh, chilled or frozen
$587m
5.53
3
Meat of bovine animals, fresh or chilled
$608m
1.75
4
Milk and cream, not concentrated nor sweetened
$470m
3.23
5
Non-alcoholic beverages (excl. water, fruit or vegetable juices)
$531m
2.29
6
Chocolate and other food preparations containing cocoa
$463m
1.73
7
Fish, fresh, whole
$374m
2.89
8
Crustaceans
$400m
1.20
9
Meat & edible offal of poultry meat
$363m
1.10
10
Sauces mixed condiments & mixed seasonings
$222m
1.94
11
Tea
$113m
2.38
The ranking/prioritisation above did not lead to the exclusion of any products from the
final shortlist. It was conducted in order to drive the selection at the final stage of the
analysis, in combination with the demand factors in each market presented in the
following section.
106
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Section 6.5.2. Demand side considerations
In order to assess the opportunity in place for each country across products, a range of
parameters were taken into consideration. These parameters and the justification for using
them to identify the best opportunities are explained in the table below.
Table 6.5.2.1.
Parameters taken into consideration
Parameter
Reason for consideration
Domestic
market size,
value or
volume terms
(depending on
product), 2011
Indicates the size of the opportunity, although opportunities exist in small/niche markets as well, the
current engagement is tasked with identifying where Government resources are best spent in the short
to medium term. Therefore, a preference is given to sizeable domestic markets
Total imports
by country,
value terms,
2011
Indicates the size of the opportunity; even though the current engagement aims to remove barriers in
closed markets, focusing on countries where imports are already of a certain scale is preferable given
the medium-term horizon of the scope
Total product
imports from
the UK as % of
total product
imports, value
terms, 2011
This parameter investigates if the UK has been completely locked out of a market or has been able to
enter even if it currently has a relatively small market share. Therefore, the aim is to focus on markets
where the UK has been locked out of the market
Target
country's
worldwide agrifood RCA by
product, 2011
While an RCA below 1 does not demonstrate a weakness in domestic production, an RCA equal to or
above 1 indicates comparative advantage in exports, therefore, countries with comparative advantage
should preferably be avoided. However, countries with a comparative advantage can also be significant
importers (e.g. USA for beef, Mexico and Russia for chocolate, etc.)
NTMs applied
by the nation
by product
category, 20092012
The Government and industry objective is to unlock trade barriers, therefore, these parameters identify
the countries where tariffs are the highest and give an indication of the NTM incidence. Therefore, the
countries and product categories where tariffs are higher and there are more NTMs better fit the
project scope and should be prioritised. (please note that the NTM analysis at this stage of the
engagement does not reflect severity by each individual measure)
Tariffs applied
by the nation
by product
category on UK
imports, 20092012
Retailer
structure and
UK retailer
presence
Indicates the presence of well-developed distribution channels to reach a large part of the local
population. The presence of UK retailers could further facilitate the distribution penetration into these
markets for British products. Therefore, UK retailer presence is a bonus, but is not a key decisionmaking factor in the final shortlist
UK and other
EU nations'
exports' relative
market share as
a % of total
imports, 2011
Assesses whether the UK and/or other EU nations have been able to penetrate the market despite the
presence of strong NTMs/high tariffs. In cases where the UK has a low market share but other EU
nations have penetrated more effectively, then there may be other underlying reasons for UK's underpenetration beyond trade barriers. Therefore, the project should prioritise the countries and product
categories where other EU countries have the same low penetration as the UK, as this indicates that no
European country was able to access these markets
Tariffs imposed
by target
countries on
top exporting
nations
Assesses whether the target country imposes lower tariffs/no tariffs on the top exporter by product
category compared to the tariff rates that are applied to the UK. If the top exporter has lower tariffs
compared to the UK, this might justify UK's smaller market share/inability to penetrate the market and
by engaging in trade negotiations to bring tariffs to the lowest level , the Government can help increase
the appeal for British products
© 2013 Grant Thornton UK LLP. All rights reserved.
107
Section 6.5.3. Final product/country output
The final shortlisting process in Step 3 followed a qualitative approach, supported by a
comprehensive range of data (already presented). Although in Step 3 there is no rigid 'logic
tree' through which a country/product combination is assessed, the final product/country
combinations were shortlisted based on the following principles:

Examining the 56 remaining options both on a per country and per product basis;

Identifying and prioritising large domestic markets with sizeable imports among
the sample;

Confirming that the UK or other EU countries have not yet penetrated to a
satisfactory level the large markets presented in the previous section;

Assessing whether the UK imposed tariffs and/or NTMs are above the longlist
average for these same markets;

Identifying the tariffs these markets impose on their preferred exporter (in order
to assess whether the tariffs imposed on UK exporters place the latter at a
comparative disadvantage);

Taking into account qualitative assessments from desktop and primary research (e.g.
UK traders targeting or not targeting specific countries or regions as per the interviews
conducted, the existence of the 'Atlantic-Pacific trade' for certain products, historic
trade conflicts between the EU/UK and the target market, etc.);

Ensuring the existence of satisfactory distribution channels and/or UK retailers'
presence in the target market under consideration; and

Preferably targeting markets with low RCA for the product under consideration as it
may indicate lower production specialisation in the specific product.
Where a country/product combination met the above criteria better than the rest of the
options in the sample, it was proposed for the final shortlist. Table 6.5.3.1 illustrates
market intelligence information for the 56 products/countries combinations and highlights
in green the final list of the six products that were shortlisted (Please note that as per Table
6.5.2.1, further information was used to select the final products but, due to space
constraints, cannot be presented in this Word report). Red indicates areas which were
eliminated from the analysis in the previous steps of the analysis and therefore were no
longer under consideration during this step. As discussed already, the products highlighted
in red were not deemed attractive enough either because the market is not sizeable enough,
or because the UK has already penetrated the market effectively or because there are no
significant trade barriers in place.
Note that the 'Domestic market size' for meat and seafood products are expressed in
volume terms (i.e. '000s of tonnes) and in value terms for the rest of the products ($m).
NTMs were compiled using the 2012 European Market Access Database and the 2009
database from WTO (which is expected to be up-to-date given the worldwide economic
downturn and the protectionist stance that most of the nations have been following during
this period. In addition, NTMs can take a long period of time to be addressed).
108
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Table 6.5.3.1.
End of Step 3 – Selecting the final products by country
Product codes and labels in order of prioritisation
1. 1905
Countries
1. USA
2. China
3. Brazil
4. Mex ico
5. Russia
6. Japan
7. India
Market assessing parameters
2. 0204
3. 0201
4. 0401
5. 2202
Bread, biscuits,
Meat of sheep or goats Meat of bov ine
Milk and cream, not
w afers, cakes and
- fresh, chilled or
animals, fresh or
concentrated nor
pastries
frozen
chilled
sw eetened
Domestic market size, 2011 (in
Total imports by country , 2011
UK imports as % of total imports,
RCA
NTMs
Tariffs, 2011
Domestic market size, 2011 (in
Total imports by country , 2011
UK imports as % of total imports,
RCA
NTMs
Tariffs, 2010
Domestic market size, 2011 (in
Total imports by country , 2011
UK imports as % of total imports,
RCA
NTMs
Tariffs, 2010
Domestic market size, 2011 (in
Total imports by country , 2011
UK imports as % of total imports,
RCA
NTMs
Tariffs, 2009
Domestic market size, 2011 (in
Total imports by country , 2011
UK imports as % of total imports,
RCA
NTMs
Tariffs, 2012
Domestic market size, 2011 (in
Total imports by country , 2011
UK imports as % of total imports,
RCA
NTMs
Tariffs, 2009
Domestic market size, 2011 (in
Total imports by country , 2010
UK imports as % of total imports,
RCA
NTMs
Tariffs, 2009
© 2013 Grant Thornton UK LLP. All rights reserved.
59,705
3,156,986
1.66%
0.61
5
1.36%
20,780
256,846
2.35%
0.32
6
18.20%
34,005
51,308
1.59%
0.08
3
18.00%
20,445
203,199
0.24%
1.50
2
11.81%
13,481
360,118
1.13%
0.58
7
15.00%
4,711
15,160
4.23%
0.42
6
30.00%
3,917
275,591
0.00%
0.21
8
14.46%
142
33,869
0.00%
0.00
3
10.00%
128
43,723
0.00%
0.01
3
10.00%
1,471
178
0.00%
0.80
7
30.00%
7,859
1,420,459
0.00%
1.17
12
8.22%
6,579
9,051
0.00%
0.03
9
13.26%
7,152
117,774
0.00%
0.55
4
11.42%
1,605
904,057
0.00%
0.88
3
20.00%
1,303
188,779
0.00%
0.00
8
27.46%
868
1,454,363
0.00%
0.18
4
38.50%
716
0.07
7
30.00%
109
6. 1806
Non-alcoholic
bev erages (ex cl.
w ater, fruit or
v egetable juices)
21,958
60,489
1.31%
0.06
7
15.00%
9,176
9,458
0.00%
0.03
3
12.90%
4,175
29,542
0.00%
0.10
2
10.00%
4,690
42,291
1.51%
0.09
9
12.93%
7,368
160
5.00%
0.02
7
30.00%
14,008
62,589
0.59%
0.21
5
26.31%
30,185
82,456
0.00%
0.01
3
20.00%
21,336
144,005
0.03%
1.00
2
15.49%
4,663
117,208
0.89%
0.36
7
20.92%
7. 0302
8. 0306
9. 0207
Chocolate and other
food preparations
Fish, fresh, w hole
Meat & edible offal of
Crustaceans
poultry meat
containing cocoa
1,675
227,908
0.77%
0.19
6
8.79%
6,214
98,092
0.17%
0.10
3
19.70%
1,090
438,297
0.38%
1.59
2
27.84%
8,322
766,620
0.13%
1.75
7
18.60%
1,050
39,697
2.76%
0.05
6
30.00%
1,476
215,862
0.00%
0.01
3
10.00%
2,239
727,965
0.02%
0.00
7
10.00%
2,945
667,984
0.86%
1.68
3
4.20%
2,622
38,253
0.00%
0.16
7
30.00%
10. 2103
490
5,717,276
0.00%
0.43
8
0.38%
5,790
825,099
1.36%
1.62
7
7.47%
111
1,235
0.00%
0.08
3
10.00%
90
50,612
0.00%
1.25
2
1.57%
712
3,107,005
0.01%
0.25
4
1.76%
516
5,537
9.45%
4.23
7
30.00%
11. 0902
Sauces mix ed
condiments & mix ed
Tea
seasonings
10,110
173,891
0.00%
1.75
11
5.74%
16,321
872,299
0.00%
0.47
9
14.90%
8,213
7,197
0.00%
5.07
3
10.00%
2,571
976,615
0.00%
0.04
2
205.69%
2,883
592,415
0.00%
0.07
8
55.29%
1,267
1,713,758
0.00%
0.08
4
7.72%
2,398
0.00%
0.01
8
74.93%
8,860
101,499
0.72%
1.54
6
19.83%
5,003
42,545
1.07%
0.03
3
16.99%
3,508
187,706
0.01%
1.32
2
0.00%
4,586
216,512
5.66%
0.87
7
42.56%
8,004
59,150
2.95%
3.47
7
15.00%
3,762
625,188
0.31%
0.96
7
7.26%
4,890
207,308
1.12%
2.62
2
10.14%
1,628
48,941
1.57%
8.52
9
100.00%
Table 6.5.3.2 below illustrates the reasoning for selecting the final six products and a high
level explanation of why some of the other options were disregarded. Under the
'Justification for not shortlisting…. products', commentary only on the next best
alternatives that did not make it to the shortlist has been included, rather than on the
whole set of the remaining 50 options.
Table 6.5.3.2.
Reasons for shortlisting/not shortlisting a product category in
a particular country
Justification for not shortlisting countries and/or
products
Country
Products shortlisted and justification
USA
0306 – crustaceans: The USA import value for
crustaceans is the largest out of all the countries and
products in the shortlist. The UK has almost no
share in the market even though tariffs are already
low for the UK. In addition, shrimps, prawns and
crabs account for c.80% of US crustaceans' imports,
which the UK can supply.
Even though beef presented a good opportunity for
USA, there is a long history of conflicts in the trade
relations between the EU and US for beef meat and
discussions about the removal of BSE barriers are
already being handled at the EU level but are likely to
be protracted.
The US 'breads and biscuits' market is very valuable
both in absolute domestic market terms and in
import terms. However, NTMs and tariffs are low,
UK already has a 1.7% import market share while
other EU nations, such as Italy and Germany,
already each holding c.4% share of the total imports.
Therefore, the category appears to present
opportunities for UK businesses but should not be a
focus for this engagement which focuses on market
access issues
China
0204 –meat of sheep or goats-fresh, chilled or
frozen: China has the world's largest domestic
market for sheep & goat meat and the 2 nd highest
import value among the target countries. There is
currently low UK market penetration of the product
category despite the UK being the world's third
largest exporter of the product. The tariff levels
imposed on the UK are among the highest within
the target countries (i.e. 15%) and larger than the
tariffs imposed on New Zealand, who is China's
largest sheep/lamb supplier (8% vs. 15% for the
UK)
0207 – meat and edible offal of poultry meat:
Large domestic consumption and imports among
target countries. Compared to Japan whose imports
are double in value terms, China offers growth
opportunities as meat consumption per capita is
forecast to increase given socio-economic
conditions. In addition, the consumption of offal is
higher in China which offers opportunities for the
UK to sell poultry parts which would otherwise be
discarded. However, please note that Brazil is the
country's top poultry supplier with 68% market
share (as % of total imports) and is subject to the
same tariff rates as the UK (i.e. 15%) and therefore
even if the UK Government is successful in
stopping the meat ban, the UK will have strong
competition from Brazil
In the case of 'breads and biscuits', UK producers
have been successful in entering the market at a
current imports share of 2.3% (one of the highest
amongst the target countries) and market access does
not appear to be necessarily a barrier for further
penetration.
Although in the case of China 'milk and cream' is the
most sizeable amongst the target countries, it is one
of the lowest value product categories (across
products and countries) in terms of imports and
therefore it was not shortlisted. However, contrary to
the belief that the distance involved may restrain
European nations from shipping non-powdered
dairy products to countries such as China, major
European dairy producers (e.g. France and Germany)
have penetrated effectively China (with imports share
of 19% and 15% respectively)
Despite Brazil having sizeable domestic markets
across many products, they consistently import much
less than the other countries in this comparison
(except for India). Brazil's protectionist policy has
persevered over the past few years and has been
confirmed by the media and the primary research.
Given the short/medium term scope of the
engagement, it would be very challenging to target a
closed market such as Brazil.
Brazil
Mexico
1806 – chocolate and other food preparations
containing cocoa: USA and Canada dominate the
imports market with 84% of total imports, however
the tariff imposed on them is 0%. Mexico is the
second largest target country in terms of value of
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Beef also appears to present significant targeting
opportunities. The European beef imports are
subject to partial ban imposed by Mexican authorities
and USA and Canada account for almost 100% of
the imports.
110
Country
Justification for not shortlisting countries and/or
products
Products shortlisted and justification
chocolate imports (after Russia) and the UK as well
as the whole EU have a low market penetration and
are subject to much higher tariffs. However, Mexico
has an RCA of 1.59 which indicates it is active in
exporting chocolate products to the rest of the
world.
1905 – Breads, biscuits, wafers, cakes and
pastries: The Mexican breads and biscuits market
presents a sizeable opportunity in terms of the
domestic retail market size but also significant
imports of $200m. At the same time, the UK has a
very small share of the market, whilst the tariffs of
12% put UK and other EU exporters at a
disadvantage when compared with USA and Canada
who export with 0% tariffs. However, it is worth
nothing that EU countries already have a 15%
market share, with Italy having 9% of the total
imports.
Russia
Japan
India
111
The Mexican poultry market also presents a very
good opportunity with the second highest level of
imports amongst the target countries and very high
tariffs imposed on EU products (206%) despite the
EU-Mexico FTA. At the same time, Mexico does not
export much chicken (as indicated by the RCA equal
to 0.04), but UK manufacturers may find it
challenging to break the US monopoly (i.e. 94%
market share)
The market for 'breads and biscuits', 'chocolates'
and 'fish' appear as good targets due to the large
domestic markets, strong imports and high
NTMs. Despite the volatile political climate in
Russia and strained relationships with the EU,
EU countries account for significant share of the
Russian imports (e.g. Germany, Italy and
Belgium have 38% share for breads and biscuits,
while Poland, Germany and Italy hold 31% for
chocolate), indicating that these markets have
identified ways of surpassing political barriers
and penetrating the Russian market. However,
the primary research indicates that UK agri-food
businesses are targeting Russia and see growth
opportunities, but acknowledge that there are
bureaucratic complexities in entering the market
0201- meat of bovine animals, fresh or
chilled: Despite Japan's beef market being the
smallest amongst the target countries, the
value of its beef imports is the largest. Due to
the BSE legacy, the UK has not penetrated
the Japanese beef market which also imposes
particularly high tariffs on imports (it also
applies 38.5% tariff on Australian imports
who is the country's largest beef supplier).
However, the full ban that Japan currently
imposes on EU meat has been regularly raised
in EU-Japan meetings and may therefore not
be resolved just through intervention by the
UK Government. The existence of the
'Atlantic-Pacific trade' also needs to be
accounted for and the extent that the UK
could penetrate the Pacific trade for beef
needs to be validated
Even though the imports are sizeable across
the remaining targeted products, the levels of
NTMs and tariffs are rather low, therefore
market access is not deemed to be a major
barrier to enter these markets
No products were selected for India because the
domestic market size appears to be much smaller
in absolute value terms compared to the other
countries and the import levels are too low.
India remains a very closed market especially for
meat and seafood products. Also, the retail
market is very fragmented and the UK retailers
have still not entered the market.
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Summarised from the above table, the final list of six product/country combinations that
were taken forward to the last phase of this project (in order to evaluate the potential
opportunity behind removing trade barriers associated with them) are:
1
'0204' sheep & goat meat in China;
2
'0207' poultry meat & offal in China;
3
'0306' crustaceans in the US;
4
'1905' breads, biscuits, wafers, cakes and pastries in Mexico;
5
'1806' chocolate in Mexico; and
6
'0201' beef in Japan.
Overall, China is the only BRIC nation that was selected for investigation in Chapter 7
(although Mexico, another large and fast growing emerging market, is included in the final
selection). This was because Brazil and India appear to have relatively closed markets
(lower import volume/value) and given the project's medium-term horizon (i.e. 3-5 years),
it was deemed unrealistic that this trade pattern could be changed during this time frame.
In addition, India's market is smaller in value terms for some products (especially in per
capita terms) and modern food distribution is not adequately developed domestically, all of
which would inhibit the penetration of UK products. In terms of Russia, it is already one
of the EU's main trade partners and many EU countries have significant shares in Russia's
imports already.
The final selection consisted of the six options that appeared to present the greatest
potential opportunity based on the evidence, but the options were also limited to six due to
project time constraints and the need for the Government to prioritise and focus its
resources to ensure the highest likelihood of success rather than start negotiations across
all 56 options. However, many of the remaining 50 product/country combinations (and
indeed the initial shortlists of 78/118 product/country combinations) may offer interesting
opportunities for UK agri-food manufacturers as evidenced by the comprehensive analysis
undertaken up to this point.
The final selection of six products/country shortlisted includes only two processed food
products. This was mainly because other EU countries appear to have successfully
penetrated target markets for the shortlisted processed products in Step 3 above. This
indicates the trade barriers (tariff and non-tariff) may not be so severe and UK's lower
penetration may be related to commercial issues rather than trade barriers. The
quantitative analysis on the most significant opportunities guided the selection of the final
six selections.
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112
Chapter 7. Forecasting the export opportunity for
the selected UK products
Section 7.1. Introduction and scope
This chapter presents the methodology, data collected and outputs in terms of forecasting
the potential opportunity for the six product/countries identified at the end of Chapter 6
through the use of econometrics tools. This chapter is structured as follows:

Section 7.2- Literature review: provides an overview of different ways in which import
demand equations have been used for similar purposes by international organisations
and academics and the key parameters they accounted for;

Section 7.3- Methodology followed and common themes in the analysis of all products:
presents the five-step process and common themes that were replicated in the analysis
of all products and ways in which they were dealt with; and

Section 7.4- Regression analysis and forecasting outputs: presents the values estimated
for the potential opportunity in place for each of the six products under three different
scenarios. For details on the steps followed for the regression analysis and forecasting
for each of the six products, please refer to the Appendix.
At this stage of the analysis, Dr Paula Ramada, a Senior Partner at London Economics,
provided valuable assistance with setting an appropriate methodology around data
processing, and with running, testing and selecting the most appropriate regression in
order to forecast the potential opportunity for UK exports. She was involved at every step
of the analysis undertaken and provided input as required.
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Section 7.2. Literature review
The objective of this chapter was to calculate the economic value associated with the
removal of trade barriers for the UK agri-food products under investigation. The aim was
to develop a methodology based on established economic frameworks. For a list of the
bibliography consulted please refer to Bibliography section of this report. The first step
entailed conducting a literature review on import demand equations in order to study the
body of work available from academia and international organisations and adapt the
existing frameworks to the Defra project.
One of the options considered was to use an adjusted version of the gravity model given
its versatility in international trade analysis. According to Ferrantino60, the gravity model is
regularly used in international trade analysis based on the hypothesis that the size of
bilateral trade flows between any two countries can be approximated by analogy with the
Newtonian theory of gravitation. In its general formulation, the gravity equation has the
following multiplicative form:
Xij = G × Si × Mj × φij
where Xij is the monetary value of exports from i to j, Mj denotes all importer-specific
factors that make up the total importer‟s demand (such as the importing country‟s GDP)
and Si comprises exporter-specific factors (such as the exporter‟s GDP) that represent the
total amount exporters are willing to supply. G is a variable that does not depend on i or j
such as the level of world liberalisation. Finally, φij represents the ease of exporter i to
access of market j (that is, the inverse of bilateral trade costs).
However, Defra's scope of work does not involve bilateral trade flow, but rather unilateral
trade (e.g. how much of a certain product can the UK export to the target countries if the
associated trade barriers were removed). Therefore, based on the application examples
seen in the literature review and input from the project team economist, the gravity model
was not deemed the best fit/most appropriate to use in the current context. Therefore, a
decision was made to approach the question through an import demand function in order
to forecast the UK's export potential to the target nations.
There is no generic form for the import demand function and the different academics who
have publicised studies in this field have developed their own functional form tailored to
the needs of their study. According to Abdelhak Senhadji61, the traditional import demand
function is specified as a log-linear function of the relative price of imports and real
income of the importing country. Because of data constraints associated with other
quantification approaches and the empirical success of the traditional import demand
specification, the import demand equation has dominated the empirical literature for more
than a quarter century.
In a 1992 study, Warner62 uses import demand equations (in a log-linear form) to explain
the behaviour of US import prices and quantities with a focus on historic exchange rate
movements. The author mentions that the consensus view on import demand models,
echoed by Krugman and Baldwin63 was that they tracked imports fairly successfully. "With
Ferrantino M. (2006), “Quantifying the Trade and Economic Effects of Non-Tariff Measures”, OECD
Trade Policy Working Papers, No. 28
60
Abdelhak Senhadji (1997), “Time-Series Estimation of Structural Import Demand Equations: A CrossCountry Analysis”, IMF
61
Warner, A. M. (1992), “Import Demand and Supply with Relatively Few Theoretical and Empirical Puzzles',
Federal Reserve Board”
62
Krugman, P.R and Baldwin R.E. (1987), “The Persistence of the US Trade Deficit”, Brooking Papers on
Economic Activity 1:1987
63
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114
plenty of variation in the data even the simplest estimation techniques yield plausible results, and
the simplest equations have by and large successfully tracked the impact of the exchange rates on
the trade balance."64
In Senhadji's study already mentioned, the author used a disaggregated figure of GDP to
reflect income levels and the ratio between the import deflator and the GDP deflator as an
indicator of relative price of imports.
Moreover, as per Gujarati 65, an attractive feature of the log-linear model, which has made
it popular in applied work (and amongst import-demand equations), is that the
independent variable's coefficient measures the elasticity of the dependent variable with
respect to the specific independent variable. Gujarati continues by stating that the reason
why the log-linear function is used widely is that "economists, businesspeople, and
governments are often interested in finding out the rate of growth of certain economic
variables, such as population, GNP, money supply, employment, productivity, and
trade deficit."
Based on the insights from literature, the expert advice from the project economist, data
availability and regression outputs, a tailored import demand function appropriate to the
specifics of the Defra project has been developed in a log-linear form. As such, this stage
accounted for, collected data and tested a variety of parameters that could explain the
behaviour of domestic demand in the markets targeted by UK agri-food products.
The parameters collected as inputs for the import demand equation are explained for each
of the products analysed. In broad terms, the parameters investigated were GDP and other
disaggregated components of GDP, such as total private consumption, in order to capture
income levels and a number of ratios that captured the relative price of imports were
calculated (e.g. ratio of import prices to the domestic retail prices, ratio of the
competition's import prices to the domestic retail prices, etc.). In addition a number of
other variables were included in the equation to capture historic trade barriers and trade
relationships with the target nation (e.g. tariffs, non-tariff measures, trade index, etc.).
By adapting the import demand equation, it was assumed that the supply of UK products
is perfectly elastic and therefore, has been excluded from the analysis. More precisely, the
assumption made was that the UK production capacity can increase to satisfy the demand
coming from new markets where barriers have been removed. Therefore, any value of
exports estimated for this project represents additional exports compared to historic
figures, generated by increasing production, rather than diverting current exports.
Nevertheless, assumptions were made around the UK production capacity to ensure that
the increase in production needed would be in line with past behaviour and if additional
production capacity would be needed to satisfy the surplus demand.
In conclusion, the value of UK exports to a target market after the removal of trade
barriers was estimated through an import demand equation in a log-linear format.
The above theoretical framework will be used to estimate the economic value of UK
exports for all of the six shortlisted product/country combinations. In the case of chicken
exports to China the theoretical framework and the analytical steps are explained in more
detail, as it is the first product analysed. For the remaining products, the explanation for
the identical analytical steps will be concise and only where the data requires a deviation
from the framework, those relevant analytical steps will be explained in more detail.
65
Gujarati, D.N. and Porter D.C. (2004), “Basic Econometrics”, The McGraw−Hill Companies
115
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Section 7.3. Methodology followed and common themes in
the analysis of all products
Section 7.3.1. Stepped approach
In each case, for the six product/countries investigated in this chapter, a stepped approach
was taken to estimate the potential opportunity presented by the reduction or complete
removal of trade barriers for the respective UK exports. This approach is explained in
detail below.

Step 1: (Opportunity and benchmark countries selection) following the identification
of the 4-code HS level at the end of Chapter 6, it was important to identify more
specifically the opportunity for UK exports by investigating the imports of the target
country as well as UK's exports at the 6-code HS level. Having completed this, a
number of comparison countries, who are already exporting the product identified to
the target market, were selected and analysed in order to enrich the sample data, build
greater power in the regression analysis and obtain a stronger understanding of
exports' behaviour;

Step 2: (Data collection) an extensive data collection process was undertaken to collect
data across a number of variables that were deemed relevant for the purposes of the
regression analysis. Many of the variables for which data was collected were not finally
included in the final regression selected, but their role and explanatory power was
tested anyway. The four main areas across which data was selected are: a) trade
statistics, b) market size/income, c) pricing and d) trade barriers;

Step 3: (Data processing) the data collected was in many cases processed in order to
create new variables (e.g. price ratios that reflect the relevant prices at which a country
exports its products compared to the target market's domestic prices), to build into the
model qualitative parameters (e.g. dummy variables), to remove observations for which
data was not deemed reliable enough or when other issues were identified while
running the regression. The relevant sections discuss the data processing undertaken
and the variables across which it took place;

Step 4: (Regression analysis and testing) a number of regressions were tested in order
to identify the most appropriate variables and the most appropriate format in which to
build them into the import demand equation. The functional form of all equations
used was in a log-linear format and many tests were run to ensure the final regression
selected was appropriate to be used as a forecasting tool of UK exports to the target
market; and

Step 5: (Economic value forecasting) once the most appropriate import demand
equation had been identified, the value of the explanatory variables were forecast to a
medium-term horizon (as per the scope of the engagement agreed with Defra at
project start) and by accounting for a 'Low', 'Base' and 'High' scenario in each case.
The forecasts were in some cases readily available in the public domain, otherwise they
had to be estimated either by observing the time trend or by carrying out additional
regression analyses and thereby collecting data and adding to the analysis new
parameters. Furthermore, a sensitivity analysis was carried out to account for the UK
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116
Sterling's exchange rate to the US Dollar given that the analysis was carried out in
Dollar terms. A number of key considerations that need to be accounted for in terms
of forecasting the value of the opportunity are provided at the end of the relevant
section for each product.
Unlike the work in Chapters 2 and 6, the analysis in Chapter 7 is carried out at the 6-code
HS level in order to identify and evaluate the specific opportunity in place for UK
exporters.
Section 7.3.2. Regression analysis methodology
Before running the regression analysis to obtain the most appropriate import demand
equation, a series of generic econometric tests, namely integration (or unit root) and
cointegration tests were undertaken.
In time series regressions, variables may have unit roots, which implies that they are not
stationary. This means that these variables grow over time while others remain stationary
(for example, price levels will grow over time whilst inflation, which reflects the first
difference in price levels, is more likely to be stationary). When variables with unit roots are
included in a regression, there is a risk that the regression results will output statistically
significant coefficients, but that these coefficients may be spurious, so that the regressed
coefficients may not truly reflect an underlying relationship between the variables in
question. Consequently, this could lead to wrongly estimating relationships among
variables of interest and make forecasts unreliable. In order to try and avoid this problem
the method commonly followed (in time series regression) is:

First test individual variables for unit roots. If there are no unit roots, it is possible to
progress to usual regression techniques;

If there are unit roots, it is necessary to investigate whether the variables are cointegrated. Two variables are co-integrated if there is a stable relationship among them
so that a linear combination of the two variables is stationary; and

If a co-integrating relationship is found, then there are regression methods that can be
used to estimate the parameters of interest that take into account both the unit root
problem and the co-integrating relationship. These methods are known as vector error
correction (VEC) methods.
In the case of the six product/countries investigated for the purpose of this project, a large
number of unit root tests were run producing mixed results. Given the relatively short
length of the time series and some unexpected values for the dependent variable in some
of the observations, the unit root tests were deemed to have little power. However, low
power is considered to be a common issue for unit root tests in panel regression. Given
that the null hypothesis of these tests is that the panel has a unit root, low power implies
that the outputs of these tests are likely to be biased towards finding unit roots when they
may not in fact be present.
Given the mixed results on the unit root tests the decision was made to further investigate
to test for cointegration between the dependent variable and the regressors. These tests
were similarly inconclusive with mixed results, but indicated that the dependent variable
may be co-integrated with at least one of the regressors.
Accordingly a number of regressions were run using regression methods that take into
account the possible cointegration issue and others that use more common panel
regression methods. The regressions were run using eViews and Stata for panel data
consisting of the UK and the comparison countries in each case. In some cases where UK
data was deemed to be unreliable (when export values are too small, volumes reported may
be unreliable, which does not to price effectively the unit exports) or where limited
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observations existed for historic UK exports, UK observations were completely removed
from the regression. Given the import-demand equations used are trying to estimate the
target country's demand for imports, they are always accounting for the importing
country's perspective, rather than the exporter's. As such, removing the UK observations
will not affect significantly the forecasts estimated for each country, which depend on the
value of the independent variables captured in each regression.
Further to the analysis presented in the following sections, the functional form of the
equation was log linear, whilst numerous iterations were run to identify the most suitable
import demand equation, by utilising:

Stepwise least squares, generalised least squares and ordinary least squares
(OLS) regressions;

Estimation methods applicable to panel data that attempt to correct for possible issues
of non-stationarity and time dependence, such as Dynamic Ordinary Least Squares
(DOLS) for Cointegrated Panel Data, generalised method of moments (GMM)
estimator, etc.;

With and without fixed/random effects for each country; and

Using different datasets (e.g. including and excluding the sanitary ban observations,
filling in estimates for the sanitary ban periods, etc.).
The import demand equations that resulted in an appropriate functional form were
shortlisted, namely:

Strong R-squared;

Statistical significance across the coefficients (as measured by the t-statistic value at a
95% confidence interval); and

Reasonable coefficient values (i.e. the sign of the coefficient reflected the
team's expectations).
In addition, while choosing between different variables, the focus was on variables where
coefficients were somewhat stable and did not appear to vary significantly across different
regressions when regressed with a different mix of variables.
As a next step, the equation(s) chosen had to pass the serial correlation, normality and
heteroskedasticity tests. Using Stata and eViews to run these tests, the final selected
equation fulfilled all these requirements and proved sufficiently reliable to be used in the
final step of estimating the potential for UK exports assuming certain trade barriers were
reduced or completely removed.
Overall, despite certain similarities amongst the six opportunities that are being evaluated
in this Chapter (they all concern the food and drink sector and in some cases the same
target markets), the six regression equations selected to explain the behaviour of imports in
each case are different. The difference might lie in the type of regression utilised or in the
variables accounted for (e.g. different price parameters accounted for, removing certain
parameter or replacing it with another, etc). For example, it may seem reasonable that the
imports demand equation in the case of chocolate for Mexico and bread & biscuits for
Mexico should be described by a similar relationship. However, the detailed relationships
selected are actually different. The main reason behind it is the limited number of
observations that was available in each case and, which, in a few cases, was not deemed
reliable enough and could, therefore, not be utilised in the analysis. As such, the team
investigated a number of relationships and ended up selecting the strongest and most
significant one for each opportunity. However, a number of variables (e.g. share in the
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118
global trade of the specific product, share of total trade with the selected market, private
consumption, price terms with tariffs built-in) appear to be significant across most or all of
the relationships and were repeatedly used to estimate the forecasts for UK exports, which
shows a certain consistency across the equations.
119
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Section 7.4. Regression analysis and forecasting outputs
This section presents the outputs forecasted for the potential opportunity in place for each
of the six products selected at the end of Chapter 6. These results follow an extensive
process undertaken that consisted of data collection and processing, regression analysis and
forecasting under three different scenarios. For more details on each step of the process,
please refer to the Appendix.
For each of the products, the data entries where in $ terms, and therefore all forecast
values were converted to GBP terms based on EIU foreign exchange forecasts for 2016
($1.61 per £). Additionally, a separate sensitivity analysis was performed on the $/£
exchange rate, as this could have a significant effect on the forecasted value of UK exports.
A conservative approach of 10% move in the exchange rate was accounted for when
compared with EIU's 5% maximum movement over a single year between 2013-2016.
Section 7.4.1. Chicken meat exports to China
Based on a number of assumptions made for the parameters (i.e. the independent
variables) of the import-demand equation selected at the regression analysis stage, forecast
values for the UK chicken exports to China in 2016 were estimated. The main assumption
made was the removal of the sanitary ban barrier within the next 2-3 years. A small tariff
rate reduction was also accounted for in line with historic progress in tariff rates reductions
(however, tariffs were still assumed to be equal across all competing countries). The
forecast value assumes that all other things not accounted for by the regression are held
constant to 2016.
Table 7.4.1.1 presents the results of the economic value estimations based on various
scenarios and sensitivity analyses. For details on the analysis undertaken and the
assumptions made for each scenario, please refer to Appendix A.
Table 7.4.1.1.
Potential opportunity for UK 020714 (chicken meat) exports
to China in 2016
Base
Low
High
40,320
19,445
51,896
Upper range (£'000s)
44,351
21,389
57,085
Lower range (£'000s)
36,288
17,500
46,706
Value forecast (£'000s)
Sensitivity analysis on £/$ exchange rate (+/-10%)
The base case scenario forecast provided above (£40m) reflects the export of 41,500
tonnes of 020714 chicken meat for 2016 under the UK export prices calculated for 2016.
This compares to 610 tonnes that China stated it imported from the UK in 2011 (even
though it has formally placed a sanitary ban on chicken meat products with UK origins).
Under the forecasting scenario it is assumed that the UK poultry industry would be able to
respond relatively quickly to this new demand and generate this supply over a relatively
small period of time of 1-2 years (assuming negotiations with China to remove the sanitary
bans take 2-3 years). Based on empirical evidence of historic UK 020714 exports globally
(during 1996-2011), the maximum amount by which the UK was ever able to increase its
exports over one year was 35,000 tonnes. However, over the period of two years (and
more specifically 2009-2011), the UK increased its 020714 exports by 62,000 tonnes. Solely
based on this historic behaviour and without assessing the current and forecast production
capacity for UK's chicken producers, it seems plausible that the UK will be able to respond
to the new demand estimated for China over a period of two years (and assuming there is
© 2013 Grant Thornton UK LLP. All rights reserved.
120
not significant additional demand generated by other regions elsewhere in the world during
the same time period).
Also, it is worth noting that, as per the import-demand equation selected to forecast the
opportunity, the scenarios above are closely tied to the following assumptions, which if
disproved could materially impact the exports performance:

The UK will maintain its competitive prices of poultry exports by 2016 in line with EU
poultry production costs. Any significant deviations from the forecast rate may
position the UK at a disadvantage compared to its peers which could severely impact
the UK's sales to China;

China is currently imposing heavy duties on US poultry imports. If the duties are
sustained, this could have a positive impact on UK's exports, however, if these duties
do not prevail, they could help the US recapture its lost share and adversely affect
UK's prospects; and

The UK will continue to increase its trading ties with China in line with the past six
years, which in turn will encourage Chinese and UK businesses to establish and
develop trade relations on chicken products. In contrast, if the UK does not
increase the trade exchanges with China, the value of chicken exports may be
impacted adversely.
Section 7.4.2. Sheep meat exports to China
Forecast values for the UK sheep meat exports to China in 2016 were estimated, primarily
assuming the removal of the sanitary ban barrier within the next 2-3 years. The forecast
value assumes that all other things not accounted for by the regression are held constant
to 2016.
Table 7.4.2.1 presents the results of the economic value estimations based on various
scenarios and sensitivity analyses. For details on the analysis undertaken and the
assumptions made for each scenario, please refer to Appendix B.
Table 7.4.2.1.
Potential opportunity for UK 020442 (sheep meat) exports to
China in 2016
Base
Low
High
5,490
2,349
7,267
Upper range (£'000s)
6,039
2,584
7,994
Lower range (£'000s)
4,941
2,114
6,540
Value forecast (£'000s)
Sensitivity analysis on £/$ exchange rate (+/-10%)
The base case scenario forecast provided above (£5.5m) reflects the export of 3,000 tonnes
of 020442 sheep meat for 2016 under the UK export prices estimated for 2016. This
compares to zero tonnes that China imported in 2011 from the UK given the sanitary ban
it has put in place on sheep meat products with UK origin. In this scenario it is assumed
that the UK sheep meat industry would be able to respond relatively quickly to this new
demand and generate this supply over a relatively small period of time of 1-2 years
(assuming negotiations with China to remove the sanitary bans take 2-3 years). Based on
empirical evidence of historic UK 020442 exports globally (during 1995-2011), the
maximum amount by which the UK was ever able to increase its exports over one year was
1,700 tonnes. However, over the period of two years (and more specifically 2009-2011),
the UK increased its 020442 exports by 2,800 tonnes. If the exports of 020422 (i.e. 'Sheep
cuts, bone in, fresh or chilled' versus frozen investigated in the case of China) are
accounted for, then the largest 2-year volume increase in the exports of 'bone-in sheep
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© 2013 Grant Thornton UK LLP. All rights reserved.
cuts' was registered over 2008-2010 with an increase of 4,200 tonnes. Solely based on this
historic behaviour and without assessing the production capacity for UK's sheep meat
producers, it seems plausible that the UK will be able to respond to the new demand
estimated for China over a period of two years (and assuming there is not significant
additional demand generated by other regions elsewhere in the world during the same
time period).
Also, it is worth noting that , as per the import-demand equation selected to forecast the
opportunity, the scenarios above are closely tied to the following assumptions that if
disproved could materially impact the exports performance:

The UK will maintain its competitive prices of sheep meat exports by 2016 in line with
EU sheep meat production costs. Any significant deviations from the forecast rate may
position the UK at a disadvantage compared to its peers which could severely impact
the UK's sales to China;

China has not reduced its tariffs on 020442 imports since 2004 (except for New
Zealand with whom China recently signed an FTA). The base case scenario assumes
that the tariffs will stay at the current levels for UK and the rest of the competing
countries. However, if China lowers its tariffs (overall, tariffs have been significantly
reduced from 45% in 1995 to 12% in 2004), then the UK's position could be improved
and could potentially capture some of New Zealand's share who is the leading sheep
meat exporter to China;

The UK will continue to increase its trading ties with China in line with the past 6
years, which in turn will encourage Chinese and UK businesses to establish and
develop trade relations on sheep meat products. In contrast, if the UK does not
increase the trade exchanges with China, the value of sheep meat exports may be
impacted adversely; and

The UK's share of world sheep meat exports (020442) will decline from the 2011
levels. Even though UK's world share has been increasing since 2008, the base
scenario accounts for the average level between 2007-2011 to be conservative since
UK's 2011 share reached almost historic high levels. However, if UK were to continue
increasing its worldwide share, that could have a positive impact on its exports
to China.
Section 7.4.3. Crustaceans exports to USA
A forecast value for the UK crustaceans exports to USA in 2016 was estimated. The
forecast value assumes that all other things not accounted for by the regression are held
constant to 2016.
Table 7.4.3.1 presents the results of the economic value estimations based on various
scenarios and sensitivity analyses. For details on the analysis undertaken and the
assumptions made for each scenario, please refer to Appendix C.
Table 7.4.3.1.
Potential opportunity for UK 030613 (crustaceans) exports to
USA in 2016
Base
Low
High
10,811
9,704
22,348
Upper range (£'000s)
11,893
10,675
24,583
Lower range (£'000s)
9,731
8.734
20,113
Value forecast (£'000s)
Sensitivity analysis on £/$ exchange rate (+/-10%)
© 2013 Grant Thornton UK LLP. All rights reserved.
122
The base case scenario forecast provided above (£10.8m) reflects the export of 2,560
tonnes of 030613 shrimps and prawns for 2016 under the UK export prices estimated for
2016. This volume of exports compares with c.1 tonne that USA stated it imported from
the UK in 2011. UK's export price in 2016 was estimated by running a linear regression
between UK's price of 030613 exports to the world and the EU producer price for fish,
the historics and forecasts for which have been provided by FAO/OECD. As such, UK's
price for 030613 was forecast at $6.79/kg, which based on the estimates made (and
presented in Appendix C) is lower than competition's. However, price alone may not be
sufficient to compete with the larger and more established crustaceans exporting nations.
Historically, during a few years, the UK had similar or lower prices than some of the
competition, but still failed to penetrate the US market effectively. As such, industry
and/or Government action may be needed to help UK exports grow in the US market.
This forecast assumed that the UK crustaceans industry would be able to respond relatively
quickly to this new demand and generate the supply over a relatively short period of time
of up to two years (assuming UK producers and exporters need time to penetrate more
effectively the complex US market, which, as per the interviews conducted, includes a
network of retailers, wholesalers and distributers as well as brokers). Based on empirical
evidence of historic UK 030613 exports globally (during 1991-2011), the maximum
amount by which the UK was ever able to increase its exports over one year was 3,000
tonnes in 2001, which is greater than the projected increase in demand from USA. Solely
based on this historic behaviour and without assessing the production capacity for UK's
crustaceans producers at present, it seems plausible that the UK may be able to respond to
the new demand estimated for USA over a period of two years (and assuming there is not
significant additional demand generated by other regions elsewhere in the world during the
same time period).
As per the import-demand equation selected to forecast the opportunity, the scenarios
above are closely tied to the following assumptions that if disproved could materially
impact the exports' performance:

The import-demand equation used for crustaceans does not account for UK's price of
shrimps and prawns to USA (it accounts for the competition's average price and USA's
producers' price) and therefore movements in the UK's price should not change the
results above from a theoretical point of view. However, it is worth noting that there is
a large difference in the projections for UK's 2016 prices and the competition's ($6.79
per kg for the UK versus $9.29 per kg for the competition). The main reason is that
both of the prices were estimated using linear regressions with EU's fish producer
prices (in the case of UK prices forecast) and world fish prices (for the competition's
prices who account for the controlling share of the world crustaceans trade)
respectively. As per FAO/OECD, EU producer prices will go down whilst world fish
price will move upwards by 2016. If the UK's crustaceans price actually reach the levels
estimated compared to the competition, it would greatly facilitate UK trade. Otherwise,
from a theoretical perspective, the UK should still be able to reach the value of trade
projected in the previous table, but the volume of trade would be smaller because of
the higher unit values of crustaceans. However, as discussed above, industry action and
Government assistance might help with penetrating the US market;

As stated, the forecasts for the UK's 2016 share of world shrimps and prawns trade
made the conservative assumption that the UK's loss of share will continue at the pace
experienced over the past five years (even though the 2011 values are at historic low
levels). This could happen, but at the same time it is possible the decline may slow
down or the share of world trade may rebound and allow the industry to grow once
again on a global scale; and
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
The UK will not further its trading ties with USA even though it has been doing so
since 2001, with the exception of 2011, when there was a slight decline compared to
2010. This is a conservative assumption that if untrue could further boost UK's
crustaceans exports.
Section 7.4.4. Chocolate exports to Mexico
Forecast values for the UK chocolate exports to Mexico in 2016 were estimated, assuming
the reduction or complete elimination of tariffs within the next 2-3 years. The forecast
value assumes that all other things not accounted for by the regression are held constant
to 2016.
Table 7.4.4.1 presents the results of the economic value estimations based on various
scenarios and sensitivity analyses. For details on the analysis undertaken and the
assumptions made for each scenario, please refer to Appendix D.
Table 7.4.4.1.
Potential opportunity for UK 180690 (chocolate) exports to
Mexico in 2016
Base
Low
High
9,579
5,171
14,307
Upper range (£'000s)
10,537
5,688
15,738
Lower range (£'000s)
8,621
4,654
12,877
Value forecast (£'000s)
Sensitivity analysis on £/$ exchange rate (+/-10%)
The base case scenario forecast (£9.6m) reflects the export of 3,000 tonnes of 180690
chocolate for 2016 under the UK export prices estimated for 2016. This compares to 22
tonnes that Mexico reported that it imported from the UK in 2011. It is assumed that the
UK chocolate industry would be able to respond relatively quickly to this new demand and
generate this supply over a relatively small period of time of 1-2 years (assuming
negotiations with Mexico to reduce the tariffs imposed take 2-3 years). Based on empirical
evidence of historic UK 180690 exports globally (during 2000-2011), the maximum
amount by which the UK was ever able to increase its exports over one year was 8,000
tonnes in 2010. Solely based on this historic behaviour and without assessing the
production capacity for UK's chocolate producers, it seems plausible that the UK will be
able to respond to the new demand estimated for Mexico over a period of one to two years
(and assuming there is not significant additional demand generated by other regions
elsewhere in the world during the same time period).
Also, it is worth noting that, as per the import-demand equation selected to forecast the
opportunity, the above scenarios are closely tied to the following assumptions that if
disproved could materially impact the exports performance:

The UK's world prices have been used as a proxy to forecast UK prices to Mexico at
the absence of reliable data. It is unclear whether the UK's prices to the world closely
reflect the prices at which the UK could be exporting chocolate to Mexico. A
comparison with the other countries gives a mixed picture. In recent years, Italy has
been exporting to Mexico at prices below their world average prices, while Canada has
been exporting at prices equal to their world prices. USA has been recently exporting
at prices above their world prices, but historically it exported at prices below their
world average as well. Any deviation of prices to Mexico from the world price, whether
above it or below it, will impact exports to Mexico;
© 2013 Grant Thornton UK LLP. All rights reserved.
124

The main trade barrier with exports of chocolate to Mexico is tariffs imposed despite
the FTA that EU has signed with Mexico for more than a decade now. The Base
scenario assumes the reduction of tariffs from 26.9% to 10%, which may appear
ambitious, but is conservative in a sense if someone accounts for the 0% tariffs that
other competing countries are subject to (e.g. USA, Canada, Chile and Argentina); and

The UK will not continue losing share in the global trade of 180690 chocolate as it has
since 1998. The Base scenario assumes that the UK's share will be equal to the 20102011 levels given the resilience shown during these two years and the large historic
decline already suffered, which may be deemed ambitious. If UK continues losing its
share that could have a serious adverse impact on the exports forecast.
Section 7.4.5. Bakers' wares, wafers and biscuits exports to Mexico
Forecast values for the UK bakers' wares and biscuits exports to Mexico in 2016 were
estimated, assuming the reduction or complete elimination of tariffs within the next 2-3
years. The forecast value assumes that all other things not accounted for by the regression
are held constant to 2016.
Table 7.4.5.1 presents the results of the economic value estimations based on various
scenarios and sensitivity analyses. For details on the analysis undertaken and the
assumptions made for each scenario, please refer to Appendix E.
Table 7.4.5.1.
Potential opportunity for UK 1905 (bakers' wares, wafers and
biscuits) exports to Mexico in 2016
Base
Low
High
5,485
3,891
6,511
Upper range (£'000s)
6,034
4,280
7,162
Lower range (£'000s)
4,937
3,502
5,860
Value forecast (£'000s)
Sensitivity analysis on £/$ exchange rate (+/-10%)
The Base case scenario forecast provided above (£5.5m) reflects the export of 2,900
tonnes of 1905 bakers' wares and biscuits for 2016 under the UK export prices estimated
for 2016. This compares with 67 tonnes that Mexico reported imported from the UK in
2011. It is assumed that the UK industry would be able to respond relatively quickly to this
new demand and generate this supply over a relatively small period of time of 1-2 years
(assuming negotiations with Mexico to reduce the tariffs imposed take 2-3 years). Based on
empirical evidence of historic UK 1905 exports globally (during 2001-2011), the maximum
amount by which the UK was ever able to increase its exports over one year was 95,000
tonnes in 2007. In addition, in 2012, the industry increased its exports by 21,000 tonnes.
Solely based on this historic behaviour and without assessing the production capacity or
other volume demands (e.g. domestic, from other regions abroad) for UK's chocolate
producers, it seems plausible that the UK will be able to respond to the new demand
estimated for Mexico over a period of one year.
Also, as per the import-demand equation selected, it is worth noting that the above
scenarios are closely tied to the following assumptions that if disproved could materially
impact the exports performance:

125
At the absence of reliable data, the UK's world prices and the import weighted average
premium/discount applied by the EU competition (i.e. Italy and Spain) have been used
to forecast UK prices to Mexico. It is unclear whether this is a reliable way of
estimating the UK's price to Mexico. In 2011, Italy exported to Mexico with only a 2%
premium on the price compared to its world average price, while Spain exported at a
© 2013 Grant Thornton UK LLP. All rights reserved.
77% premium. The Base case scenario accounted for the competition's weighted
average premium. Any deviation from the estimated price, whether above or below it,
will impact exports (value and volumes) to Mexico;

The main trade barrier with exports of bakers' wares and biscuits to Mexico is tariffs
imposed despite the FTA that EU has signed with Mexico for more than a decade
now. The Base scenario assumes the reduction of tariffs from 14.2% to 5%, which may
appear ambitious, but is conservative in a sense if someone accounts for the 0% tariffs
that other competing countries are subject to (e.g. USA, Canada); and

The UK will not continue losing share in the global trade of 1905 as it has been doing
during the period covered by this analysis. The Base scenario assumes that the UK's
share will be equal to the 2011 levels given the large historic decline already suffered,
which may be deemed ambitious. If UK continues losing its share that could have an
adverse impact on the exports forecast.
Section 7.4.6. Beef to Japan
Forecast values for the UK beef exports to Japan in 2016 were estimated, assuming the
removal of the sanitary ban within the next 2-3 years. The forecast value assumes that all
other things not accounted for by the regression are held constant to 2016.
Table 7.4.6.1 presents the results of the economic value estimations based on various
scenarios and sensitivity analyses. For details on the analysis undertaken and the
assumptions made for each scenario, please refer to Appendix F.
Table 7.4.6.1
Potential opportunity for UK 020130 (beef) exports to Japan
in 2016
Base
Low
High
11,784
7,871
12,457
Upper range (£'000s)
12,962
8,658
13,703
Lower range (£'000s)
10,606
7,084
11,211
Value forecast (£'000s)
Sensitivity analysis on £/$ exchange rate (+/-10%)
The Base case scenario forecast provided (£11.8m) reflects the export of 2,675 tonnes of
020130 beef for 2016 under the UK export prices estimated for 2016. This compares with
zero tonnes currently imported from the UK by Japan due to the ban imposed on UK
beef. It is assumed that the UK beef industry would be able to respond relatively quickly to
this new demand and generate this supply over a relatively small period of time of 1-2 years
(assuming negotiations with Japan to remove the ban take 2-3 years). Based on empirical
evidence of historic UK 020130 exports globally (during 1998-2011), the UK has been
increasing significantly its exports since 2006 when countries that had imposed ban on the
UK started lifting them following reassurances that the UK beef was free from BSE. For
example, from 2.8kilotonnes (kt) in 2001, UK's global exports increased to 12.1kt in 2006
and 44.6kt in 2010. Even in 2011, UK's exports increased by 5.4kt to reach 50.0kt. Solely
based on this historic behaviour and without assessing the production capacity for UK's
beef producers, it seems plausible that the UK will be able to respond to the new demand
estimated for Japan over a period of a year (and assuming there is not significant additional
demand generated by other regions elsewhere in the world during the same time period).
Even accounting for the expected import restriction of importing beef from cattle younger
than 30 months old (that Japan is currently imposing on other EU nations), it is
understood based on data from Defra that less than 20% of the UK's beef comes from
cattle older than 30 months old. Therefore, this import restriction is not expected to pose
significant pressure on UK's cattle capacity.
© 2013 Grant Thornton UK LLP. All rights reserved.
126
The scenarios above are closely tied to the following assumptions that if disproved could
materially impact the exports performance:

A conservative assumption made in the Base scenario is that the UK will not be able to
continue growing its share in the world export beef market despite its growing share
over the past 5-10 years. If the UK does manage to grow its global share, that could
impact positively on its exports to Japan;

Despite the shrinking trade ties between Japan and UK over the past decade, the share
of business generated by Japan has stabilised over the last four years and the base
scenario reflects that. Otherwise, UK's beef exports could be smaller. However,
following the announcement by the EU to start discussions for an FTA with Japan, the
UK can be hopeful that Japan will grow its importance as a trading partner in the
future (and potentially even affect the tariff levels in a positive way, similarly to Mexico
who is subject to a 0% tariff for its beef exports to Japan); and

A potential challenge that has not been accounted for by the model is the presence of
greater competition in the future. Following Japan's ban lift on France and Netherlands
in 2013, the UK will have two EU players to compete with for the Japanese market,
whose 2016 income levels and beef consumption (as per FAO/OECD) are expected
to stay at the current levels. As such, these countries will need to attract some of the
share currently held by the larger players in the market.
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Conclusion
Following a comprehensive research and analytical exercise, this study has, for UK agrifood exports:

Established where the most significant trade barriers are;

Identified a long list of opportunities;

Sized the economic value associated with a sample of the most
prominent opportunities;

Identified where effort from Government and industry could be focused to
achieve growth.
In addition, the study has developed a robust methodology, which Government and
industry can use to monitor and investigate export opportunities. The methodology
established is grounded in broad literature review, primary research with businesses,
industry associations and policymakers and extensive data collection and
quantitative analysis.
The literature review covered a range of academic studies and reports published by
international organisations on trade economics, market access barriers and trade barriers'
quantification techniques. The literature review was not central to the project's objectives
but it was necessary to provide context and ground the work of the analysis conducted.
Also, the review highlighted the benefits of removing trade barriers and provided
additional evidence for Government action in opening up trade for UK businesses.
The interviews conducted were designed to complement the findings and data collected
through desktop research. The interview sample was not designed to be statistically
representative but to collect real-life examples of issues that UK businesses face in the
process of exporting and the approach they take in dealing with a range of trade barriers.
Although not a central element of the project (as another Defra-commissioned study
focused on areas for Government support was running in parallel), the interviews also
captured areas where the Government can assist businesses with their exporting activities.
The largest part of the study consisted of data collection, processing and analysis in order
to identify significant export opportunities with sizeable market value and significant trade
barriers in place. In the longlisting exercise, target countries with valuable markets, strong
food imports and positive economic growth potential were ranked and 30 of them were
selected for further investigation. The 30 countries represent a wide mix, including large
developed economies, smaller wealthy ones, BRIC nations and other emerging markets.
The longlist of products focused on UK product categories at the 4-code HS level where
the UK is well-positioned to trade internationally. Out of 184 categories investigated and
ranked, 20 of them were selected based on strong RCA rating, sizeable world imports and
UK exports to the EU and non-EU countries. The list of 20 products includes 10 highly
processed categories, 8 lightly processed and 2 unprocessed categories.
Whilst shortlisting the countries and products identified above, the focus was on matching
countries and products that offered opportunities with high economic potential for UK
exporters, but which were blocked due to the presence of trade barriers (a mix of tariff and
non-tariff barriers). A three-step approach was developed to filter out the original 600
combinations to a manageable number of opportunities that could be further evaluated
and sized in the next stage of the project. As such, attention should be drawn to the
outputs of step 1 of the shortlisting analysis (i.e. the 118 product/country combinations) as
all of them represent potential export opportunities with barriers in place that could be
© 2013 Grant Thornton UK LLP. All rights reserved.
128
pursued by Government and industry. The final six product/country combinations
selected at the end of the shortlisting process represent significant opportunities that were
carefully selected (amongst 56 product/country combinations) based on a rigorous
approach, but the remaining 112 should not be disregarded.
The six products carried forward for economic valuation were selected on a range of
criteria, amongst which: size of domestic market and import demand, presence of tariffs
and/or NTMs, retail and distribution network, competing exporting nations and terms of
trade with the UK versus competitors. The feasibility and timeline of removing existing
trade barriers was also a factor considered. The timeline used for the trade barriers'
removal was in the medium-term (i.e. 3-5 years) as per scoping discussions with the Defra
team. When forecasting for each opportunity, UK's industry production capacity was used
to ensure it is possible to meet the additional demand generated within the timeframe
investigated. This was tested by analysing the variance of historic UK world exports.
The economic opportunity associated with the six products selected was forecast to 2016,
because under all cases there was evidence that with focused Government/EU efforts and
industry action, the barriers could be removed. Even in the most challenging situation,
such as beef exports to Japan (who adopts stringent quality controls and high SPS
standards), whose historic behaviour resulted in full ban for UK meat exports and partial
ban for exports from other countries over a long period of time; recent developments
(access for French and Dutch beef as well as US and Canadian beef) indicate that it is
feasible for the UK to obtain similar access in the next four years. However, it is not
confirmed that all the barriers assessed can be removed by 2016, only that the conditions
required to do so are already in place if Government and industry pursue them in a timely
and consistent manner.
In some cases, the products assessed were facing a number of barriers. The most
important/prohibitive barriers and their impact on trade have been carefully assessed by
the team, and where relevant built into the import demand equations (e.g. for chicken meat
to China, tariffs, the sanitary ban as well as inspection requirements were accounted for in
the selected import demand equation. For sheep meat to China, inspection requirements
were disregarded from the relationship selected as they equally applied across all countries
and the team had no reason to believe that this would change in the foreseeable future).
Even though the equations may account for a number of barriers, the forecasting mainly
considers the removal of the most prohibitive barrier and forecasts the remaining trade
barriers as per historic trends. This was done to obtain realistic outputs, to avoid putting
the UK in an overly optimistic position compared to its rivals and maintain a Government
focus on the key issues that need to be addressed in each case. For example, in the case of
chicken to China, the base case scenario forecasts the value of exports if the ban for UK
meat is removed, whilst plant inspections are expected to be maintained and tariff rates to
be reduced in line with historic behaviour for all exporting countries.
This project will directly contribute to the commitments made in Defra‟s Export Action
Plan and help deliver Defra‟s Business Plan commitment on the potential for growth
through overseas trade. More specifically, this study will enable the prioritisation of policy
interventions at critical leverage points, for example where the ratio of potential market
opportunity to the cost of overcoming barriers to access that opportunity, is higher.
Targeting of policy interventions at these points can be expected to result in greater
positive impact for UK agri-food and drink businesses. The output of this project will
therefore assist in targeting trade barrier negotiations as well as offer clear and
comprehensive information to industry and trade associations in order to fulfil their role in
lifting market access barriers.
As a next step, to reap the benefits of this theoretical analysis, Government resources
could be focused on selecting a group of countries where a number of opportunities for
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UK agri-food exports exist. This can be achieved by further investigating the outputs of
this study but bearing in mind that opportunities may exist beyond the 20 product
categories longlisted in this study. In this case, the methodology developed by this report
can be applied by Government to test the opportunities in place across a wider number of
product categories in the countries identified. Furthermore, UKTI regional offices in the
target countries can inform this process and test local demand based on the local market
knowledge and contacts.
Even though it is understood that trade is an EU competence and that UK Government
needs to allocate a lot of resources to promote UK interests in discussions with the
Commission, high-level ministerial involvement is still crucial to engage in bilateral
negotiations with target countries and unlock barriers for the UK industry. Based on
industry discussions, Government resources should also continue to be focused on
providing businesses with a central information portal with export guidance, in-depth
practical market insights and commercial solutions and funding for trade fairs to showcase
the British agri-food industry.
Moreover, concerted action from the industry and Government can produce a stronger
partnership as proven by past evidence (e.g. the opening of the pork market in China
which was the result of negotiations and concerted effort by UKTI, Defra and the British
Pig Association and is expected to result in exports worth £45 million over five years). The
industry can in turn use the outputs of this report and the methodology established to
allow it to target new markets more effectively. More specifically, industry can follow a
similar approach to better understand the opportunity in place, benchmark its competitive
position and where possible attempt to address any deficiencies.
This project has addressed a key priority for Government and industry to investigate where
opportunities for UK agri-food exports exist and where trade barriers are blocking access
to these markets. Thorough research and analysis has been undertaken to develop a robust
methodology that can be used by both Government and industry to support their export
growth strategy. The findings indicate that significant and varied opportunities exist across
countries and products, but require concerted and focused actions to be realised.
© 2013 Grant Thornton UK LLP. All rights reserved.
130
Appendix
A. Estimating the value of UK chicken meat exports to
China
Step 1
Parameters and benchmark countries selection
In order to obtain the most detailed and relevant results, the product shortlisted at the end
of Chapter 6 (0207 'meat and edible offal of poultry meat') was decomposed at the 6-code
HS level to understand the exact sub-product category that China is importing. This
ensured that, given the wide category of food products covered by poultry, the project
team narrowed down the specific poultry opportunity for the UK:

020714: Fowls (gallus domesticus), cuts & offal, frozen (92.1% of total 0207 Chinese
imports in 2011) - hereby referred to as 'chicken'; and

020727: Turkey, cuts & offal, frozen (7.6% of total 0207 Chinese imports in 2011).
Following this investigation, turkey products were disregarded given the small size of the
opportunity compared to chicken (020714). Therefore, the import demand equation was
used to estimate the value of UK 020714 exports to China if the existing ban due to
sanitary reasons were to be removed. 020714 is also the 0207 category that UK currently
exports the most globally, accounting for 49% (in value terms) of all 0207 exports.
It is worth noting that China's 020714 imports can be further broken down to the 8-code
HS level:

02071422: Frozen chicken claw (44% of 020714 imports);

02071421: Frozen mid-joint wing of chicken (42% of 020714 imports);

02071411: Frozen cuts chicken, with bone (8% of 020714 imports); and

02071429: Frozen offal of chicken, not elsewhere specified (6% of 00714 imports).
Frozen chicken claws and the mid-joint wings, which form the largest part of China's
020714 imports, are part of the so called 'fifth quarter' that is not widely consumed in the
UK, but presents a good opportunity to export to China. As such, there is not a large
discrepancy in the level of quality of China's chicken '020714' imports.
The analysis is carried out by accounting for the behaviour of historic UK exports to China
as well as by analysing the behaviour of 020714 imports from competing countries. The
comparative approach also has the advantage that it enriches the limited sample data
available on the UK (as discussed in the following sections) by comparing the impact of
trade barriers imposed on the UK with the impact on other exporting nations. In the case
of 020714 chicken to China, when analysing trade, Brazil, USA and Argentina were
revealed as the major exporters to China historically (since 1996). In addition, France, who
exports only a small share to China, is the only major European exporter, and as such was
selected for comparative purposes (as the trade barriers it faces are more similar to those of
the UK compared to the three major exporters USA, Brazil and Argentina). Therefore, in
step 2, the data collection and processing exercise includes data on UK, France, China, US,
Brazil and Argentina.
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© 2013 Grant Thornton UK LLP. All rights reserved.
Step 2
Data collection
In order to estimate the most appropriate import demand equation to estimate UK chicken
meat exports to China, a data collection exercise was undertaken, namely sourcing the
parameters/variables that were deemed necessary as inputs in the regression analysis. Most
of the data collected spanned the 1996-2011 period, mainly because trade data (that was
one of the main inputs to the equation) is not available at the 6-code HS level prior to
1996. The data collected was on an annual basis because trade barriers imposed by the
target market on the UK and comparison countries investigated is not tracked and
centralised, and therefore, data was deemed challenging to collect on a quarterly or
monthly basis. As Defra's timeline is short-to-medium term, forecasts were collected
(where available) up to 2016. More details on forecasting the parameters is provided in step
5. Therefore, the economic analysis undertaken to estimate the chicken export opportunity
is based on data from the 1996-2011 period and forecasts up to 2016.
As mentioned in the literature review section, demand is broadly driven by income levels
and the relative import price. Therefore, the data collected for this project includes
parameters that exert an impact on income levels in China and price of chicken meat:

With regards to income, GDP is the generic income parameter used in macroeconomic
studies. However, given that this project accounts for agri-food products, GDP
components, such as private consumption, were also investigated as they were
considered more appropriate proxies for income levels of the population in the target
market. Similarly, private consumption may not be the most appropriate parameter
given its scale compared to the much smaller value of domestic consumption of a
particular agri-food sub-category, such as 020714 – cuts and offal of chicken. As such,
another suitable parameter would be food consumption in China, but the figures were
not available across the review period 1996-2011.Therefore the retail market value of
020714 was considered to be an appropriate proxy (the chicken meat retail market
value in China was approximated in Step 3 using inputs collected at this stage, namely
the retail price for chicken meat in China and China's poultry consumption). All of the
above income parameters were collected and tested to identify the most suitable inputs
in the import demand equation; and

As regards price, a variety of prices were collected to account for China's domestic
prices, the price of UK imports to China vs. competing countries and the retail price
for chicken meat in China.
In addition, trade/import data was collected together with the various tariff and non-tariff
measures applied by China against the UK and comparison countries over the
1996-2011 period.
Overall, data was collected on a number of variables across four major categories that were
considered to explain the behaviour of imports' demand; trade/import data, domestic
market size/income, prices and trade barriers.
In the case of chicken to China, the focus was primarily on non-tariff measures since tariffs
were identical across all five countries. However, tariff levels for all five countries
demonstrated a declining trend over time and were incorporated in the import prices to
compare against domestic retail prices in China. In terms of non-tariff measures, they were
first introduced in the regression analysis as dummy variables and were therefore, collected
in a binary format (with a value of '1' if a barrier was in place for a given year against a
certain country and '0' to indicate no barrier was in place). However, as shown in step 3,
some of these trade barriers were then processed and entered in the model in a nondummy format where it was deemed more appropriate and where the results turned out to
be more statistically significant.
© 2013 Grant Thornton UK LLP. All rights reserved.
132
The data collected is presented in Table A.1. It is worth noting that more parameters were
actually collected and tested during this first evaluating exercise, but failed to demonstrate
any explanatory power in the regression and were therefore dismissed. As such, the
following table includes the most relevant parameters collected and tested. Some of the
parameters below were not used in the regression analysis stage, but rather in the
forecasting stage as explained in Step 5.
Table A.1.
Parameters collected
Country coverage
Source
19962011
Brazil, USA, Argentina,
UK, France
Trade Map, Comtrade
China GDP
19962016
China
China total private consumption
19962016
China
China poultry production and
consumption in volume terms
19972021
China
FAO/OECD, USDA
Wholesale price of 020714 to China by
exporting country
19962011
Brazil, USA, Argentina,
UK, France
Trade Map, Comtrade
Wholesale price of 020714 to the
World by exporting country
19962011
Brazil, USA, Argentina,
UK, France
Trade Map, Comtrade
World and EU price of poultry
19962021
World, EU
FAO/OECD
World wholesale price of poultry
based on global exports
19962011
World
Trade Map, Comtrade
Retail price for poultry in China
19962016
China
FAPRI
Exchange rate for Euro, UK Sterling
and Chinese Renminbi in US Dollar
terms
19962016
China, USA, EU, UK
Economist Intelligence
Unit
Tariff rates
19962011
Brazil, USA, Argentina,
UK, France
Sanitary and phytosanitary measures
(in this case, export bans)
19962011
Brazil, USA, Argentina,
UK, France
Countervailing and anti-dumping
measures (taxes applied on imports
which act as ban because they make
the product prohibitively expensive)
19962011
Brazil, USA, Argentina,
UK, France
Parameter
type
Category
Trade data
Exports of 020714 to China and the
World in volume and value terms
Market
size/income
Price
Trade
barriers
Inspection requirements (products
exported must be produced in a plant
certified for exports in the target
market. Inspection requirements act as
a barrier because of the lengthy
process to get a plant certified, thus
the volume exported is controlled by
the importing country)
133
Time
series
19962011
Brazil, USA, Argentina,
UK, France
World Bank,
Economist Intelligence
Unit
World Bank,
Economist Intelligence
Unit
Trade Map, WTO,
TRAINS
USDA, WTO, MADB,
trade press, documents
published by the
ministries/embassies of
comparison countries
USDA, WTO, MADB,
trade press, documents
published by the
ministries/embassies of
comparison countries
USDA, WTO, MADB,
trade press, documents
published by the
ministries/embassies of
comparison countries
© 2013 Grant Thornton UK LLP. All rights reserved.
Step 3
Data processing
The data collected above was further processed and adjusted to make it relevant to the
current project (the specific effort of evaluating the opportunity for chicken meat in China)
and the methodology proposed (running a log linear regression to identify the relevant
import demand equation).
The changes to the raw data collected and the new variables created were decided upon
following a number of iterations and trial tests in order to enhance the regression and
increase the robustness of the forecasts. These changes took place for a number
of reasons:

Data was not always available at the 6-code HS level at which the analysis is
undertaken and therefore, needed to be derived from available inputs (e.g. calculated
the retail market size for China's 020714 chicken, by accounting for China's retail
poultry price, the total consumption levels for poultry and by comparing the total
poultry imports with the total 020714 levels of imports);

The team tried to minimise the number of variables (and especially the use of dummy
variables if an alternative was available) used in the regression, but at the same time
capture as much information as possible for the regression to be robust;
 e.g. China imposed large duties on US chicken meat imports in 2010 in the form of
countervailing and antidumping measures. The original approach was to introduce a
countervailing measure dummy to explain the behaviour of US chicken imports, but
then it was considered more appropriate to apply the duty as an increase on the US
price instead and removed the countervailing dummy variable.

In an effort to further reduce the use of dummy variables and ensure the independent
variables are explaining the behaviour of imports demand, the observations collected
and associated with periods of sanitary bans on chicken imports were completely
removed from the regression sample. This way, the model did not account for any
period during which China had imposed a sanitary ban on the imports of a specific
country and, therefore, the regression is estimating import values in the absence of
sanitary bans and by accounting for all other parameters presented in the following
table; and

As a result of removing a number of trade barriers associated dummies and due to the
decision not to use fixed effects in the regression (as it is a dynamic model where
import demand has been changing through time for each of the countries), it was
necessary to collect additional data on parameters that would indicate the differing
trade relationships each country has with China throughout time (e.g. an index of
bilateral trade across manufacturing sectors between each comparison country
and China).
The data processing that was undertaken to value the opportunity for chicken meat to
China is explained below in Table A.2.
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134
Table A.2.
Data processing
Parameter type
Category
Time series Country
coverage
Methodology
Source
Trade data
Global market
share of country's
exports of 020714
1996-2011
Brazil, USA,
Argentina,
UK, France
Trade Map,
Comtrade
Total trade
(excluding services)
between exporting
countries and China
1996-2011
Brazil, USA,
Argentina,
UK, France
Calculated each
country's global exports
of 020714 as a % of
total global trade of
020714 to help explain
the historic levels of
imports to China
Calculated each
country's total trade
with China as a % of the
country's total global
trade to help explain the
country's trade
relationships with China
Adjusted China
domestic
consumption of
020714
1997-2011
China
Looked into the historic
share of imports of
020714 over 0207 and
applied it on the total
poultry consumption of
China by FAO
FAO, Trade
Map, Comtrade
China's domestic
market value proxy
for 020714
1997-2011
China
Using China's retail
price proxy below and
China's adjusted
domestic consumption
of 020714 above
FAO, Trade
Map, Comtrade,
FAPRI
World price proxy
for poultry
1996-2011
World
FAO
Chinese retail price
proxy
1996-2011
China
Wholesale price to
China with tariffs
added
1996-2011
Brazil, USA,
Argentina,
UK, France
Competition's
import weighted
average prices for
020714 (excluding
the specific
exporting country)
1996-2011
Brazil, USA,
Argentina,
UK, France
Competition's
import weighted
1996-2011
China, Brazil,
USA,
Calculated by looking
into the weighted
average producers' price
of the top poultry
producing countries that
account for 60-70% of
the world production
Applied the average
price difference of
Chinese imports of 0207
and 020714 and applied
the % difference on
China's retail poultry
price
The tariffs were tested
in the regressions in two
different ways; as a
stand-alone variable for
each country separately
and by adding them on
top of the wholesale
price at which each
country exported sheep
meat to China. In the
latter case, separate price
ratios were created that
accounted for the
exporting prices
including tariffs
Reflects the importing
competition's weighted
average price by the
value of imports.
Derived the import
weighted average price
of 020714 exports to
China for each year and
each country but
excluding the imports of
the specific country
Divided the two
parameters
Market
size/income
Price
135
Trade Map,
Comtrade
FAPRI, Trade
Map, Comtrade
Trade Map,
Comtrade
Trade Map,
Comtrade
Trade Map,
Comtrade
© 2013 Grant Thornton UK LLP. All rights reserved.
Parameter type
Category
Time series Country
coverage
average prices over
China retail prices
Trade barriers
Methodology
Source
Argentina,
UK, France
Wholesale price to
China over China
retail prices
1996-2011
China, Brazil,
USA,
Argentina,
UK, France
Divided the two
parameters
Trade Map,
Comtrade
Wholesale price to
China over
competition's
import weighted
average prices
1996-2011
China, Brazil,
USA,
Argentina,
UK, France
Divided the two
parameters
Trade Map,
Comtrade
Countervailing and
anti-dumping
measures
2010-2011
USA
MADB, WTO,
press search,
documents
published by the
ministries and
embassies of
comparison
countries
Sanitary and
phytosanitary
measures
1996-2011
Brazil, USA,
UK, France
Given these measures
only concern the USA
and the immediate result
was to make USA
products significantly
more expensive through
the countervailing and
anti-dumping taxes
imposed on US chicken
imports in
August/September
2010, the % increase
was added to the US
imported weighted
average price
Removed all
observations associated
with sanitary ban
periods and as a result
completely removed the
'ban' dummy from the
regression
The data outlined above reflects the various iterations the project team performed, but
only a number of these variables were shortlisted for running the import demand equation
regression analysis.
Step 4
Regression analysis
The chosen regression equation and the associated results are presented in the following
table. A pooled OLS regression model with Driscoll and Kraay standard errors (i.e. robust
standard errors for panel regressions with cross-sectional dependence) was used for
estimation. Given the number of parameters in the regression and the number of
observations available for each country, data pooling66 was necessary in this case in order
to increase the number of degrees of freedom. In addition, given the regression is trying to
estimate China's demand for imports, it is always accounting for the importing country's
perspective, rather than the exporter's. As such, China‟s elasticity of demand (for example)
should not change based on which country the import is coming from. Hence, data
pooling is a reasonable approach.
The error structure is assumed to be heteroskedastic and autocorrelated. Driscoll-Kraay
standard errors are robust to general forms of cross-sectional (across countries, in this
case) and temporal dependence when the time dimension becomes large. In the specific
implementation, the constant term was removed since the constant term was statistically
In pooled, or combined, data are elements of both time-series and cross-section data. For example, the data
on each country's exports to China from 1996-2011 is time-series data, whereas the data on the exports to
China for the five competing countries for a single year are cross-sectional data. In this case, the pooled data
would consist of 80 observations – 16 annual observations for each of the five countries.
66
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136
insignificant when included. The R-squared tends to be higher when the constant term is
omitted but in this case, even with the constant term, the R-squared reached 76% which is
quite respectable given the large amount of variation in the data.
All the variables of interest turn out to be statistically significant and have the expected
signs. The fact that the estimates allow for the presence of autocorrelation in the residuals
takes care to some extent of some of the possible non-stationarity issues that might be
relevant in a time series regression. As discussed, several tests were run in order to
investigate the presence of unit roots and cointegration in the variables of interest. The
results of these tests were somewhat inconclusive given the low power of unit root tests to
reject the null hypothesis of a unit root and the low power of cointegration tests to reject
the hypothesis of no cointegration. While there was some suspicion that non-stationarity
may be an issue in the variables of the model, the many attempts that were made to correct
for this yielded very poor statistical results. Vector error correction methods and dynamic
OLS methods led either to statistically insignificant parameters or unreasonable estimated
forecasts for the variable of interest.
One of the main problems caused by non-stationarity is auto-correlation in the residuals.
Since the chosen regression method is able to control for auto-correlation in the residuals,
since it yields reasonable and precise estimates of the variables of interest and also because
it has reliable in-sample prediction behaviour, there is sufficient confidence to proceed
with this model to build forecasts for the UK exports.
Table A.3.
Equation chosen to forecast UK chicken meat exports to
China
Regression with Driscoll-Kraay standard errors
Number of obs =75
Method: Pooled OLS
Number of groups = 5
Group variable (i): country
F( 4, 14) = 2852.57
maximum lag: 1
Prob > F = 0.0000
R-squared = 0.9875
Root MSE = 1.1814
Drisc/Kraay
imp_val_p
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
Share of country's total
exports to China as % of
total country's global exports
1.311
.1721122
7.61
0.000
.9414573
Exporting country's global
chicken exports as a % of
world trade of chicken
0.686
.0665852
10.30
0.000
.5431373 .8287596
Proxy for China's domestic
market value of 020714
0.974
.0291151
33.44
0.000
.9111729
Ratio of exporting country's
price to China over China's
domestic retail price of
020714 (with tariffs built in
the prices)
(1.981)
.3510474
-5.64
0.000
-2.734072 -1.228228
Inspection requirement
dummy
(0.686)
.3196324
-2.15
0.050
-1.371355 -.0002681
1.679745
1.036064
As discussed, the coefficients of the parameters above have the expected signs. All
parameters have a positive sign except for the inspection requirements dummy, which,
when in place, exerts a negative impact on imports and the price ratio (i.e. the wholesale
price at which a country exports chicken to China over China's domestic price), which
indicates that when a country increases its price as a proportion to China's domestic price,
137
© 2013 Grant Thornton UK LLP. All rights reserved.
then imports by the specific country are adversely affected. In addition, it appears that the
price ratio and China's export share are the only elastic variables (i.e. their coefficients are
smaller than -1.0 and larger than 1.0 respectively) and therefore, the imports demanded are
most sensitive with these two variables than the remaining ones. This means that small
movements in prices or the overall trade ties with China can have a more severe impact on
the chicken imports demanded by China than a movement in China's chicken meat market
size (for example).
In the context of a log-linear equation, which is what has been used to run the regression
analyses in Chapter 7, the parameters' coefficients indicate the percentage change of the
dependent variable's value for each unit movement in the value of the independent
variable. For example, if the equation is represented by:
ln(y) = a1 × ln(x1) + a2 × ln(x2) + …. + c
where y is the dependent variable, x1 is one of the independent variables and a1 represents
the coefficient for x1, then, if x1 increases by 'b%', y will grow or decline by 'a1 × b%'.
Step 5
Economic value forecasting
The most suitable import demand equation identified in step 4 was used to estimate the
economic value of UK exports to China in the absence of the phytosanitary ban. As
discussed, following discussions with Defra, this analysis provided estimates for UK's
export potential accounting solely for the removal of the sanitary bans for UK poultry
exports. As such, the forecast figure provided in the Section 7.4.1 assumed that inspection
requirements for UK facilities exporting to China will stay in place, as they apply to most
countries exporting to China.
The economic value for UK exports was calculated for 2016, assuming that it will take 2-3
years for UK/EU trade negotiations to lead in the removal of trade barriers and a short
period during which exports will be ramped up. The forecast was calculated in US $ and
then converted to GBP using forecast exchange rates.
Before forecasting for the value of imports in 2016, it was necessary to forecast the values
of the explanatory variables involved to input them in the import demand equation. For
some of them, the forecast values were publicly available, but for others, separate
regression analyses had to be run or assumptions had to be made to estimate their value
in 2016.
A scenario analysis was undertaken on some of the variables, assuming that the previous
years' trend will continue (base scenario), whilst high and low case scenarios were also
modelled. Please refer to the tables below for the assumptions made at this stage of
the analysis.
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138
Table A.4.
Explanatory variable
Inspection requirement
dummy
Assumptions made for forecasting the parameters used in
the import demand equation – Base case scenario
Value forecast for Methodology
2016 under Base
scenario
1 (Dummy
variable)
Following discussions with Defra, this exercise for chicken in China will
only assume the removal of the sanitary ban barrier by 2016. Therefore,
the assumption is that UK plants will be required to go through the
inspection process
Share of country's total
exports to China as % of
total country's global
exports
4.4%
Takes the linear trend from 2006 onwards and carries it forward
Exporting country's
global chicken exports
as a % of world trade of
chicken
1.8%
Takes the average value from the last 5 years since 2006
China's domestic retail
price of 020714
$3.02 per kg
Proxy for China's
domestic market value
of 020714
$57.8bn
UK's export price of
020714 to China
Ratio of exporting
country's price to China
over China's domestic
retail price of 020714
(with tariffs built in the
prices)
139
$1.56 per kg
0.54
By sourcing China's retail poultry price forecasts from Fapri (in RMB
currency) and the RMB/USD forecast exchange rates by EIU, China's
retail price forecasts for 2016 in $ terms was derived. To identify the
020714 specific price, the team analysed the average % difference in the
country's poultry and 020714 imports (which has demonstrated a very
small variance of +/-2% over the 16 years since 1996) and took into
account the average difference since 2006
Having forecast China's retail price for 020714, the forecasts provided by
FAO/OECD in terms of China's total consumption of poultry in volume
terms were taken into account. The split in imports between 0207 and
020714 historically was considered to estimate the consumption of
020714 chicken in China and the analysis accounted for a number of
scenarios to estimate the total retail market size in 2016
Using EU world poultry price forecasts provided by FAO/OECD and
using EUR/USD exchange rates provided by EIU, a regression analysis
was run on the relationship between UK's export prices of 020714 and
EU's poultry prices to identify a strong and statistically significant
relationship. Therefore, the value provided was forecast based on the
outputs of this linear regression analysis. However, it is worth noting that
the price at which a country exports its products and the quantities
imported by another country are in reality linked and inter-dependent
Derived using the figures above and by accounting for a further reduction
in tariffs from 6.7% in 2011 to 4% in 2016. This tariff assumption is
solely based on the 2.3% reduction that took place in 2010 and the fact
that tariffs have historically been reduced from 20% in 1996. Even if this
assumption may appear to be overly optimistic, the regressions have been
tested by applying equal tariffs across all countries and the UK will
therefore, not gain any comparative advantage from this likely tariff
reduction
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Table A.5.
Explanatory variable
Inspection requirement
dummy
Forecasting assumptions for High scenario
Value forecast for Methodology
2016 under High
scenario
1 (Dummy
variable)
Following discussions with Defra, this exercise for chicken in China will
only assume the removal of the sanitary ban barrier by 2016. Therefore,
the assumption is that UK plants will be required to go through the
inspection process
Share of country's total
exports to China as % of
total country's global
exports
4.4%
Takes the weakest 5 year CAGR during 1996-2011 and carries it forward
Exporting country's
global chicken exports
as a % of world trade of
chicken
2.3%
Takes the strongest 5 year CAGR from 1996-2011 and carries it forward
China's domestic retail
price of 020714
$3.02 per kg
Proxy for China's
domestic market value
of 020714
$60.4bn
Having forecast China's retail price for 020714, the forecasts provided by
FAO/OECD in terms of China's total consumption of poultry in volume
terms were taken into account. The split in imports between 0207 and
020714 historically was considered to estimate the consumption of
020714 chicken in China and the analysis accounted for a number of
scenarios to estimate the total retail market size in 2016 (in this case the 5
year average since 2006)
$1.56 per kg
Using EU world poultry price forecasts provided by FAO/OECD and
using EUR/USD exchange rates provided by EIU, a regression analysis
was run on the relationship between UK's export prices of 020714 and
EU's poultry prices to identify a strong and statistically significant
relationship. Therefore, the value provided was forecast based on the
outputs of this linear regression analysis. However, it is worth noting that
the price at which a country exports its products and the quantities
imported by another country are in reality linked and inter-dependent
UK's export price of
020714 to China
Ratio of exporting
country's price to China
over China's domestic
retail price of 020714
(with tariffs built in the
prices)
0.532
By sourcing China's retail poultry price forecasts from Fapri (in RMB
currency) and the RMB/USD forecast exchange rates by EIU, China's
retail price forecasts for 2016 in $ terms was derived. To identify the
020714 specific price, the team analysed the average % difference in the
country's poultry and 020714 imports (which has demonstrated a very
small variance of +/-2% over the 16 years since 1996) and took into
account the average difference since 2006
Using figures above and assuming tariff reduction from 6.7% to 3%
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140
Table A.6.
Explanatory variable
Inspection requirement
dummy
Forecasting assumptions for Low scenario
Value forecast for Methodology
2016 under Low
scenario
1 (Dummy
variable)
Following discussions with Defra, this exercise for chicken in China will
only assume the removal of the sanitary ban barrier by 2016. Therefore,
the assumption is that UK plants will be required to go through the
inspection process
Share of country's total
exports to China as % of
total country's global
exports
3.0%
Constant on 2011 value
Exporting country's
global chicken exports
as a % of world trade of
chicken
1.5%
Takes the linear trend from 2007 onwards and carries it forward
China's domestic retail
price of 020714
$3.02 per kg
Proxy for China's
domestic market value
of 020714
$55.2bn
Having forecast China's retail price for 020714, the forecasts provided by
FAO/OECD in terms of China's total consumption of poultry in volume
terms were taken into account. The split in imports between 0207 and
020714 historically was considered to estimate the consumption of
020714 chicken in China and the analysis accounted for a number of
scenarios to estimate the total retail market size in 2016 (in this case
historically smallest consumption rate since 1996)
$1.56 per kg
Using EU world poultry price forecasts provided by FAO/OECD and
using EUR/USD exchange rates provided by EIU, a regression analysis
was run on the relationship between UK's export prices of 020714 and
EU's poultry prices to identify a strong and statistically significant
relationship. Therefore, the value provided was forecast based on the
outputs of this linear regression analysis. However, it is worth noting that
the price at which a country exports its products and the quantities
imported by another country are in reality linked and inter-dependent
0.551
Derived using the figures above and by assuming no further reduction in
tariffs from 6.7% in 2011
UK's export price of
020714 to China
Ratio of exporting
country's price to China
over China's domestic
retail price of 020714
(with tariffs built in the
prices)
141
By sourcing China's retail poultry price forecasts from Fapri (in RMB
currency) and the RMB/USD forecast exchange rates by EIU, China's
retail price forecasts for 2016 in $ terms was derived. To identify the
020714 specific price, the team analysed the average % difference in the
country's poultry and 020714 imports (which has demonstrated a very
small variance of +/-2% over the 16 years since 1996) and took into
account the average difference since 2006
© 2013 Grant Thornton UK LLP. All rights reserved.
B. Estimating the value of UK sheep meat exports to China
Step 1
Parameters and benchmark countries selection
In order to obtain the most detailed and relevant results, the product shortlisted at the end
of Chapter 6 (0204 'meat of sheep or goats') was decomposed at the 6-code HS level to
understand the exact sub-product category that China is importing. This ensured that,
given the wide category of food products covered by sheep and goat meats, the project
team narrowed down the specific opportunity for the UK:

020442: Sheep cuts, bone in, frozen (97.4% of total 0204 Chinese imports in 2011).
Therefore, the import demand equation was used to estimate the value of UK 020442
exports to China if the existing ban due to sanitary reasons were to be removed.
When trying to break down China's 020442 imports to the 8-code HS level to get an even
better understanding of the specific imports by China, it is not clear what kind of quality
cuts China imports. However, by comparing the average worldwide export prices of the
countries exporting to China 020442 sheep meat and the prices at which they export these
products to China, the prices to China turn out to be much lower (more specifically, 30%50% lower according to the country). Assuming that transportation cost savings (since
most of the competition comes from countries relatively close to China as discussed
below) do not allow for such large price differences, it can be implied that China imports
the lower quality cuts of sheep meat that are not widely consumed in the UK, but present a
good opportunity to export to China.
The analysis was therefore carried out by analysing the behaviour of the imports from
competing countries. In the case of sheep meat to China, there is no data available for the
UK, at least for the period of 1992-2011 (when trade data is publically available for
020442) due to the sanitary ban imposed during these years. In the case of 020442 sheep
meat to China, when analysing trade, New Zealand, Australia and Uruguay were revealed
as the major exporters to China historically (since 1992). Altogether, these three countries
accounted for 100% of China's 020442 imports in 2011. Uruguay was not exporting to
China prior to 2005 due to a sanitary ban and in 2011 it exported $7m worth of 020442
sheep meat. No European country (facing similar trade barriers to the UK) is currently
exporting 020442 to China. Therefore, in step 2, the data collection and processing
exercise includes data on China, Australia, New Zealand, Uruguay and the UK (for the
UK, data has been collected on its worldwide export activities of 020442 sheep meat rather
than China specific for comparative and forecasting purposes).
Step 2
Data collection
In order to select the most appropriate import demand equation to estimate UK sheep
meat exports to China, a data collection exercise was undertaken, namely sourcing the
parameters/variables that were deemed necessary as inputs in the regression analysis. Most
of the data collected spanned the 1992-2011 period, mainly because trade data (that was
one of the main inputs to the equation) is not available at the 6-code HS level prior to
1992. The data collected was on an annual basis because trade barriers imposed by the
target market on the UK and comparison countries investigated is not tracked and
centralised, and therefore, data was deemed challenging to collect on a quarterly or
monthly basis. The same applies on data around domestic sheep meat prices, etc. As
Defra's timeline is short-to-medium term, forecasts were collected (where available) up to
2016. More details on forecasting the parameters are provided in step 5.
As mentioned in the literature review, demand is broadly driven by income levels and the
relative import price. Therefore, the data collected for this project includes parameters that
exert an impact on income levels in China and price of sheep meat:
© 2013 Grant Thornton UK LLP. All rights reserved.
142

With regards to income, GDP is the generic income parameter used in macroeconomic
studies. However, given that this project accounts for agri-food products, GDP
components, such as private consumption, were also investigated as they were
considered more appropriate proxies for income levels of the population in the target
market; and

As regards price, a variety of prices were collected to account for China's domestic
prices, the price of UK imports to China vs. competing countries and the producers'
price for sheep meat in China. Retail prices would have been preferable to producers'
prices but they were not available. However, according to FAO/OECD, China
produces more than 98% of the sheep meat it consumes. As such, China's producers'
prices should effectively capture movements in the domestic price of sheep meat and
therefore relative price movements as the import demand equation commands.
In addition, trade/import data was collected together with the various tariff and non-tariff
measures applied by China against the UK and comparison countries over the 1992-2011
review period.
Overall, data was collected on a number of variables across four major categories that were
considered to explain the behaviour of imports' demand: trade/import data, domestic
market size/income, prices and trade barriers.
In terms of trade barriers, the focus was primarily on the sanitary ban imposed on imports
from the UK. Tariff levels for EU imports were at 12% similarly to imports from Australia
and Uruguay and have been enjoying a declining trend over time. However, New Zealand
who has recently entered in a Free Trade Agreement (FTA) with China has been enjoying
preferential tariff levels (at 6.7% in 2011 and expected to be reduced to 0% by 2015). In
terms of the sanitary bans, they were first introduced in the regression analysis as dummy
variables and were therefore, collected in a binary format (with a value of '1' if a barrier was
in place for a given year against a certain country and '0' to indicate no barrier was in
place). However, as discussed in step 3, regressions using different datasets were run; one
with the sanitary ban dummy variable and the ban observations and one without the ban
observations and therefore the ban dummy.
The following table includes the most relevant parameters collected and tested. Some of
the parameters shown in the following table were not actually used in the regression
analysis stage, but were collected for forecasting purposes as shown in Step 5.
143
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Table B.1.
Parameter
type
Trade data
Market
size/income
Parameters collected
Time series
Country coverage
Source
Exports of 020442 to China and the
World in volume and value terms
1992-2011
China, UK, New
Zealand, Australia,
Uruguay
Trade Map,
Comtrade
China GDP
1992-2016
China
China total private consumption
1992-2016
China
China sheep meat production and
consumption in volume terms
1991-2021
China
Category
Wholesale price of 020442 to China by
exporting country
Wholesale price of 020442 to the
World by exporting country
World price of sheep meat
Price
Producer price for sheep meat in
China and European Union
Exchange rate for Euro, UK Sterling
and Chinese Renminbi in US Dollar
terms
Trade
barriers
Step 3
1992-2021
UK, New Zealand,
Australia, Uruguay
UK, New Zealand,
Australia, Uruguay
World
Trade Map,
Comtrade
Trade Map,
Comtrade
FAO/OECD
1992-2021
China, EU27
FAO/OECD
1992-2016
China, USA, UK, EU
Economist
Intelligence Unit
1992-2011
1992-2011
1993-2016
(incomplete
years)
UK, New Zealand,
Australia, Uruguay
Sanitary and phytosanitary measures
(in this case export bans)
1992-2011
UK, New Zealand,
Australia, Uruguay
Shipping route distance between
China – Shanghai (China's largest
commercial port) and each country's
major port
N/A
China, UK, New
Zealand, Australia,
Uruguay
Tariff rates
World Bank,
Economist
Intelligence Unit
World Bank,
Economist
Intelligence Unit
FAO/OECD,
USDA
Trade Map, WTO,
TRAINS and trade
press
WTO, MADB,
trade press
Desktop research
Data processing
The data collected above was further processed and adjusted to make it relevant to the
current project (the specific effort of evaluating the opportunity for sheep meat in China)
and the methodology proposed (running a log linear regression to identify the relevant
import demand equation).
The changes to the raw data collected and the new variables created were decided upon
following a number of iterations and trial tests in order to enhance the regression and
increase the robustness of the forecasts. These changes took place for a number
of reasons:

To minimise the number of variables (and especially the use of dummy variables if an
alternative was available) used in the regression, but at the same time capture as much
information as possible for the regression to be robust;
 e.g. tariffs imposed by China on sheep meat imports were tested in the regression
both as a stand-alone variable and also by incorporating them in the average import
prices from each country individually;

In an effort to further reduce the use of the ban dummy variable and ensure the
independent variables are explaining the behaviour of imports demand effectively, two
datasets were tested; one with the sanitary ban dummy variable and the ban
observations and one without the ban observations and the ban dummy. In the latter
case and similarly to chicken in China the model did not account for any period during
which China had imposed a sanitary ban on the imports of a specific country and
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144
therefore, the regression is estimating import values in the absence of sanitary bans and
by accounting for all other parameters presented in the following table; and

It was necessary to collect additional data on parameters that would indicate the
differing trade relationships each country has with China throughout time (e.g. an
index of bilateral trade across manufacturing sectors between each comparison country
and China).
The data processing that was undertaken to value the opportunity for sheep meat to China
is explained in Table B.2. Overall, it was decided to remove the observations from 19921995 due to significant variances noticed in the average export prices across countries
(which may be attributed to small trade values at the time and unreliable volume
figures reported).
Table B.2.
Data processing
Parameter Category
type
Global market share
of country's exports
of 020442
Trade
data
Total trade (excluding
services) between
exporting countries
and China
Wholesale price to
China
Price
Trade
barriers
145
Time
series
Country
coverage
Methodology
19952011
UK, New
Zealand,
Australia,
Uruguay
China, UK,
New Zealand,
Australia,
Uruguay
Uruguay
Calculated each country's global exports of 020442 as
a % of total global trade of 020442 to help explain
the historic levels of imports to China
19952011
19952004
Wholesale price to
China with tariffs
added
19952011
UK, New
Zealand,
Australia,
Uruguay
Competition's import
weighted average
prices for 020442
19952011
UK, New
Zealand,
Australia,
Uruguay
Competition's import
weighted average
prices over China
producers' prices
Wholesale price to
China over China
producers' prices
19952011
Wholesale price to
China over
competition's import
weighted average
prices
Tariff rates
19952011
UK, New
Zealand,
Australia,
Uruguay
UK, New
Zealand,
Australia,
Uruguay
UK, New
Zealand,
Australia,
Uruguay
19952011
19952005
UK, New
Zealand,
Australia,
Uruguay
Calculated each country's total trade with China as a
% of the country's total global trade to help explain
the country's trade relationships with China
For the regressions run with the ban observations
(during 1995-2004), when Uruguay was not exporting
to China, an estimated price had to be entered for
Uruguay's potential exports. To calculate the price, a
separate regression analysis was run between
Uruguay's export prices to China from 2005-2011
and the price of Uruguay's exports to the rest of the
world. Following the results of this regression, it was
possible to estimate the prices at which Uruguay
could have been exporting its sheep meat to China
during the ban period
The tariffs were tested in the regressions in two
different ways; as a stand-alone variable for each
country separately and by adding them on top of the
wholesale price at which each country exported
sheep meat to China. In the latter case, separate price
ratios were created that accounted for the exporting
prices including tariffs
Reflects the importing competition's weighted
average price by the value of imports. Derived the
import weighted average price of 020442 exports to
China for each year and each country, but excluding
the imports of the specific country
Divided the two parameters
Divided the two parameters
Divided the two parameters
Out of the 17-year period covered in this analysis,
tariff rates were not available on the
WTO/TRAINS/Trade Map databases for six years.
In this case, the tariffs were filled in by assuming they
were similar to the previous/closest period.
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The data outlined above reflects the various iterations performed, but only a number of
these variables were shortlisted for running the import demand equation
regression analysis.
Step 4
Regression analysis
The chosen regression equation and the associated results are presented in the following
table. A pooled OLS regression model with Driscoll and Kraay standard errors was used
for estimation. The error structure is assumed to be heteroskedastic and autocorrelated.
Driscoll-Kraay standard errors are robust to general forms of cross-sectional (across
countries, in this case) and temporal dependence when the time dimension becomes large.
All the variables of interest turn out to be statistically significant and have the expected
signs. The regression obtained very high R-squared. This is an indication that the variation
in the explanatory variables in fact explains a large part (96.5%) of the variation in the
dependent variable. This can be considered quite high even for a time series model
(particularly given that the time series in the case of sheep meat to China is not very long at
17 periods). On the other hand, such a high R-squared could raise concerns that some of
the variables in the regression may have unit roots. When there are unit roots on the left
hand side and on the right hand side of the regression, a very strong R-squared can be
generated even if the variables are not strongly correlated.
To overcome the above, it is possible to include as an additional explanatory variable a
lagged version of the dependent variable. This can indicate the impact of unit roots on the
estimates. A model with the lagged dependent variable was run and, as expected, there
were changes in the values of the coefficients. However, the appropriateness of the overall
fit was not affected in a meaningful way: the R-squared increased by less than 1%; the
estimates of the parameters of interest are slightly less precise; the model with lags of the
dependent variable has a disadvantage in that it cannot be used for forecast since the UK
does not have reliable data for the dependent variable in the period covered.
The fact that the estimates allow for the presence of autocorrelation in the residuals takes
care to some extent some of the possible non-stationarity issues that might be relevant in a
time series regression. As discussed, several tests were run in order to investigate the
presence of unit roots and cointegration in the variables of interest. The results of these
tests were somewhat inconclusive given the low power of unit root tests to reject the null
hypothesis of a unit root and the low power of cointegration tests to reject the hypothesis
of no cointegration. While there was some suspicion that non-stationarity may be an issue
in the variables of the model, the many attempts that were made to correct for this yielded
very poor statistical results. Vector error correction methods and dynamic OLS methods
led either to statistically insignificant parameters or unreasonable estimated forecasts for
the variable of interest.
One of the main problems caused by non-stationarity is auto-correlation in the residuals.
Since the chosen regression method is able to control for auto-correlation in the residuals,
as it yields reasonable and precise estimates of the variables of interest and also because it
has reliable in-sample prediction behaviour, there is sufficient confidence to proceed with
this model to build forecasts for the UK exports.
The regression followed in the case of sheep meat exports to China is quite different to the
approach followed for chicken exports to China. This is understood since one specific type
of regression may not be appropriate for all valuations that need to be realised. Even
though the markets may appear to be similar in behaviour (especially in the case of sheep
meat and chicken meat exports to China), one single regression may not suffice to explain
all relationships especially given the limited number of observations in each case and the
relatively large number of explanatory variables that are included in each relationship.
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146
Table B.3.
Equation chosen to forecast UK sheep meat exports to China
Regression with Driscoll-Kraay standard errors
Number of obs = 51
Method: Pooled OLS
Number of groups = 3
Group variable (i): country
F( 5, 16) = 255.01
maximum lag: 2
Prob > F = 0.0000
R-squared = 0.9650
Root MSE = 0.7857
Drisc/Kraay
imp_val_p
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
Constant coefficient
(77.7854)
9.2895
Sanitary ban dummy
China's total private
consumption
Exporting country's
global sheep meat
exports as a % of world
trade of sheep meat
Share of country's total
exports to China as % of
total country's global
exports
Ratio of exporting
country's price to China
over competition's
exporting price of
020442 to China (with
tariffs built in the prices)
(2.9997)
0.7425
(8.3700)
0
-97.47837 -58.09248
(4.0400)
0.001
-4.573817 -1.425563
4.4593
0.4330
10.3000
0
3.541491 5.37716
1.1147
0.1086
10.2700
0
.8845206 1.344834
0.8983
0.2773
3.2400
0.005
.3105249 1.486146
(0.8526)
0.3391
(2.5100)
0.023
-1.571573 -.1337126
As discussed above, the coefficients of the parameters above have the expected signs. All
parameters have a positive sign except for the sanitary ban dummy, which when in place
exerts a negative impact on imports and the price ratio (i.e. the wholesale price at which a
country exports sheep meat to China over the competition's exporting price), which
indicates that when a country increases its price as a proportion to the competition's export
price, then imports by the specific country are adversely affected. In addition, it appears
that private consumption and global sheep meat export share are the only elastic variables
(i.e. their coefficients are larger than 1.0) and therefore, the imports demanded are most
sensitive with these two variables than the remaining ones. This means that small
movements in China's private consumption can have a more severe impact on the sheep
meat imports demanded by China than a movement in overall trade ties with China
(for example).
Step 5
Economic value forecasting
The most suitable import demand equation identified in step 4 was used to estimate the
economic value of UK exports to China in the absence of the phytosanitary ban. As such,
the forecast figure provided in Section 7.4.2 assumed that inspection requirements for UK
facilities exporting to China will stay in place, as they apply to all competing countries
exporting to China.
The economic value for UK exports was calculated for 2016, assuming that it will take 2-3
years for UK/EU trade negotiations to lead in the removal of trade barriers and a short
period during which exports will be ramped up. The forecast was calculated in US $ and
then converted to GBP using forecast exchange rates.
Before forecasting for the value of imports in 2016, it was necessary to forecast the values
of the explanatory variables involved to input them in the import demand equation. For
147
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some of them, the forecast values were publicly available, but for others separate
regression analyses had to be run or assumptions had to be made to estimate their value
in 2016.
A scenario analysis was undertaken on some of the variables, assuming that the previous
years' trend will continue (base scenario), whilst high and low case scenarios were also
modelled. Please refer to tables B.4-B.6 for the assumptions made at this stage of
the analysis.
Table B.4.
Explanatory variable
Assumptions made for forecasting the parameters used in
the import demand equation
Value forecast for Methodology
2016 under Base
scenario
Sanitary ban dummy
0 (Dummy variable)
Given that the aim is to assess UK's exports in 2016 assuming the removal
of the sanitary ban, a value of 0 was assigned to the respective dummy
variable
China's total private
consumption
$1,589,274,596,000
Made use of the Economist Intelligence Unit's forecasts for China's
private consumption (in constant terms in Yuans) and the forecast
USD/RMB exchange rate by 2016. The 2011-2016 growth rate forecast in
USD terms was applied to China's private consumption that the regression
used from World Bank (also in constant terms)
Exporting country's
global sheep meat
exports as a % of world
trade of sheep meat
1.30%
Share of country's total
exports to China as %
of total country's global
exports
4.4%
UK's wholesale price to
China of 020442
$2.95 per kg
During 2010 and 2011, UK's worldwide wholesale price of 020442 exports
were very competitive amongst Uruguay, New Zealand and Australia and
closely tracked Australia's world prices (at $4.2 per kg in 2011). At the
same time, UK's non-EU 020442 exports prices were well below the UK's
world average ($2.25 per kg versus $4.2 per kg) and well below Australia's
prices to China, which were at $3.01 per kg. Therefore, at this stage, a
conservative assumption was made that UK's 020442 export price to
China could have reflected Australia's price (i.e. at $3.01 per kg)
As such, assuming the UK's 020442 prices will continue to be competitive
and assuming they are closely linked to the European Union's sheep meat
producers' prices, then UK's price to China was forecast by accounting for
$3.01 per kg in 2011 and applying the growth forecast in EU's producer
prices (provided by FAO/OECD)
However, it is worth noting that the price at which a country exports its
products and the quantities imported by another country are in reality
linked and inter-dependent
Competition's
wholesale price to
China of 020442
$3.31 per kg
A separate multiple regression was run for the competition's price to
China by using Chinese sheep meat producers' prices and World price for
sheep meat as explanatory variables (both of which turned out to be
significant). The forecasts for the independent variables were provided by
FAO/OECD
Ratio of exporting
country's price to China
over competition's
exporting price of
020442 to China (with
tariffs built in the
prices)
0.95
Took the 5-year average the UK had between 2007-2011. This was a
conservative estimate given that over the past 4 years the UK has been
increasing its world share. However, it was determined to account for the
average since the 1.46% share (i.e. the UK's share in 2011) is only slightly
below the historic high the UK ever reached (i.e. 1.52%) over the 17-year
period covered by this analysis and given that the UK has increased its
share in the past to similar levels, but has then fallen behind again
Took the linear trend of China's trade share for the UK since 2006 and
carried it forward to 2016. China has grown significantly as UK's trade
partner and from 1.36% in 2006, it accounted for 2.98% of UK's total
products trade in 2011
The ratio was calculated by making use of the figures above. However, the
tariffs were first added on both the UK's price forecast and the
competition's price. Given that tariff rates for the UK/EU, Australia and
Uruguay have not changed since 2004 (they are still at 12%), the
assumption was that the tariffs will stay at the same level until 2016 for all
these countries. However, following the FTA New Zealand signed with
China, it is expected that tariffs for New Zealand will be removed by 2015,
which was accounted for in the forecasts made.
Again, this is a conservative assumption, since it is not unlikely that China
may lower its tariffs for the UK and the other countries, which would
improve UK's position compared to New Zealand who is the leading
exporter of sheep meat to China
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148
Table B.5.
Explanatory variable
Forecasting assumptions for High scenario
Value forecast for Methodology
2016 under High
scenario
Sanitary ban dummy
0 (Dummy variable)
Given that the aim is to assess UK's exports in 2016 assuming the
removal of the sanitary ban, a value of 0 was assigned to the respective
dummy variable
China's total private
consumption
$1,589,274,596,000
Made use of the Economist Intelligence Unit's forecasts for China's
private consumption (in constant terms in Yuans) and the forecast
USD/RMB exchange rate by 2016. The 2011-2016 growth rate
forecast in USD terms was applied to China's private consumption
that the regression used from World Bank (also in constant terms)
Exporting country's
global sheep meat
exports as a % of world
trade of sheep meat
1.50%
Takes the maximum share since 1994 (given that there has been
limited variation during the past 17 years)
Share of country's total
exports to China as %
of total country's global
exports
4.4%
Takes the weakest 5-year CAGR during 1996-2011 and carries it
forward
UK's wholesale price to
China of 020442
$2.69 per kg
UK's trend of 2010-2011 of having smaller prices on world (and
especially non-EU) exports is sustained to 2016 and tracks Australia's
World and China prices in 2010 & 2011. From then on, follows
decline in producer prices as per World sheep meat producer prices
However, it is worth noting that the price at which a country exports
its products and the quantities imported by another country are in
reality linked and inter-dependent
Competition's wholesale
price to China of
020442
$3.31 per kg
A separate multiple regression was run for the competition's price to
China by using Chinese sheep meat producers' prices and World price
for sheep meat as explanatory variables (both of which turned out to
be significant). The forecasts for the independent variables were
provided by FAO/OECD
Ratio of exporting
country's price to China
over competition's
exporting price of
020442 to China (with
tariffs built in the
prices)
0.847
The ratio was calculated by making use of the figures above. However,
the tariffs were first added on both the UK's price forecast and the
competition's price. Assumed 4.4% reduction in tariffs for all
countries and assumed New Zealand's will stay at 0%
149
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Table B.6.
Explanatory variable
Forecasting assumptions for Low scenario
Value forecast for Methodology
2016 under Low
scenario
Sanitary ban dummy
0 (Dummy variable)
China's total private
consumption
$1,589,274,596,000
Given that the aim is to assess UK's exports in 2016 assuming the
removal of the sanitary ban, a value of 0 was assigned to the respective
dummy variable
Made use of the Economist Intelligence Unit's forecasts for China's
private consumption (in constant terms in Yuans) and the forecast
USD/RMB exchange rate by 2016. The 2011-2016 growth rate
forecast in USD terms was applied to China's private consumption
that the regression used from World Bank (also in constant terms)
Exporting country's
global sheep meat
exports as a % of world
trade of sheep meat
1.10%
Share of country's total
exports to China as %
of total country's global
exports
3.0%
UK's wholesale price to
China of 020442
$4.13 per kg
UK returns to the historic high prices it had. By comparing 5 year
averages (2007-2011) of UK global prices and Competition's global
prices, UK's are 24.5% higher than competition's, which are calculated
below.
However, it is worth noting that the price at which a country exports
its products and the quantities imported by another country are in
reality linked and inter-dependent
Competition's wholesale
price to China of
020442
$3.31 per kg
A separate multiple regression was run for the competition's price to
China by using Chinese sheep meat producers' prices and World price
for sheep meat as explanatory variables (both of which turned out to
be significant). The forecasts for the independent variables were
provided by FAO/OECD
Ratio of exporting
country's price to China
over competition's
exporting price of
020442 to China (with
tariffs built in the
prices)
1.329
The ratio was calculated by making use of the figures above. However,
the tariffs were first added on both the UK's price forecast and the
competition's price. Assumed no reduction in tariffs for all countries
and assumed New Zealand's will stay at 0%
Takes the minimum share of the last 5 years (given that there has been
limited variation during the past 17 years)
Constant on 2011 value
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150
C. Estimating the value of UK crustaceans exports to USA
Contrary to the rest of the products investigated in Chapter 7, UK exports of crustaceans
to USA do not face significant trade barriers. The tariffs are at 0% and there are no
particular sanitary bans imposed on UK crustaceans, which forbid exporting activities to
the US. The only barriers that exist include horizontal non-tariff measures similar to those
imposed by US authorities on many other imports from the EU. As per MADB, these are
the barriers that are most relevant to imports from the EU:

Anti-dumping duties and practice of zeroing – zeroing is a calculation device used by
the United States for increasing, often substantially, the exporter's margin of dumping
and thus the amount of anti-dumping duty paid. Zeroing has two main effects on EU
exporters. Firstly, it increases the amount of duty paid on those goods exported to the
US, thus reducing their competitiveness. Secondly, by increasing the rate of antidumping duty, it deters many exporters from exporting to the US at all;

Rules of origin – USA does not recognise EU as a country of origin nor does it accept
EU certificates of origin. In order to justify EU country of origin status, EU firms are
required to furnish supplementary documentation and follow further procedures,
which can be a source of additional costs. However, this may not be relevant in the
case of crustaceans exports to USA; and

Import restrictions for the protection of endangered sea turtles – the US has
repetitively prohibited the importation of shrimp that was produced without Turtle
Excluder Device (TED) technology that is aimed to protect sea turtles. However, this
does not apply to UK crustaceans either.
The EU and UK Government can assist UK exporters with removing some of the barriers
mentioned above, but it understood that none of these barriers are forbidding entry of UK
exporters to the US market and these barriers can be overcome, if they are systematically
pursued by UK exporters (as stated by the interviewees during the primary research). It is
also understood that UK exporters may be discouraged from pursuing exports to the US
due to the domestic retail/distribution structure, which they perceive as being more
complex due to the presence of a number of players (i.e. retailers, wholesalers, distributors
as well as brokers).
The major barrier presented for the UK in the substantial crustaceans import market
(worth c.$4bn in 2011) is the competition from Asian countries who also control the
crustaceans trade on a world scale. Even though it has not been validated by desktop
research, it is understood that the horizontal barriers mentioned above are very likely
imposed on these Asian exporters as well and they appear to be exporting very successfully
crustaceans to the US market.
The valuation exercise in this section estimates the value of crustacean exports to USA if
this market was proactively targeted by UK exporters and taking into account the UK's
and competing countries' historic behaviour.
Step 1
Parameters and benchmark countries selection
In order to obtain the most detailed and relevant results, the product shortlisted at the end
of Chapter 6 (0306 'crustaceans') was decomposed at the 6-code HS level to understand
the exact sub-product category that USA is importing. Given the wide category of food
products covered by crustaceans, this enabled the narrowing down of the specific
opportunity for the UK:

151
030613: Shrimps and prawns, frozen, in shell or not, including boiled in shell (70% of
total 0306 US imports in 2011);
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
030614: Crabs frozen, in shell or not, including boiled in shell (13% of total 0306 US
imports in 2011);

030612: Lobsters not elsewhere specified, frozen, in shell or not, including boiled in
shell (7% of total 0306 US imports in 2011); and

030622: Lobsters not elsewhere specified, not frozen, in shell or not, including boiled
in shell (5% of total 0306 US imports in 2011).
Following this investigation, crabs, lobsters and the remaining crustaceans were
disregarded because of the small share they represent. The import demand equation was
used to estimate the value of UK 030613 exports to USA. In 2011, 030613 also accounted
for 20% of all 0306 crustaceans exports of the UK on a global basis (i.e. second most
exportable crustacean).
It is worth noting that USA's 030613 imports could be further broken down to:

0306130040: Shrimps and prawns, frozen, peeled (50% of 030613 imports);

0306130015: Shrimps and prawns, frozen, shell-on, 67-88 per kg
(9% of 030613 imports);

0306130009: Shrimps and prawns, frozen, shell-on, 46-55 per kg
(8% of 030613 imports); and

0306130003: Shrimps and prawns, frozen, shell-on, less than 33 per kg
(7% of 030613 imports).
It appears that the US imports higher quality shrimps and prawns judging by the high share
of peeled products as well as the medium/large size of shell-on ones. However, it is not
possible to compare the above break-down with UK's exports, which categorises its
030613 exports by the family type rather than the size and form served.
Therefore, the analysis was carried out by analysing the behaviour of imports from
competing countries as well as the early exports of UK products (as explained below, the
UK exports from the recent years were dropped from the analysis). In the case of
crustaceans to USA, Asian countries and Thailand in particular dominate trade with USA.
However, other countries such as Ecuador and Mexico also export significant quantities as
well (above $300m in 2011). These are also the countries that dominate the world trade of
shrimps and prawns. No European country (facing similar trade barriers to the UK) is
currently exporting significant quantities of 030613 to USA. Therefore, in step 2, the data
collection and processing exercise includes data on the UK and eight major competing
countries (Thailand, Indonesia, Ecuador, India, Vietnam, Mexico, Malaysia, China).
Step 2
Data collection
In order to estimate the most appropriate import demand equation to estimate UK shrimp
and prawns exports to USA, a data collection exercise was undertaken, namely sourcing the
parameters/variables that were deemed necessary as inputs in the regression analysis. Most
of the data collected spanned the 1991-2011 period, mainly because trade data (that was
one of the main inputs to the equation) was not available at the 6-code HS level prior to
1991. The data collected was on an annual basis because trade barriers imposed by the
target market on the UK and comparison countries investigated is not tracked and
centralised, and therefore, data was deemed challenging to collect on a quarterly or
monthly basis. The same applies on data around domestic crustacean prices, etc. As
Defra's timeline is short-to-medium term, forecasts were collected (where available) up to
2016. More details on forecasting the parameters is provided in step 5.
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152
As mentioned in the literature review, demand is broadly driven by income levels and the
relative import price. Therefore, the data collected for this project includes parameters that
exert an impact on income levels in USA and price of shrimps and prawns:

With regards to income, GDP is the generic income parameter used in macroeconomic
studies. In this case, a more disaggregated figure of the GDP was used by subtracting
exports from the GDP to make it more relevant to the domestic income level of the
USA population. However, given that this project accounts for agri-food products,
GDP components, such as private consumption, were also investigated as they were
considered more appropriate proxies for income levels of the population in the target
market; and

As regards price, a variety of prices were collected to account for USA's domestic
prices, the price of UK imports to USA vs. competing countries and the producers'
price for crustaceans in USA. Retail prices would have been preferable to producers'
prices but they were not available. However, according to FAO/OECD, USA
produces 60% of the fish it consumes. As such, USA's producers' prices should
effectively capture movements in the domestic price of seafood and therefore, relative
price movements as the import demand equation commands.
In addition, trade/import data was collected together with the various tariff and non-tariff
measures applied by USA against the UK and comparison countries over the 1991-2011
review period.
Overall, data was collected on a number of variables across four major categories that were
considered to explain the behaviour of imports' demand: trade/import data, domestic
market size/income, prices and trade barriers.
Tariff levels for EU imports as well as imports from the comparison countries have been
at 0% over the review period. As mentioned already, the UK exports have not faced any
significant trade barriers beyond the competition from the major exporting nations. In
terms of trade barriers faced by the comparison countries, the focus was primarily on the
anti-dumping duties and bans imposed by the USA. The anti-dumping duties, which
started being imposed primarily after 2004, concerned allegations that the crustaceans
industry (and shrimp farming in particular) was heavily subsidised by the government in
the respective country. These duties were removed around 2009-2010 for most countries,
but the USA has recently started reviewing new allegations against foreign government
subsidies and fears have been raised that a new round of anti-dumping duties may start
against USA's major exporters.
In terms of bans, these concerned disease outbreaks in the exporting countries as well as
the protection of sea turtles who were threatened in the fishing process of crustaceans in
many of the exporting countries (by not using turtle excluder devices in their nets while
fishing in areas where there is a significant likelihood of encountering sea turtles). In
addition, another parameter that has significantly affected countries' export levels over the
review period was production shocks due to adverse weather conditions in the exporting
countries. Last but not least, Vietnam, another major exporting nation of shrimps and
prawns, was subject to a trade embargo that was removed in 1993. These trade barriers
(bans from disease outbreaks and sea turtles protection, production shocks and trade
embargo) were entered in the model as dummy variables and were therefore, collected in a
binary format (with a value of '1' if a barrier was in place for a given year against a certain
country and '0' to indicate no barrier was in place).
The following table includes the most relevant parameters collected and tested. Some of
the parameters in the following table were not used in the regression analysis stage, but for
forecasting purposes as discussed in Step 5.
153
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Table C.1.
Parameters collected
Parameter
type
Category
Time series
Country coverage
Source
Trade data
Exports of 030613 to USA
and the World in volume
and value terms
1991-2011
UK, USA, Thailand,
Indonesia, Ecuador, India,
Vietnam, Mexico, Malaysia,
China
Trade Map, Comtrade
Market
size/income
USA GDP & exports
1991-2016
USA
USA total private
consumption
USA crustaceans/fish
production and
consumption in volume
terms
1991-2016
USA
1991-2021
USA
World Bank, Economist
Intelligence Unit
World Bank, Economist
Intelligence Unit
FAO/OECD
Wholesale price of 030613
to USA by exporting
country
1991-2011
Wholesale price of 030613
to the World by exporting
country
1991-2011
World price of fish
USA, UK and EU27
producer price for fish and
crustaceans
Exchange rate for UK
Sterling in US Dollar terms
1991-2021
1991-2021
UK, USA, Thailand,
Indonesia, Ecuador, India,
Vietnam, Mexico, Malaysia,
China
UK, USA, Thailand,
Indonesia, Ecuador, India,
Vietnam, Mexico, Malaysia,
China
World
USA, UK, EU27
1991-2016
USA, UK
Tariff rates
1991-2011
Anti-dumping duties
1991-2016
UK, USA, Thailand,
Indonesia, Ecuador, India,
Vietnam, Mexico, Malaysia,
China
UK, USA, Thailand,
Indonesia, Ecuador, India,
Vietnam, Mexico, Malaysia,
China
Sanitary and phytosanitary
measures, production
shocks, and other types of
export bans
1991-2011
UK, USA, Thailand,
Indonesia, Ecuador, India,
Vietnam, Mexico, Malaysia,
China
Shipping route distance
between major ports
N/A
UK, USA, Thailand,
Indonesia, Ecuador, India,
Vietnam, Mexico, Malaysia,
China
Price
Trade
barriers
Step 3
Trade Map, Comtrade
Trade Map, Comtrade
FAO/OECD
US Department of
Labor, ONS,
FAO/OECD
Economist Intelligence
Unit
Trade Map, WTO,
TRAINS
WTO, MADB, trade
press, documents
published by the
ministries/embassies of
comparison countries
USDA, WTO, MADB,
trade press, documents
published by the
ministries/embassies of
comparison countries
Desktop research
Data processing
The data collected above was further processed and adjusted to make it relevant to the
current project (the specific effort of evaluating the opportunity for shrimps and prawns in
USA) and the methodology proposed (running a log linear regression to identify the
relevant import demand equation).
The changes to the raw data collected and the new variables created were decided upon
following a number of iterations and trial tests in order to enhance the regression and
increase the robustness of the forecasts. These changes took place for a number
of reasons:

To minimise the number of variables (and especially the use of dummy variables if an
alternative was available) used in the regression, but at the same time capture as much
information as possible for the regression to be robust;
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154
 e.g. anti-dumping duties imposed by USA on 030613 imports were tested in the
regression both as a stand-alone variable and also by incorporating them in the
average import prices from each country individually;

In an effort to further reduce the use of dummy variables and ensure the independent
variables were explaining the behaviour of imports demand effectively, the different
types of trade barriers, which were entered as dummy variables in the model, were
merged into a single 'trade barrier' dummy. This was also done because the different
types of trade barriers involved were deemed to have a similar impact on trade across
the exporting countries all of which were exporting substantial quantities of shrimps
and prawns; and

It was necessary to collect additional data on parameters that would indicate the
differing trade relationships each country has with USA throughout time (e.g. an index
of bilateral trade across manufacturing sectors between each comparison country
and USA).
The data processing that was undertaken to value the opportunity for crustaceans in USA
is explained in Table C.2. It is worth noting that certain observations were removed from
the regression because data was not available across all parameters for that specific year
and country (29 observations were removed out of 189 in total). Amongst the data
removed, UK's trade observations between 2003-2011 were removed because the average
export prices obtained were rather volatile and varied significantly from the average due to
the small (and potentially unreliable) volume sizes reported by USA.
Table C.2.
Data processing
Parameter
type
Category
Time
series
Country coverage
Methodology
Trade data
Global market share
of country's exports
of 030613
19912011
Total trade
(excluding services)
between exporting
countries and USA
19912011
UK, USA, Thailand,
Indonesia, Ecuador,
India, Vietnam, Mexico,
Malaysia, China
UK, USA, Thailand,
Indonesia, Ecuador,
India, Vietnam, Mexico,
Malaysia, China
Calculated each country's global exports of
030613 as a % of total global trade of
030613 to help explain the historic levels
of imports to USA
Calculated each country's total trade with
USA as a % of the country's total global
trade to help explain the country's trade
relationships with USA
Wholesale price to
USA with duties
added
20052011
Thailand, Ecuador, India,
Vietnam, China
Competition's import
weighted average
prices for 030613
19912011
UK, USA, Thailand,
Indonesia, Ecuador,
India, Vietnam, Mexico,
Malaysia, China
Competition's import
weighted average
prices over USA
producers' prices
Wholesale price to
USA over USA
producers' prices
19912011
Wholesale price to
USA over
competition's import
19912011
UK, USA, Thailand,
Indonesia, Ecuador,
India, Vietnam, Mexico,
Malaysia, China
UK, USA, Thailand,
Indonesia, Ecuador,
India, Vietnam, Mexico,
Malaysia, China
UK, USA, Thailand,
Indonesia, Ecuador,
India, Vietnam, Mexico,
The duties were tested in the regressions in
two different ways; as a stand-alone
variable for each country separately and by
adding them on top of the wholesale price
at which each country exported shrimps
and prawns to China. In the latter case,
separate price ratios were created that
accounted for the exporting prices
including duties
Reflects the importing competition's
weighted average price by the value of
imports. Derived the import weighted
average price of 030613 exports to USA
for each year and each country, but
excluding the imports of the specific
country
Divided the two parameters
155
19912011
Divided the two parameters
Divided the two parameters
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Parameter
type
Category
Time
series
weighted average
prices
Trade
barriers
Anti-dumping duties
Country coverage
Methodology
Malaysia, China
20052011
Thailand, Ecuador, India,
Vietnam, China
It was not possible to obtain or calculate
an average duty imposed on 030613
imports throughout the whole period,
since the US authorities progressively
reduced the tariff imposed and imposed
different levels of tariffs to shrimp
producers from a single country. As such,
used a weighted approach based on the
trade press findings to apply an average
rate across countries and years
The data outlined above reflects the various iterations performed, but only a number of
these variables were shortlisted for running the import demand equation
regression analysis.
Step 4
Regression analysis
The specification chosen and attached in the following table uses the Generalised Least
Squares (GLS) estimator for random-effects models of cross-sectional time-series data
when the disturbance term is first-order autoregressive. The model specifies that there is
AR(1) autocorrelation within panels and that the coefficient of the AR(1) process is
common to all the panels. This method of regression also takes into account possible
heteroskedasticity of the errors since it is a GLS estimator.
The estimates of the coefficients on the independent variables are reasonably significant.
None of the price ratios that were tested seemed to add particularly to the explanation of
movements in the dependent variable. By using a lag of the price term (in this case the
price ratio of UK‟s competitors relative to USA‟s domestic price) all the coefficients of the
explanatory variables become statistically significant (the coefficient on the price term is
borderline significant, which means its level may not be estimated very precisely, even if it
does have the correct sign; it is recommended therefore, that this elasticity is interpreted
with caution). The remaining five explanatory variables are found to have a high level of
statistical significance.
The overall R-squared is close to 80%, which can be considered high for a panel model
such as this. Overall, this model can therefore, be considered to have a good statistical fit
to the data and as such, appropriate to use for forecasting UK exports. The chosen
regression equation and the associated results are presented in the following table.
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156
Table C.3.
Equation chosen to forecast UK crustaceans exports to USA
RE GLS regression with AR(1) disturbances
Number of obs = 160
Group variable: country
Number of groups = 9
R-sq:
corr(u_i, Xb)
within = 0.5011
Obs per group:
min = 10
between = 0.9384
avg = 17.8
overall = 0.7983
max = 20
= 0 (assumed)
Wald chi2 (7)
= 138.43
Prob > chi2
= 0.0000
------------------------------------------------- theta ---------------------------------------------min
5%
median
95%
max
0.3379
0.3379
0.4311
0.4311
0.4311
imp_val
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
Constant coefficient
(38.4295)
11.2110
(3.4300)
0.001
-60.40264 -16.45641
Trade barriers dummy
variable
(0.4973)
0.1249
(3.9800)
0.000
-0.742168 -0.252399
Anti-dumping duties
(0.0676)
0.0228
(2.9600)
0.003
-0.112409 -0.022885
USA's total private
consumption
2.4130
0.4854
4.9700
0.000
1.461532
Share of exporting
country's trade with USA
as % of total country's
global exports
0.4198
0.1327
3.1600
0.002
0.159734 0.679941
Exporting country's global
030613 exports as a % of
world trade of 030613
0.9518
0.1252
7.6000
0.000
0.706479
Ratio - Competition's
import weighted average
prices over USA producer
price
0.5888
0.3035
1.9400
0.052
-0.006061
rho_ar
0.74545311 (estimated autocorrelation coefficient)
sigam_u
0.40173498
sigma_e
0.35975013
rho_fov
0.55496839 (fraction of variance due to u_i)
3.364415
1.197081
1.183757
As discussed above, the coefficients of the parameters above have the expected signs. All
parameters have a positive sign except for the trade barriers dummy, which, when in place,
exerts a negative impact on imports and the anti-dumping, which indicates that when USA
increases the duties imposed on a certain country, then imports by the specific country are
adversely affected. In addition, it appears that USA's private consumption is the only
elastic variable (i.e. the coefficient is larger than 1.0) and therefore, the imports demanded
are most sensitive with this variable than the remaining ones. This means that small
movements in private consumption can have a more severe impact on the crustaceans'
imports demanded by USA than a movement in the price ratio (for example).
157
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Step 5
Economic value forecasting
The most suitable import demand equation identified in step 4 was used to estimate the
economic potential value of UK crustaceans' exports to USA. As discussed, the UK is not
currently facing specific trade barriers in its crustaceans' trade with the USA other than the
competition from the world's major suppliers.
The economic value for UK exports was calculated for 2016 similarly to the rest of the
products to give time to UK producers and exporters to increase production and penetrate
the USA market more effectively. The forecast was calculated in US$ and then converted
to GBP using forecast exchange rates.
Before forecasting for the value of imports in 2016, it was necessary to forecast the values
of the explanatory variables involved to input them in the import demand equation. For
some of them, the forecast values were publicly available, but for others separate
regression analyses had to be run or assumptions had to be made to estimate their value
in 2016.
A scenario analysis was undertaken on some of the variables, assuming that the previous
years' trend will continue (base scenario), whilst high and low case scenarios were also
modelled. Please refer to tables C.4-C.6 for the assumptions made at this stage of
the analysis.
Table C.4.
Explanatory variable
Trade barriers
USA's total private
consumption, constant
terms
Exporting country's global
shrimp and prawns exports
as a % of world trade of
shrimp and prawns
Share of country's total
exports to USA as % of
total country's global
exports
Anti-dumping duties
Competition's import
weighted prices of 030613
Assumptions made for forecasting the parameters used in
the import demand equation
Value forecast for Methodology
2016 under Base
scenario
0 (Dummy variable) The USA has not imposed this far any significant trade barriers on EU
exports of shrimps and prawns to the USA and there is no reason to
expect that this will change to 2016
$9,284,128,542 Used the Economist Intelligence Unit's forecasts for USA's private
consumption (in constant terms in $) by 2016. The 2011-2016 growth
rate forecast was applied to USA's historic private consumption that the
regression used from World Bank (also in constant terms)
0.4% The UK has been losing share over the past 10 years in terms of its
world share of shrimp and prawn exports. To calculate the forecast
share in 2016, a conservative approach was taken by using the CAGR
between 2007-2011 and projecting that to 2016. This can be deemed to
be conservative because UK's share in 2011 is already at record low
levels and it could be assumed that the UK will not continue losing
share at the same pace
9.6% The USA has been growing in importance as a trading partner between
2001-2010. However, in 2011, there was a slight decline (9.4% in 2011
versus 9.6% in 2010). Therefore, the Base scenario makes the
conservative assumption that by 2016 the USA's share as a trade partner
of the UK will not surpass its historic high 2010 level
0% No duties have been applied this far on EU exports and even though
the USA authorities are currently reviewing dumping allegations against
sever major shrimp exporters, there is no reason to believe that duties
may be imposed on the UK by 2016
$9.29 per kg Assuming that countries adjust their export prices to address the duties
occasionally imposed on them, a linear regression was run between
competition's weighted prices (with the occasional duties added to the
prices) and the 'world price - world unit value of trade for fish', the
historics and forecasts for which were provided by FAO/OECD.
Having obtained an estimate for the 2016 weighted average price of the
competition with the duty added, there was a need to filter out the
approximate duty included in the price. To do this, needed to estimate
the competition's weighted duty in 2016 by accounting for the fact that
the US is currently considering to impose a new round of anti-dumping
duties on most of the competing countries. As such, the Base scenario
assumes that USA will in fact impose new duties by the end of 2013 (as
the trade press also states) and that by 2016 these duties will have been
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158
Explanatory variable
Value forecast for Methodology
2016 under Base
scenario
progressively reduced in a similar fashion with the last round of duties
which started in 2005 (and therefore the levels in 2016 will be similar to
those in 2008)
However, it is worth noting that the price at which a country exports its
products and the quantities imported by another country are in reality
linked and inter-dependent
USA producer price of
crustaceans
119.5 (index) Ran a separate linear regression analysis between USA producer price
index for crustaceans and US producer price for fish. The historics and
forecasts for the US producer price for fish were provided by
FAO/OECD
Ratio of competition's
import weighted average
prices over USA producer
price of crustaceans
Table C.5.
0.078 The ratio was calculated using the figures above.
Forecasting assumptions for High scenario
Explanatory variable
Trade barriers
USA's total private consumption,
constant terms
Value forecast Methodology
for 2016 under
High scenario
0 (Dummy
variable)
$
9,284,128,542
The USA has not imposed this far any significant trade barriers
on EU exports of shrimps and prawns to the USA and there is
no reason to expect that this will change to 2016
Used the Economist Intelligence Unit's forecasts for USA's
private consumption (in constant terms in $) by 2016. The
2011-2016 growth rate forecast was applied to USA's historic
private consumption that the regression used from World
Bank (also in constant terms)
Exporting country's global shrimp
and prawns exports as a % of world
trade of shrimp and prawns
0.8%
The UK has been losing share over the past 10 years in terms
of its world share of shrimp and prawn exports. To calculate
the forecast share in 2016, takes the historic average since 2007
Share of country's total exports to
USA as % of total country's global
exports
10.5%
The USA has been growing in importance as a trading partner
between 2001-2010. However, in 2011, there was a slight
decline (9.4% in 2011 versus 9.6% in 2010). The scenario,
takes the 2-year CAGR during 2009-2011 and carries it
forward
0%
No duties have been applied this far on EU exports and even
though the USA authorities are currently reviewing dumping
allegations against sever major shrimp exporters, there is no
reason to believe that duties may be imposed on the UK by
2016
Anti-dumping duties
Competition's import weighted prices
of 030613
USA producer price of crustaceans
159
$9.29 per kg
132.02 (index)
Assuming that countries adjust their export prices to address
the duties occasionally imposed on them, a linear regression
was run between competition's weighted prices (with the
occasional duties added to the prices) and the 'world price world unit value of trade for fish', the historics and forecasts
for which were provided by FAO/OECD.
Having obtained an estimate for the 2016 weighted average
price of the competition with the duty added, there was a need
to filter out the approximate duty included in the price. To do
this, needed to estimate the competition's weighted duty in
2016 by accounting for the fact that the US is currently
considering to impose a new round of anti-dumping duties on
most of the competing countries. As such, the High scenario
assumes that USA will in fact impose new duties by the end of
2013 (as the trade press also states) and that by 2016 these
duties will have been progressively reduced in a similar fashion
with the last round of duties which started in 2005 (and
therefore the levels in 2016 will be similar to those in 2008)
However, it is worth noting that the price at which a country
exports its products and the quantities imported by another
country are in reality linked and inter-dependent
Takes average from early period with historic highs of
producer costs.
© 2013 Grant Thornton UK LLP. All rights reserved.
Value forecast Methodology
for 2016 under
High scenario
Explanatory variable
0.070
Ratio of competition's import
weighted average prices over USA
producer price of crustaceans
Table C.6.
Explanatory variable
Trade barriers
The ratio was calculated using the figures above.
Forecasting assumptions for Low scenario
Value forecast for Methodology
2016 under Low
scenario
0 (Dummy
variable)
USA's total private
consumption, constant
terms
$ 9,284,128,542
Exporting country's
global shrimp and
prawns exports as a %
of world trade of
shrimp and prawns
0.4%
Share of country's total
exports to USA as % of
total country's global
exports
Anti-dumping duties
4.9%
0%
Competition's import
weighted prices of
030613
$9.65 per kg
USA producer price of
crustaceans
Ratio of competition's
import weighted
average prices over
USA producer price of
crustaceans
93.20 (index)
0.103
The USA has not imposed this far any significant trade barriers on EU
exports of shrimps and prawns to the USA and there is no reason to
expect that this will change to 2016
Used the Economist Intelligence Unit's forecasts for USA's private
consumption (in constant terms in $) by 2016. The 2011-2016 growth
rate forecast was applied to USA's historic private consumption that the
regression used from World Bank (also in constant terms)
The UK has been losing share over the past 10 years in terms of its world
share of shrimp and prawn exports. To calculate the forecast share in
2016, a conservative approach was taken by using the CAGR between
2007-2011 and projecting that to 2016. This can be deemed to be
conservative because UK's share in 2011 is already at record low levels
and it could be assumed that the UK will not continue losing share at the
same pace.
The USA has been growing in importance as a trading partner between
2001-2010. However, in 2011, there was a slight decline (9.4% in 2011
versus 9.6% in 2010). The scenario, assumes decline started in 2010
(2011 level was slightly below 2010) to return to the 2005 level by 2016
No duties have been applied this far on EU exports and even though the
USA authorities are currently reviewing dumping allegations against sever
major shrimp exporters, there is no reason to believe that duties may be
imposed on the UK by 2016
Assuming that countries adjust their export prices to address the duties
occasionally imposed on them, a linear regression was run between
competition's weighted prices (with the occasional duties added to the
prices) and the 'world price - world unit value of trade for fish', the
historics and forecasts for which were provided by FAO/OECD.
Having obtained an estimate for the 2016 weighted average price of the
competition with the duty added, there was a need to filter out the
approximate duty included in the price. To do this, needed to estimate
the competition's weighted duty in 2016 by accounting for the fact that
the US is currently considering to impose a new round of anti-dumping
duties on most of the competing countries. As such, the Low scenario
assumes that USA will have removed all duties imposed on competition
by 2016.
However, it is worth noting that the price at which a country exports its
products and the quantities imported by another country are in reality
linked and inter-dependent
Takes 5-year average from 2008-2012
The ratio was calculated using the figures above.
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160
D. Estimating the value of UK chocolate exports to Mexico
Step 1
Parameters and benchmark countries selection
In order to obtain the most detailed and relevant results, the product shortlisted at the end
of Chapter 6 (1806 'chocolate and other food preparations containing cocoa') was
decomposed at the 6-code HS level to understand the exact sub-product category that
Mexico is importing. Given the wide category of food products covered by chocolate
products, this enabled the identification of the specific opportunity for the UK:

180690: Chocolate and other food preparations containing cocoa not elsewhere
specified (73.1% of total 1806 Mexican imports in 2011);

180620: Chocolate and other food preparations containing cocoa weighing more than
2 kg (14.8% total 1806 Mexican imports in 2011); and

180631: Chocolate and food preparations containing cocoa in blocks, slabs/bars, filled,
not exceeding 2 kg (7.2% total 1806 Mexican imports in 2011).
180690 also accounts for 62% of UK's 1806 world exports. Therefore, the import demand
equation was used to estimate the value of UK 180690 exports to Mexico assuming tariff
barriers would be reduced or removed completely as tariffs are the main trade barriers in
the case of 180690 UK exports to Mexico.
When trying to break down Mexico's 180690 imports to the 8-code HS level to get a better
understanding of Mexico's imports, it is not clear what specific kind of chocolate and food
preparations Mexico imports.
The analysis is carried out by analysing the behaviour of the imports from competing
countries. In the case of chocolate to Mexico, the UK has been historically exporting small
values of chocolates during 1992-2011 (during when trade data is publically available for
180690), but as explained further below, UK's exports to Mexico were disregarded from
the analysis. This was because at small trade values there is a higher risk that the volumes
recorded and reported are not reliable enough, therefore distorting significantly the average
prices calculated for UK exports to Mexico. In the case of chocolate to Mexico, when
analysing trade, USA, Canada, Argentina and Chile were revealed as the major exporters to
Mexico historically. Altogether, these four countries accounted for 94% of Mexico's
180690 imports in 2011. The analysis also captured Italy and Belgium, two EU nations
who face similar trade barriers with the UK and who together account for 2.5% of
Mexico's 180690 imports. Therefore, in step 2, the data collection and processing exercise
includes data on USA, Canada, Argentina, Chile, Italy, Belgium and the UK.
Step 2
Data collection
In order to estimate the most appropriate import demand equation related to UK
chocolate exports to Mexico, a data collection exercise was undertaken, namely sourcing
the parameters/variables that were deemed necessary as inputs in the regression analysis.
Most of the data collected spanned the 1992-2011 period, mainly because trade data (that
was one of the main inputs to the equation) is not available at the 6-code HS level prior to
1992. The data collected was on an annual basis because much of the data incorporated in
the analysis is not reported on a quarterly or monthly basis. As Defra's timeline is short-tomedium term, forecasts were collected (where available) up to 2016. More details on
forecasting the parameters is provided in step 5.
As mentioned in the literature review, demand is broadly driven by income levels and the
relative import price. Therefore, the data collected for this project includes parameters that
exert an impact on income levels in Mexico and price of chocolate:
161
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
With regards to income, GDP is the generic income parameter used in macroeconomic
studies. In this case, a more disaggregated figure of the GDP was used by subtracting
exports from the GDP to make it more relevant to the domestic income level of the
Mexican population. However, given that this project accounts for agri-food products,
GDP components, such as private consumption, were also investigated as they were
considered more appropriate proxies for income levels of the population in the target
market; and

As regards price, a variety of prices were collected to account for Mexico's domestic
prices, the price of UK imports to Mexico vs. competing countries and the producers'
price for chocolate in Mexico. Retail prices would have been preferable to producers'
prices but they were not available. However, as per FAO in 2008, Mexico produces
0.8% of the world's total cacao production even though it is not an active exporter and
consumes most of it domestically. Moreover, in terms of sugar, another key ingredient
for chocolate, Mexico produces more than it actually consumes as per FAO/OECD in
2011. As such, Mexico's chocolate producer prices should be a good reflection of the
actual prices of domestically produced chocolate and effectively capture domestic
chocolate's price movements and therefore, relative price movements as the import
demand equation commands.
In addition, trade/import data was collected together with the tariff measures applied by
Mexico against the UK and comparison countries over the 1992-2011 review period.
Overall, data was collected on a number of variables across four major categories that were
considered to explain the behaviour of imports' demand: trade/import data, domestic
market size/income, prices and trade barriers.
In terms of trade barriers, the focus was primarily on the tariffs imposed on imports from
the UK/EU. Tariff levels for EU imports were at 26.9%, which is not the case with the
competing countries whose trade agreements with Mexico have eliminated tariffs from
their 180690 exports. It is worth noting that on 1997 EU and Mexico signed an FTA
which came into force on 2000. Even though the FTA has led to the removal of trade
barriers horizontally and across many product categories, the tariffs for 180690 continue to
position EU nations at a disadvantage when compared with the other nations covered in
this analysis. No other particular trade barriers or NTMs were identified with regards to
chocolate trade with Mexico during the period investigated.
The following table includes the most relevant parameters collected and tested. Some of
the parameters shown in the following table were not actually used in the regression
analysis stage, but were collected for forecasting purposes as shown in Step 5.
© 2013 Grant Thornton UK LLP. All rights reserved.
162
Table D.1.
Parameters collected
Category
Trade data
Exports of 180690 to Mexico and the
World in volume and value terms
1992-2011 Mexico, UK, USA,
Trade Map, Comtrade
Canada, Argentina, Chile,
Italy, Belgium
Market
size/income
Mexico GDP and total worldwide
exports
1992-2016 Mexico
Mexico total private consumption
1992-2016 Mexico
Mexico cocoa and sugar production and
consumption in volume terms
1992-2016 Mexico
Wholesale price of 180690 to Mexico by
exporting country
1992-2011 UK, USA, Canada,
Argentina, Chile, Italy,
Belgium
1992-2011 UK, USA, Canada,
Argentina, Chile, Italy,
Belgium
1992-2015 World
Price
Time series Country coverage
Source
Parameter
type
Wholesale price of 180690 to the World
by exporting country
World and EU price of sugar and cocoa
Trade barriers
Producer price for tablet chocolate in
Mexico
1992-2021 Mexico
Exchange rate for Euro, UK Sterling
and Mexican Peso in US Dollar terms
1992-2016 Mexico, USA, EU, UK
Tariff rates
Shipping route distance between Mexico
and each country's major port
Step 3
1997-2016 UK, USA, Canada,
(incomplete Argentina, Chile, Italy,
years) Belgium
World Bank,
Economist
Intelligence Unit
World Bank,
Economist
Intelligence Unit
FAO/OECD
Trade Map, Comtrade
Trade Map, Comtrade
FAO/OECD,
desktop research
Mexico's National
Statistics Office
Economist
Intelligence Unit
Trade Map, WTO,
TRAINS and trade
press
N/A Mexico, UK, USA,
Desktop research
Canada, Argentina, Chile,
Italy, Belgium
Data processing
The data collected above was further processed and adjusted to make it relevant to the
current project (the specific effort of evaluating the opportunity for chocolate in Mexico)
and the methodology proposed (running a log linear regression to identify the relevant
import demand equation).
The changes to the raw data collected and the new variables created were decided upon
following a number of iterations and trial tests in order to enhance the regression and
increase the robustness of the forecasts. These changes took place for a number
of reasons:

The team tried to minimise the number of variables used in the regression, but at the
same time capture as much information as possible for the regression to be robust;
 e.g. tariffs imposed by Mexico on chocolate imports were tested in the regression
both as a stand-alone variable and also by incorporating them in the average import
prices from each country individually; and
 It was necessary to collect additional data on parameters that would indicate the
differing trade relationships each country has with Mexico throughout time (e.g. an
index of bilateral trade across manufacturing sectors between each comparison country
and Mexico).
The data processing that was undertaken to value the opportunity for chocolate to Mexico
is shortly explained in Table D.2. Overall, it was decided to remove the observations for
the UK exports due to significant variances noticed in the average export price, which may
be attributed to small trade values and potentially unreliable volume figures reported
(which tends to be the case for small value trades).
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Table D.2.
Data processing
Parameter
type
Category
Time Country
series coverage
Methodology
Trade data
Global market share of
country's exports of
180690
1992- UK, USA,
2011 Canada,
Calculated each country's global exports of 180690
as a % of total global trade of 180690 to help explain
the historic levels of imports to Mexico
Total trade (excluding
services) between exporting
countries and Mexico
Price
Wholesale price to Mexico
Wholesale price to Mexico
with tariffs added
Argentina,
Chile, Italy,
Belgium
1992- Mexico, UK,
2011 USA, Canada,
Argentina,
Chile, Italy,
Belgium
1992- Argentina, Chile During the period of 1992-1998, a total of six
1998
observations for both countries had to be replaced
1992- UK, USA,
2011 Canada,
Argentina,
Chile, Italy,
Belgium
Trade
barriers
Calculated each country's total trade with Mexico as
a % of the country's total global trade to help
explain the country's trade relationships with Mexico
Competition's import
weighted average prices for
180690
1992- UK, USA,
2011 Canada,
Competition's import
weighted average prices
over Mexico's producers'
prices
19922011
Wholesale price to Mexico
over Mexico producers'
prices
19922011
Wholesale price to Mexico
over competition's import
weighted average prices
19922011
Tariff rates
1992- UK, USA,
1996 Canada,
Argentina,
Chile, Italy,
Belgium
UK, USA,
Canada,
Argentina,
Chile, Italy,
Belgium
UK, USA,
Canada,
Argentina,
Chile, Italy,
Belgium
UK, USA,
Canada,
Argentina,
Chile, Italy,
Belgium
Argentina,
Chile, Italy,
Belgium
due to the significant variance observed in the prices
(similarly to the UK, these variances can be
attributed to the small trade values and volumes
reported) calculated. The prices were then replaced
with the average prices at which these countries
exported chocolate to the world during the
respective periods
The tariffs were tested in the regressions in two
different ways; as a stand-alone variable for each
country separately and by adding them on top of the
wholesale price at which each country exported
chocolate in Mexico. In the latter case, separate price
ratios were created that accounted for the exporting
prices including tariffs
Reflects the importing competition's weighted
average price by the value of imports. Derived the
import weighted average price of 180690 exports to
Mexico for each year and each country but excluding
the imports of the specific country
Divided the two parameters
Divided the two parameters
Divided the two parameters
Out of the 20-year period covered in this analysis,
tariff rates were not available on the
WTO/TRAINS/Trade Map databases for six years.
In this case, the tariffs were filled in by assuming
they were similar to the following years (especially
given that tariffs did not change during 1997-2003)
The data outlined above reflects the various iterations the project team performed, but
only a number of these variables were shortlisted for running the import demand equation
regression analysis.
Step 4
Regression analysis
A panel-data linear model was fitted by using feasible generalised least squares (FGLS).
Given that previous tests had indicated the presence of autocorrelation in the residuals
(shocks in period t-1 stay on to affect the dependent variable in period t), cross-sectional
correlation (similar shocks affect all countries in the sample contemporaneously) and
© 2013 Grant Thornton UK LLP. All rights reserved.
164
heteroskedasticity (the size of the variability of shocks is not constant across observations),
a regression method that corrects for all of them was used. In particular, a panel-specific
error autocorrelation structure has been assumed, a panel-specific error variance term and
six cross-sectional correlation terms. The error auto-regression term is estimated by the
model using a time series auto-correlation calculation.
The model yielded a good fit of the parameters of interest (the coefficients of the
explanatory variables), the estimated parameters have the expected sign and the model has
a reasonable overall fit (note that in this type of regression, R-squared is not typically
reported, but the conclusively significant Wald test provides reassurance of overall fit).
Overall, the estimated model offers a reliable base on which to forecast future levels of
UK exports.
Table D.3.
Equation chosen to forecast UK chocolate exports to Mexico
Cross-sectional time-series FGLS regression
xtgls imp_val priv_cons over_pri_mext_pro_pri choco_share mexic_share , panels(hetero) corr(psar1) rhotype(tscorr)
Coefficients: generalised least squares
Panels:
heteroskedastic
Correlation: panel-specific AR(1)
Estimated covariances = 6
Number of obs = 110
Estimated autocorrelations = 6
Number of groups = 6
Estimated coefficients = 5
Obs per group: min = 13
avg = 18.33
max = 20
Wald chi2(4) = 56.06
Prob > chi2 = 0.0000
imp_val_p
Constant coefficient
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
-236.2389 -82.63766
-159.4383
39.1847
-4.07
0.000
Mexico's private
consumption
6.482651
1.459585
4.44
0.000
3.621918
9.343384
Exporting country's global
180690 exports as a % of
world trade of 180690
chocolate products
1.052628
.2966007
3.55
0.000
.4713016
1.633955
Share of country's total
exports to Mexico as % of
total country's global exports
.8099142
.2432286
3.33
0.001
.3331949
1.286633
Ratio of exporting country's
wholesale price to Mexico
over Mexico's chocolate
producer price (with tariffs
built in the prices)
-.5197196
.2597657
-2.00
0.045
-1.028851 -.0105882
As discussed above, the coefficients of the parameters above have the expected signs. All
parameters have a positive sign except for the price ratio (i.e. the wholesale price at which a
country exports chocolate to Mexico over Mexico's producer price), which indicates that
when a country increases its price as a proportion to Mexico's domestic price, then imports
by the specific country are adversely affected. In addition, it appears that private
consumption and a country's global chocolate exports share are the only elastic variables
(i.e. their coefficients are larger than 1.0) and therefore, the imports demanded are most
165
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sensitive with these two variables than the remaining ones. This means that small
movements in private consumption or the share of the global chocolate trade can have a
more severe impact on the chocolate imports demanded by Mexico than a movement in
the price ratio (for example).
Step 5
Economic value forecasting
The most suitable import demand equation identified in step 4 was used to estimate the
economic value of UK exports to Mexico in the case of reduction or complete removal of
tariffs applied on EU chocolate imports.
The economic value for UK exports was calculated for 2016, assuming that as part of the
FTA it will take 2-3 years for UK/EU trade negotiations to lead in the removal of trade
barriers and a short period during which exports will be ramped up. The forecast was
calculated in US$ and then converted to GBP using forecast exchange rates.
Before forecasting for the value of imports in 2016, it was necessary to forecast the values
of the explanatory variables involved to input them in the import demand equation. For
some of them, the forecast values were publicly available, but for others separate
regression analyses had to be run or assumptions had to be made to estimate their value
in 2016.
A scenario analysis was undertaken on some of the variables, assuming that the previous
years' trend will continue (base scenario), whilst high and low case scenarios were also
modelled. Please refer to tables D.4-D.6 for the assumptions made at this stage of the
analysis.
Table D.4.
Explanatory variable
Tariff rate on UK/EU
imports
Mexico's total private
consumption
Exporting country's global
180690 chocolate exports
as a % of world trade of
180690 chocolate
Share of UK's total
exports to Mexico as % of
total UK's global exports
UK's wholesale price to
Mexico of 180690
Mexico's chocolate
producer price (indexed)
Assumptions made for forecasting the parameters used in
the import demand equation
Value forecast for Methodology
2016 under Base
scenario
10%
$610,177,319,832
3.500%
0.336%
$5.16 per kg
69.75
The base case scenario assumes a 16.9% reduction in tariff rates from
26.9% to 10% in 2016. This compares to 0% that competing countries
such as USA, Canada, Chile and Argentina are currently subject to
Made use of the Economist Intelligence Unit's forecasts for Mexico's
private consumption (in constant terms in Pesos) and the forecast
USD/MXN exchange rate by 2016. The 2011-2016 growth rate forecast
in USD terms was applied to Mexico's private consumption that the
regression used from World Bank (also in constant terms)
The UK has been losing share in the global trade of 180690 chocolate.
However, in recent years (2010 & 2011) it has demonstrated resilience and
therefore the base scenario takes the average of these two years and carries
it forward to 2016
Mexico's share of total trade for the UK has varied little since 2000 and has
fluctuated between 0.302% and 0.379%. As such, the Base scenario took
the 5-year average (2007-2011) whereby Mexico's share of trade has
continued fluctuating
Ran a multiple regression between UK's chocolate price to the world and
world price of raw sugar and cocoa beans and obtained a significant
relationship
In order to forecast UK's price in 2016, made use of the forecasts for the
price of sugar provided by FAO/OECD. However, for cocoa, futures'
prices were available only up to 2014. Using the futures' prices for sugar
(with which cocoa had a similar price behaviour during 2011-2014),
forecast the price of cocoa in 2015 and made the assumption that the 2016
price of cocoa will be the same as in 2015
However, it is worth noting that the price at which a country exports its
products and the quantities imported by another country are in reality
linked and inter-dependent
Ran a linear regression between Mexico's producer price and the price of
cocoa beans. However, similarly to above, futures' price for cocoa beans
were available up to 2014 and therefore forecast their price up to 2015
© 2013 Grant Thornton UK LLP. All rights reserved.
166
Explanatory variable
Value forecast for Methodology
2016 under Base
scenario
using the sugar futures' price changes for 2015 (with which cocoa had a
similar price behaviour during 2011-2014). Assumed that cocoa's 2016
price will be same to 2015
Ratio of UK's price to
Mexico over Mexico's
producer price (with tariffs
built in the prices)
Table D.5.
Explanatory variable
Tariff rate on UK/EU
imports
Mexico's total private
consumption
0.081
Added to UK's price forecast above the tariff rate for 2016 and divided it
with Mexico's indexed producer price above
Forecasting assumptions for High scenario
Value forecast for Methodology
2016 under High
scenario
0%
$610,177,319,832
Assumes complete elimination of tariffs
Made use of the Economist Intelligence Unit's forecasts for Mexico's
private consumption (in constant terms in Pesos) and the forecast
USD/MXN exchange rate by 2016. The 2011-2016 growth rate forecast
in USD terms was applied to Mexico's private consumption that the
regression used from World Bank (also in constant terms)
Exporting country's
global 180690 chocolate
exports as a % of world
trade of 180690
chocolate
3.915%
The UK has been losing share in the global trade of 180690 chocolate.
The scenario takes the historic average since 2007
Share of UK's total
exports to Mexico as %
of total UK's global
exports
0.379%
Mexico's share of total trade for the UK has varied little since 2000 and
has fluctuated between 0.302% and 0.379%. The scenario takes the
highest figure of the past decade
UK's wholesale price to
Mexico of 180690
$5.16 per kg
Ran a multiple regression between UK's chocolate price to the world
and world price of raw sugar and cocoa beans and obtained a significant
relationship.
In order to forecast UK's price in 2016, made use of the forecasts for
the price of sugar provided by FAO/OECD. However, for cocoa,
futures' prices were available only up to 2014. Using the futures' prices
for sugar (with which cocoa had a similar price behaviour during 20112014), forecast the price of cocoa in 2015 and made the assumption that
the 2016 price of cocoa will be the same as in 2015.
However, it is worth noting that the price at which a country exports its
products and the quantities imported by another country are in reality
linked and inter-dependent
Mexico's chocolate
producer price (indexed)
90.73
Equal to historic highs levels of 2011
Ratio of UK's price to
Mexico over Mexico's
producer price (with
tariffs built in the prices)
0.057
Added to UK's price forecast above the tariff rate for 2016 and divided
it with Mexico's indexed producer price above
167
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Table D.6.
Explanatory variable
Tariff rate on UK/EU
imports
Mexico's total private
consumption
Forecasting assumptions for Low scenario
Value forecast for Methodology
2016 under Low
scenario
26.9%
$610,177,319,832
Assumes tariffs stay at same level with 2011
Made use of the Economist Intelligence Unit's forecasts for Mexico's
private consumption (in constant terms in Pesos) and the forecast
USD/MXN exchange rate by 2016. The 2011-2016 growth rate forecast
in USD terms was applied to Mexico's private consumption that the
regression used from World Bank (also in constant terms)
Exporting country's
global 180690 chocolate
exports as a % of world
trade of 180690
chocolate
2.552%
Takes the negative CAGR since 2007 and applies it until 2016
Share of UK's total
exports to Mexico as %
of total UK's global
exports
0.302%
Mexico's share of total trade for the UK has varied little since 2000 and
has fluctuated between 0.302% and 0.379%. The scenario takes the
lowest figure of the past decade
UK's wholesale price to
Mexico of 180690
$6.19 per kg
Equal to historic high levels of UK world export price of chocolate in
2011. However, it is worth noting that the price at which a country
exports its products and the quantities imported by another country are
in reality linked and inter-dependent
Mexico's chocolate
producer price (indexed)
66.19
Followed same approach as in Base case. However, assumed price of
cocoa in 2016 is at the 2014 levels, which is below the 2015 levels
forecast in Base case above.
Ratio of UK's price to
Mexico over Mexico's
producer price (with
tariffs built in the prices)
0.119
Added to UK's price forecast above the tariff rate for 2016 and divided
it with Mexico's indexed producer price above
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168
E. Estimating the value of UK bakers' wares and biscuits
exports to Mexico
Step 1
Parameters and benchmark countries selection
In order to obtain the most detailed and relevant results, the product shortlisted at the end
of Chapter 6 ('1905 bread, biscuits, wafers, cakes and pastries') was decomposed at the 6code HS level to understand the exact sub-product category that Mexico is importing.
Given the wide category of food products covered by the 1905 products, this enabled the
identification of the specific opportunity for the UK:

190590: Communion wafers, empty cachets for pharmaceutical use & similar products
& bakers' wares not elsewhere specified (67.8% of total 1905 Mexican imports
in 2011);

190531: Sweet biscuits (16.5% of total 1905 Mexican imports in 2011);

190532: Waffles and wafers (10.5% of total 1905 Mexican imports in 2011); and

190540: Rusks, toasted bread and similar toasted products (5.0% of total 1905 Mexican
imports in 2011).
Given that the 190590 category also appeared to be rather broad, it was further
decomposed to better understand what goods Mexico imports:

19059099: Bakers wares' products (100% of total 1905 Mexican imports in 2011).
It is worth noting that the UK's world 1905 exports consist of:

190590: Communion wafers, empty cachets for pharmaceutical use & similar products
& bakers' wares not elsewhere specified (49% of total 1905 UK exports in 2011);

190531: Sweet biscuits (38% of total 1905 UK exports in 2011); and

190532: Waffles and wafers (8% of total 1905 UK exports in 2011).
The categorisation of UK exports at the 8-code HS level is different to Mexico's, so it is
not easy to cross reference accurately the 19059099 code used by Mexico. However, UK's
world 190590 exports are almost exclusively bakers' wares' related rather than related to
communion wafers or cachets for pharmaceutical use:

19059060: fruit tarts, currant bread, panettone, meringues, Christmas stollen, croissants
and other bakers' wares with added sweetener (excl. crispbread, gingerbread and the
like, sweet biscuits, waffles and wafers and rusks) (28% of total 190590 UK exports
in 2011);

19059090: pizzas, quiches and other unsweetened bakers' wares (excl. crispbread,
gingerbread and the like, sweet biscuits, waffles and wafers, rusks and similar toasted
products, bread, communion wafers, empty cachets for pharmaceutical use) (26% of
total 190590 UK exports in 2011); and

19059030: bread, not containing added honey, eggs, cheese or fruit, whether or not
containing in the dry state <= 5% by weight of either sugars or fats (26% of total
190590 UK exports in 2011).
Given the wide range of products covered by 1905, it was decided to evaluate the
opportunity for the UK at the 4-code HS level rather than the 6-code level as it was done
with the rest of the products in Chapter 7.
169
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Therefore, the import demand equation was used to estimate the value of UK 1905
exports to Mexico hereby referred to as 'bakers' wares and biscuits' assuming tariff barriers
would be reduced or removed completely. This is because tariffs are the main trade
barriers in the case of 1905 UK exports to Mexico.
In the case of bakers' wares and biscuits to Mexico, the UK has been exporting very small
values during 1992-2011 (during when trade data is publically available for 1905), but as
explained further below, UK's exports to Mexico were disregarded from the analysis. This
was because at small trade values there is a higher risk that the volumes recorded and
reported are not reliable enough, therefore distorting significantly the average prices
calculated for UK exports to Mexico. In the case of bakers' wares and biscuits to Mexico,
when analysing trade, USA, Italy, Spain, Indonesia and Canada were revealed as the major
exporters to Mexico historically. Altogether, these five countries accounted for 90% of
Mexico's 1905 imports in 2012. As such, the analysis captured Spain and Italy, two EU
nations who face similar trade barriers with the UK. Therefore, in step 2, the data
collection and processing exercise includes data on USA, Italy, Spain, Indonesia, Canada
and the UK.
Step 2
Data collection
In order to estimate the most appropriate import demand equation to estimate UK bakers'
wares and biscuits exports to Mexico, a data collection exercise was undertaken, namely
sourcing the parameters/variables that were deemed necessary as inputs in the regression
analysis. Most of the data collected spanned the 1992-2011 period, mainly because data
across the different parameters investigated in the regression is not available prior to 1992.
The data collected was on an annual basis because a lot of the data incorporated in the
analysis is not reported on a quarterly or monthly basis. As Defra's timeline is short-tomedium term, forecasts were collected (where available) up to 2016. More details on
forecasting the parameters is provided in step 5.
As mentioned in the literature review, demand is broadly driven by income levels and the
relative import price. Therefore, the data collected for this project includes parameters that
exert an impact on income levels in Mexico and price of bakers' wares and biscuits:

With regards to income, GDP is the generic income parameter used in macroeconomic
studies. In this case, a more disaggregated figure of the GDP was used by subtracting
exports from the GDP to make it more relevant to the domestic income level of the
Mexican population. However, given that this project accounts for agri-food products,
GDP components, such as private consumption, were also investigated as they were
considered more appropriate proxies for income levels of the population in the target
market; and

As regards price, a variety of prices were collected to account for Mexico's domestic
prices, the price of UK imports to Mexico vs. competing countries and the producers'
price for wheat in Mexico. Average retail prices for bakers' wares and biscuits would
have been preferable to wheat's producers' price, but they were not available (especially
given the wide range of products covered in the category). However, as per
FAO/OECD, Mexico produces 60% of the wheat it consumes and wheat is the key
ingredient used in the production of bakers' wares and biscuits products. It is worth
noting that wheat alone may not be able to fully capture movements in the retail price
of processed goods, such as bakers' wares and biscuits, which also depend on other
inputs (e.g. labour costs, energy costs). For the purpose of this exercise, Mexico's
wheat producer price alone is used to capture movements in the domestic prices for
bakers' wares and biscuits and therefore, relative price movements as the import
demand equation commands.
© 2013 Grant Thornton UK LLP. All rights reserved.
170
In addition, trade/import data was collected together with the tariff measures applied by
Mexico against the UK and comparison countries over the 1992-2011 review period.
Overall, data was collected on a number of variables across four major categories that were
considered to explain the behaviour of imports' demand: trade/import data, domestic
market size/income, prices and trade barriers.
In terms of trade barriers, the focus was primarily on the tariffs imposed on imports from
the UK/EU. Tariff levels for EU imports were at 14.2%, which is not the case with some
of the competing countries whose trade agreements with Mexico have eliminated tariffs
from their 1905 exports. It is worth noting that on 1997 EU and Mexico signed an FTA
which came into force on 2000. Even though the FTA has led to the removal of trade
barriers horizontally and across many product categories, the tariffs for 1905 continue to
position EU nations at a disadvantage when compared with other nations covered in this
analysis. No other particular trade barriers or NTMs were identified with regards to bakers'
wares and biscuits trade with Mexico during the period investigated.
The table below includes the most relevant parameters collected and tested. Some of the
parameters shown below were not actually used in the regression analysis stage but were
collected for forecasting purposes as shown in Step 5.
Table E.1.
Parameter
type
Trade data
Market
size/income
Price
Trade
barriers
Step 3
Parameters collected
Category
Time series Country coverage
Source
Exports of 1905 to Mexico and the
World in volume and value terms
1992-2011
Mexico, UK, USA, Italy,
Spain, Indonesia,
Canada
Trade Map,
Comtrade
Mexico GDP and total worldwide
exports
1992-2016
Mexico
Mexico total private consumption
1992-2016
Mexico
Mexico wheat production and
consumption in volume terms
1992-2016
Mexico
World Bank,
Economist
Intelligence Unit
World Bank,
Economist
Intelligence Unit
FAO/OECD
Wholesale price of 1905 to Mexico by
exporting country
1992-2011
UK, USA, Italy, Spain,
Indonesia, Canada
Trade Map,
Comtrade
Wholesale price of 1905 to the World
by exporting country
1992-2011
UK, USA, Italy, Spain,
Indonesia, Canada
Trade Map,
Comtrade
Producer price of wheat for the World,
EU, USA, Mexico and Canada
1992-2016
World, Mexico, EU,
USA, Canada
FAO/OECD
Exchange rate for Euro, UK Sterling,
Canadian Dollar and Mexican Peso in
US Dollar terms
1992-2016
Mexico, UK, USA,
Canada, EU
Economist
Intelligence Unit
Tariff rates
1997-2016
UK, USA, Italy, Spain,
Indonesia, Canada
Trade Map, WTO,
TRAINS and trade
press
Mexico, UK, USA, Italy,
Spain, Indonesia,
Canada
Desktop research
Shipping route distance between
Mexico and each country's major port
N/A
Data processing
The data collected above was further processed and adjusted to make it relevant to the
current project (the specific effort of evaluating the opportunity for bakers' wares and
biscuits in Mexico) and the methodology proposed (running a log linear regression to
identify the relevant import demand equation).
171
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The changes to the raw data collected and the new variables created were decided upon
following a number of iterations and trial tests in order to enhance the regression and
increase the robustness of the forecasts. These changes took place for a number
of reasons:

The team tried to minimise the number of variables used in the regression, but at the
same time capture as much information as possible for the regression to be robust;
 e.g. tariffs imposed by Mexico on imports were tested in the regression both as a
stand-alone variable and also by incorporating them in the average import prices
from each country individually; and

It was necessary to collect additional data on parameters that would indicate the
differing trade relationships each country has with Mexico throughout time (e.g. an
index of bilateral trade across manufacturing sectors between each comparison country
and Mexico).
The data processing that was undertaken to value the opportunity for bakers' wares and
biscuits to Mexico is shortly explained in Table E.2 below. Overall, it was decided to
remove the observations for the UK exports due to significant variances noticed in the
average export price, which may be attributed to small trade values and potentially
unreliable volume figures reported (which tends to be the case for small value trades).
Table E.2.
Parameter
type
Trade data
Data processing
Category
Time Country
series coverage
Methodology
Global market share of
country's exports of 1905
19922011
UK, USA,
Italy, Spain,
Indonesia,
Canada
Calculated each country's global exports of 1905
as a % of total global trade of 1905 to help explain
the historic levels of imports to Mexico
Total trade (excluding
services) between
exporting countries and
Mexico
19922011
Mexico, UK,
USA, Italy,
Spain,
Indonesia,
Canada
Calculated each country's total trade with Mexico
as a % of the country's total global trade to help
explain the country's trade relationships with
Mexico
Wholesale price to
Mexico with tariffs
added
19922011
UK, USA,
Italy, Spain,
Indonesia,
Canada
Competition's import
weighted average prices
for 1905
19922011
UK, USA,
Italy, Spain,
Indonesia,
Canada
The tariffs were tested in the regressions in two
different ways; as a stand-alone variable for each
country separately and by adding them on top of
the wholesale price at which each country
exported bakers' wares and biscuits in Mexico. In
the latter case, separate price ratios were created
that accounted for the exporting prices including
tariffs
Reflects the importing competition's weighted
average price by the value of imports. Derived the
import weighted average price of 1905 exports to
Mexico for each year and each country but
excluding the imports of the specific country
Competition's import
weighted average prices
over Mexico's producers'
prices
Wholesale price to
Mexico over Mexico
producers' prices
19922011
Wholesale price to
Mexico over
competition's import
weighted average prices
19922011
UK, USA,
Italy, Spain,
Indonesia,
Canada
UK, USA,
Italy, Spain,
Indonesia,
Canada
UK, USA,
Italy, Spain,
Indonesia,
Canada
Price
19922011
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Divided the two parameters
Divided the two parameters
Divided the two parameters
172
Parameter
type
Category
Tariff rates
Trade
barriers
Time Country
series coverage
19922011
UK, USA,
Italy, Spain,
Indonesia,
Canada
Methodology
The various databases were contradicting each
other in terms of the tariffs output for bakers'
wares and biscuits across countries and periods.
However, the fact was that USA and Canada
maintained preferred rates throughout the whole
period compared to EU and Indonesia. Tariffs
were not available during 1992-1996 and rates
were estimated by assuming they were equal to
1997
The data outlined above reflects the various iterations the project team performed, but
only a number of these variables were shortlisted for running the import demand equation
regression analysis.
Step 4
Regression analysis
The PCSE estimator was selected for the regression, which calculates panel-corrected
standard error estimates for linear cross-sectional time-series models. When computing the
standard errors and the variance-covariance estimates, this regressor assumes that the
disturbances are, by default, heteroskedastic and contemporaneously correlated across
panels. The PCSE estimator does not correct for autocorrelation, but autocorrelation was
verified not being an issue in this sample using the Wooldridge test for autocorrelation in
panel data (i.e. the null hypothesis of no first-order autocorrelation could not be rejected at
the usual significance level).
The choice of regressors follows closely what has been done with the other products.
However, in this case, the price terms include both a price ratio of wholesale import price
to Mexico's producer price of wheat and a separate variable for the competition's wholesale
import prices. The combination of one ratio and one price allows us to include the
maximum amount of information in the regressors while preserving low standard errors
for each of the regressors. The results of this regression are reassuring. The level of overall
fit measured by the R-squared (80%) and the low standard errors of the coefficient
estimates, together with the expected signs for the coefficients indicate that this regression
model fits the data well and is therefore a good basis for forecasting.
173
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Table E.3.
Equation chosen to forecast UK bakers' wares and biscuits
exports to Mexico
Linear regression, correlated panels corrected standard errors (PCSEs)
Group variable: country
Number of obs =
Time variable: year
Number of groups =
Panels: correlated (unbalanced)
Obs per group:
96
5
Autocorrelation: no autocorrelation
min =
18
Sigma computed by casewise selection
avg =
19
max =
20
Estimated covariances
= 15
Estimated autocorrelations
=0
R-squared
= 0.8052
Estimated coefficients
=6
Wald chi2(5)
= 852.04
Prob > chi2
=0
Panel-corrected
imp_val_p
Std. Err
t
P>|t|
Mexico's total private
consumption
2.397
0.579
4.140
0
1.263164
3.530928
Share of exporting country's
trade with Mexico as % of total
country's global exports
0.462
0.125
3.690
0
.2163762
.7071396
Exporting country's global 1905
exports as a % of world trade of
1905
1.156
0.119
9.730
0
.9228259
1.388182
Ratio - Wholesale price to
Mexico of 1905 (post tariffs)
over Mexico's producer price of
wheat
(0.555)
0.243
(2.280)
0.022
-1.031325
-.0788962
Competition's import weighted
average wholesale price of 1905
to Mexico (post-tariff)
1.495
0.429
3.480
0
.6540245
2.336953
(53.416)
15.181
(3.520)
0
-83.1709
-23.6618
Constant coefficient
Coef.
[95% Conf. Interval]
As discussed above, the coefficients of the parameters above have the expected signs. All
parameters have a positive sign except for the price ratio (i.e. the wholesale price at which a
country exports 1905 to Mexico over Mexico's wheat producer price), which indicates that
when a country increases its price as a proportion to Mexico's domestic price, then imports
by the specific country are adversely affected. In addition, it appears that Mexico's private
consumption, competition's export prices and the share of global 1905 exports are elastic
variables (i.e. their coefficients are larger than 1.0) and therefore, the imports demanded are
most sensitive with these three variables than the remaining ones. This means that small
movements in competition's prices or Mexico's private consumption can have a more
severe impact on the 1905 imports demanded by Mexico than a movement in the overall
trade ties with Mexico (for example).
Step 5
Economic value forecasting
The most suitable import demand equation identified in step 4 was used to estimate the
economic value of UK exports to Mexico in the case of reduction or complete removal of
tariffs applied on EU bakers' wares and biscuits imports.
The economic value for UK exports was calculated for 2016, assuming that it will take 2-3
years for UK/EU trade negotiations to lead in the removal of trade barriers and a short
period during which exports will be ramped up. The forecast was calculated in US$ and
then converted to GBP using forecast exchange rates.
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174
Before forecasting for the value of imports in 2016, it was necessary to forecast the values
of the explanatory variables involved to input them in the import demand equation. For
some of them, the forecast values were publicly available, but for others separate
regression analyses had to be run or assumptions had to be made to estimate their value
in 2016.
A scenario analysis was undertaken on some of the variables, assuming that the previous
years' trend will continue (Base scenario), whilst high and low case scenarios were also
modelled. Please refer to tables E.4-E.6 below for the assumptions made at this stage of
the analysis.
Table E.4.
Assumptions made for forecasting the parameters used in
the import demand equation
Explanatory variable
Value forecast for Methodology
2016 under Base
scenario
Tariff rate on UK/EU
imports
UK/EU: 5%
USA & Canada:
0%
Indonesia: 14.2%
The base case scenario assumes a 9.2% reduction in tariff rates from
14.2% to 5% in 2016 for the EU. This compares to 0% that competing
countries such as USA & Canada are already subject to. It is assumed
that Indonesia (who accounts for 2% of total Mexico's 1905 imports)
will not have equal bargaining power with EU and will not manage to
negotiate any reduction in the tariffs
Mexico's total private
consumption
$610,177,319,832
Made use of the Economist Intelligence Unit's forecasts for Mexico's
private consumption (in constant terms in Pesos) and the forecast
USD/MXN exchange rate by 2016. The 2011-2016 growth rate forecast
in USD terms was applied to Mexico's private consumption that the
regression used from World Bank (also in constant terms)
Exporting country's
global 1905 exports as a
% of world trade of
1905
4.310%
The UK has been losing share in the global trade of 1905 bakers' wares
and biscuits. Assumes the historic decline of the world share will stop
and that UK's share in 2016 will equal the historic low of 2011
Share of UK's total
exports to Mexico as %
of total UK's global
exports
0.336%
Mexico's share of total trade for the UK has varied little since 2000 and
has fluctuated between 0.302% and 0.379%. As such, the Base scenario
took the 5-year average (2007-2011) whereby Mexico's share of trade
has continued fluctuating
UK's wholesale price to
Mexico of 1905 (pretariff)
$3.03 per kg
By using the OECD/FAO forecast for EU's wheat producer price for
2016 in Euro terms and the forecasts by EIU on the EUR/USD
exchange rate, estimated EU's producer prices in 2016
Then, ran a multiple linear regression analysis between UK's average
world export prices of 1905 against World price of wheat (historics and
forecasts also provided by OECD/FAO in US $ terms) and EU's
producer price of wheat and estimated average UK's price to the world
of 1905 in 2016
To identify UK's price to Mexico, estimated the import weighted
average premium applied on the price of the competing EU countries'
(i.e. Italy and Spain) 1905 exports to Mexico compared to their world
1905 export average prices. Assumed that the 2011 premium will be the
same in 2016
However, it is worth noting that the price at which a country exports its
products and the quantities imported by another country are in reality
linked and inter-dependent
$193.17 per tonne
Forecast was provided in Mexican Pesos terms by OECD/FAO. Using
EIU's forecasts for the exchange rate of MXN/USD, estimated
Mexico's producer price in US $ terms
Mexico's wheat
producer price
175
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Explanatory variable
Value forecast for Methodology
2016 under Base
scenario
Competition's import
weighted average prices
(pre-tariff)
$2.58 per kg
Ran linear regressions between each competing country's wheat
producer prices (historics and forecasts provided by OECD/FAO in
local currency terms and used EIU's exchange rate forecasts to estimate
forecasts in US $ terms) and the country's 1905 export price to Mexico
to estimate their export price in 2016
Used a weighted average price for Spain and Italy given that the
producer prices were provided for EU as a whole. OECD/FAO did
not have any data on Indonesia's producer prices, and its export price
for 2016 was assumed equal to USA's given that the two countries have
been exporting at similar prices since 2006 (Indonesia currently
accounts for 2% of Mexico's 1905 imports)
Assumed that Mexico's 2011 import market share for each country will
be sustained in 2016 and therefore calculated an import weighted
average price for the competition
However, it is worth noting that the price at which a country exports its
products and the quantities imported by another country are in reality
linked and inter-dependent
Competition's import
weighted average prices
(post-tariff)
$2.62 per kg
Using figures above
Ratio of UK's price to
Mexico over Mexico's
producer price (with
tariffs built in the prices)
Table E.5.
Explanatory variable
Tariff rate on UK/EU
imports
Mexico's total private
consumption
0.016
Added to UK's price forecast above the tariff rate for 2016 and divided
it with Mexico's indexed producer price above
Forecasting assumptions for High scenario
Value forecast for 2016 Methodology
under High scenario
UK/EU: 0%
USA & Canada: 0%
Indonesia: 14.2%
The high scenario assumes tariffs will be eliminated for the EU by
2016. It is assumed that Indonesia (who accounts for 2% of total
Mexico's 1905 imports) will not have equal bargaining power with
EU and will not manage to negotiate any reduction in the tariffs
$610,177,319,832
Made use of the Economist Intelligence Unit's forecasts for
Mexico's private consumption (in constant terms in Pesos) and the
forecast USD/MXN exchange rate by 2016. The 2011-2016
growth rate forecast in USD terms was applied to Mexico's private
consumption that the regression used from World Bank (also in
constant terms)
Exporting country's
global 1905 exports as a
% of world trade of
1905
4.710%
The UK has been losing share in the global trade of 1905 bakers'
wares and biscuits. The scenario accounts for the 5-year average
between 2007-2011
Share of UK's total
exports to Mexico as %
of total UK's global
exports
0.379%
Mexico's share of total trade for the UK has varied little since 2000
and has fluctuated between 0.302% and 0.379%. As such, the High
scenario takes the highest figure of the past decade
UK's wholesale price to
Mexico of 1905 (pretariff)
$3.03 per kg
By using the OECD/FAO forecast for EU's wheat producer price
for 2016 in Euro terms and the forecasts by EIU on the
EUR/USD exchange rate, estimated EU's producer prices in 2016
Then, ran a multiple linear regression analysis between UK's
average world export prices of 1905 against World price of wheat
(historics and forecasts also provided by OECD/FAO in US $
terms) and EU's producer price of wheat and estimated average
UK's price to the world of 1905 in 2016
To identify UK's price to Mexico, estimated the import weighted
average premium applied on the price of the competing EU
countries' (i.e. Italy and Spain) 1905 exports to Mexico compared
to their world 1905 export average prices. Assumed that the 2011
premium will be the same in 2016
However, it is worth noting that the price at which a country
exports its products and the quantities imported by another country
are in reality linked and inter-dependent
Mexico's wheat
$193.17 per tonne
Forecast was provided in Mexican Pesos terms by OECD/FAO.
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176
Explanatory variable
producer price
Value forecast for 2016 Methodology
under High scenario
Using EIU's forecasts for the exchange rate of MXN/USD,
estimated Mexico's producer price in US $ terms
Competition's import
weighted average prices
(pre-tariff)
$2.58 per kg
Ran linear regressions between each competing country's wheat
producer prices (historics and forecasts provided by OECD/FAO
in local currency terms and used EIU's exchange rate forecasts to
estimate forecasts in US $ terms) and the country's 1905 export
price to Mexico to estimate their export price in 2016
Used a weighted average price for Spain and Italy given that the
producer prices were provided for EU as a whole. OECD/FAO
did not have any data on Indonesia's producer prices, and its export
price for 2016 was assumed equal to USA's given that the two
countries have been exporting at similar prices since 2006
(Indonesia currently accounts for 2% of Mexico's 1905 imports)
Assumed that Mexico's 2011 import market share for each country
will be sustained in 2016 and therefore calculated an import
weighted average price for the competition
However, it is worth noting that the price at which a country
exports its products and the quantities imported by another country
are in reality linked and inter-dependent
Competition's import
weighted average prices
(post-tariff)
$2.59 per kg
Using figures above
Ratio of UK's price to
Mexico over Mexico's
producer price (with
tariffs built in the
prices)
177
0.016
Added to UK's price forecast above the tariff rate for 2016 and
divided it with Mexico's indexed producer price above
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Table E.6.
Explanatory variable
Tariff rate on UK/EU
imports
Forecasting assumptions for Low scenario
Value forecast for 2016 Methodology
under Low scenario
UK/EU: 10%
USA & Canada: 0%
Indonesia: 14.2%
The low scenario assumes tariffs will stand at 10% for the EU by
2016. It is assumed that Indonesia (who accounts for 2% of total
Mexico's 1905 imports) will not have equal bargaining power with
EU and will not manage to negotiate any reduction in the tariffs
$610,177,319,832
Made use of the Economist Intelligence Unit's forecasts for
Mexico's private consumption (in constant terms in Pesos) and the
forecast USD/MXN exchange rate by 2016. The 2011-2016
growth rate forecast in USD terms was applied to Mexico's private
consumption that the regression used from World Bank (also in
constant terms)
Exporting country's
global 1905 exports as a
% of world trade of
1905
3.547%
The UK has been losing share in the global trade of 1905 bakers'
wares and biscuits. The scenario takes the 5-year CAGR since 2007
and projects it to 2016 assuming the declining trend will continue
Share of UK's total
exports to Mexico as %
of total UK's global
exports
0.302%
Mexico's share of total trade for the UK has varied little since 2000
and has fluctuated between 0.302% and 0.379%. As such, the low
scenario takes the 5-year CAGR since 2007 and projects it to 2016
assuming the declining trend will continue
UK's wholesale price to
Mexico of 1905 (pretariff)
$3.36 per kg
By using the OECD/FAO forecast for EU's wheat producer price
for 2016 in Euro terms and the forecasts by EIU on the
EUR/USD exchange rate, estimated EU's producer prices in 2016
Then, ran a multiple linear regression analysis between UK's
average world export prices of 1905 against World price of wheat
(historics and forecasts also provided by OECD/FAO in US $
terms) and EU's producer price of wheat and estimated average
UK's price to the world of 1905 in 2016
To identify UK's price to Mexico, estimated the import weighted
average premium applied on the price of the competing EU
countries' (i.e. Italy and Spain) 1905 exports to Mexico compared
to their world 1905 export average prices. Assumed that the 2009
premium (which was the highest during the past 10 years) will be
the same in 2016
However, it is worth noting that the price at which a country
exports its products and the quantities imported by another country
are in reality linked and inter-dependent
Mexico's total private
consumption
Mexico's wheat
producer price
$193.17 per tonne
Forecast was provided in Mexican Pesos terms by OECD/FAO.
Using EIU's forecasts for the exchange rate of MXN/USD,
estimated Mexico's producer price in US $ terms
Competition's import
weighted average prices
(pre-tariff)
$2.58 per kg
Ran linear regressions between each competing country's wheat
producer prices (historics and forecasts provided by OECD/FAO
in local currency terms and used EIU's exchange rate forecasts to
estimate forecasts in US $ terms) and the country's 1905 export
price to Mexico to estimate their export price in 2016
Used a weighted average price for Spain and Italy given that the
producer prices were provided for EU as a whole. OECD/FAO
did not have any data on Indonesia's producer prices, and its export
price for 2016 was assumed equal to USA's given that the two
countries have been exporting at similar prices since 2006
(Indonesia currently accounts for 2% of Mexico's 1905 imports)
Assumed that Mexico's 2011 import market share for each country
will be sustained in 2016 and therefore calculated an import
weighted average price for the competition
However, it is worth noting that the price at which a country
exports its products and the quantities imported by another country
are in reality linked and inter-dependent
Competition's import
weighted average prices
(post-tariff)
$2.64 per kg
Using figures above
Ratio of UK's price to
Mexico over Mexico's
producer price (with
tariffs built in the
prices)
0.019
Added to UK's price forecast above the tariff rate for 2016 and
divided it with Mexico's indexed producer price above
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178
F. Estimating the value of UK beef to Japan
Step 1
Parameters and benchmark countries selection
In order to obtain the most detailed and relevant results, the product shortlisted at the end
of Chapter 6 (0201 'meat of bovine animals, fresh or chilled') was decomposed at the 6code HS level to identify sub-product categories imported by Japan. Given the wide
category of food products covered by beef products, this enabled the focus and selection
of the specific opportunity for the UK:

020130: Bovine cuts boneless, fresh or chilled (100% of total 0201 Japanese imports
in 2011).
020130 also accounts for 55% of the UK's 0201 world exports. In order to ensure a
broader view, the value of Japan's frozen beef imports (i.e. 0202 'meat of bovine animals,
frozen') was also investigated. 0202 Japanese imports came up to c.$1.2bn in 2011. Given
that the UK does not appear to have a comparative advantage in frozen beef (as shown in
Chapter 2), that Japan imports more fresh or chilled beef (c.$1.5bn in 2011) and as fresh or
chilled beef can be transported long distances, the study investigated the opportunity for
020130 beef exports to Japan.
The main barrier towards exporting beef to Japan is the ban that Japan has imposed on the
UK following sanitary concerns after the Bovine Spongiform Encephalopathy (BSE)
outbreak. Japan had imposed similar restrictions to other EU countries, but in January
2013 it announced that it will lift the ban for exports by France and the Netherlands of
beef from cattle younger than 30 months old. Based on data from the UK and USA, it is
understood that cattle younger than 30 months old reflects c.80% and c.90% of the total
cattle capacity respectively for the two countries. Furthermore, Japan continues imposing
relatively high tariffs on beef imports of 38.5%. However, the tariff rates apply on all major
exporting nations (except for Mexico who enjoys 0% tariff, but only accounted for 0.7% of
Japan's total beef imports in 2011) and have been at the same level since 2000. Therefore,
the import demand equation was used to estimate the value of UK 020130 exports to
Japan assuming the ban on UK beef would be removed, that UK producers would be
allowed to export beef from cattle younger than 30 months old by 2016, similarly to
France and Netherlands (the same restriction also applies to USA and Canada who are
major exporters of beef to Japan) and that tariff rates would stay at the same levels with the
period from 2000-2013. Based on desktop research and by investigating the average import
prices by Japan (compared to the world average import prices), it is understood that Japan
imports high-quality beef cuts, which presents a good opportunity for UK producers.
The analysis was carried out by analysing the behaviour of imports from competing
countries. In the case of beef to Japan during 1998-2011 (during when data across all
parameters of interest was publically available for 020130), the UK has not been exporting
any quantities because of the ban in place. In the case of beef to Japan, when analysing
trade, Australia, USA, New Zealand, Canada and Mexico were revealed as the major
exporters to Japan historically. Altogether, these countries accounted for 100% of Japan's
020130 imports in 2011. The analysis did not capture any EU nations since they were all
subject to similar sanitary bans during the period under review. Therefore, in step 2, the
data collection and processing exercise includes data on Australia, USA, New Zealand,
Canada, Mexico and the UK.
Step 2
Data collection
In order to estimate the most appropriate import demand equation to estimate UK beef
exports to Japan, a data collection exercise was undertaken, namely sourcing the
parameters/variables that were deemed necessary as inputs in the regression analysis. Most
179
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of the data collected spanned the 1998-2011 period, mainly because data across certain
parameters (e.g. Japan's retail price of beef as well as the domestic beef prices for the
exporting countries) was not available 1998. The data collected was on an annual basis
because much of it incorporated in the analysis is not reported on a quarterly or monthly
basis. As Defra's timeline is short-to-medium term, forecasts were collected (where
available) up to 2016. More details on forecasting the parameters is provided in step 5.
As mentioned in the literature review, demand is broadly driven by income levels and the
relative import price. Therefore, the data collected for this project includes parameters that
exert an impact on income levels in Japan and the price of beef:

With regards to income, GDP is the generic income parameter used in macroeconomic
studies. In this case, a more disaggregated figure of the GDP was used by subtracting
exports from the GDP to make it more relevant to the domestic income level of the
Japanese population. However, given that this project accounts for agri-food products,
GDP components, such as private consumption, were also investigated as they were
considered more appropriate proxies for income levels of the population in the target
market; and

As regards price, a variety of data was collected to account for Japan's domestic prices,
the potential price of UK imports to Japan vs. competing countries and the retail price
for beef in Japan. However, as per FAO/OECD, Japan produces 40% of the beef it
consumes and, as such, the behaviour of Japan's retail prices should reflect movements
in import prices.
In addition, trade/import data was collected together with the non-tariff and tariff
measures applied by Japan against the UK and comparison countries over the 1998-2011
review period. Overall, data was collected on a number of variables across four major
categories that were considered to explain the behaviour of imports' demand: trade/import
data, domestic market size/income, prices and trade barriers.
In terms of trade barriers, the focus was primarily on the sanitary ban imposed on imports
from the UK which was recently lifted for other EU nations. France and Netherlands are
now free to export beef from cattle younger than 30 months old similarly to USA and
Canada. Out of the comparison countries, Australia, New Zealand and Mexico are not
subject to this constraint, even though it should not make a significance difference to the
level of exports (given that 80%-90% of total beef production appears to originate from
cattle younger than 30 months old in the case of UK and USA). In terms of tariffs all
countries are subject to 38.5% except for Mexico who signed an Economic Partnership
Agreement (EPA) with Japan in 2004, the first comprehensive trade agreement that Japan
signed with any country. Since then, Mexico's beef imports have been subject to 0% tariff.
It is worth noting that EU and Japan have recently announced that they are considering
entering into discussions for an FTA between the two parties which could assist with
reducing the tariff rate in the future and overall improve the trade ties between them. No
other particular trade barriers or NTMs were identified with regards to beef trade with
Japan during the period investigated.
The following table includes the most relevant parameters collected and tested. Some of
the parameters shown in the following table were not actually used in the regression
analysis stage, but were collected for forecasting purposes as shown in Step 5.
© 2013 Grant Thornton UK LLP. All rights reserved.
180
Table F.1.
Parameters collected
Parameter
type
Category
Time series Country coverage
Source
Trade data
Exports of 020130 to Japan and the
World in volume and value terms
1998-2011
Japan, UK, Australia,
USA, New Zealand,
Canada, Mexico
Trade Map,
Comtrade
Market
size/income
Japan GDP and total worldwide exports
1998-2016
Japan
World Bank,
Economist
Intelligence Unit
Japan total private consumption
1998-2016
Japan
World Bank,
Economist
Intelligence Unit
Japan beef production and
consumption in volume terms
1998-2016
Japan
FAO/OECD
Wholesale price of 020130 to Japan by
exporting country
1998-2011
UK, Australia, USA,
New Zealand, Canada,
Mexico
Trade Map,
Comtrade
Wholesale price of 020130 to the World
by exporting country
1998-2011
UK, Australia, USA,
New Zealand, Canada,
Mexico
Trade Map,
Comtrade
Retail price for beef in Japan
1998-2016
Japan
FAPRI
Domestic prices for beef (wholesale,
producer or retail prices)
1998-2016
Europe, Australia, USA,
New Zealand, Canada,
Mexico
FAPRI
Exchange rate for Yen, Euro, UK
Sterling, New Zealand Dollar,
Australian Dollar, Canadian Dollar, and
Mexican Peso in US Dollar terms
1998-2016
Japan, UK, Europe,
Australia, USA, New
Zealand, Canada,
Mexico
Economist
Intelligence Unit
Tariff rates
1998-2011
UK, Australia, USA,
New Zealand, Canada,
Mexico
Trade Map, WTO,
TRAINS and trade
press
Import ban due to sanitary concerns –
dummy variable
1998-2011
UK, USA, Canada
Trade press
Other import restrictions (i.e. accepting
imports of beef from cattle younger
than 20 months old) – dummy variable
1998-2011
UK, USA, Canada
Trade press
Shipping route distance between Japan
each country's major port
N/A
Japan, UK, Australia,
USA, New Zealand,
Canada, Mexico
Desktop research
Price
Trade
barriers
Step 3
Data processing
The data collected above was further processed and adjusted to make it relevant to the
current project (the specific effort of evaluating the opportunity for beef in Japan) and the
methodology proposed (running a log linear regression to identify the relevant import
demand equation).
The changes to the raw data collected and the new variables created were decided upon
following a number of iterations and trial tests in order to enhance the regression and
increase the robustness of the forecasts. These changes took place for a number
of reasons:

To minimise the number of variables used in the regression, but at the same time
capture as much information as possible for the regression to be robust;
 e.g. tariffs imposed by Japan on beef imports were tested in the regression both as a
stand-alone variable and also by incorporating them in the average import prices
from each country individually;
181
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
It was necessary to collect additional data on parameters that would indicate the
differing trade relationships each country has with Japan throughout time (e.g. an index
of bilateral trade across manufacturing sectors between each comparison country
and Japan);

It was necessary to identify an appropriate variable that captures the different degrees
of non-tariff import restrictions imposed by Japan on beef imports:
 The complete ban of beef imports introduced immediately after BSE outbreaks as in
the case of UK, USA and Canada;
 Importing beef from cattle younger than 20 months old which also puts significant
pressure on a certain country's imports as it may reflect only 20% of the exportable
beef capacity of a certain country, based on US trade press;
 Importing beef from cattle younger than 30 months old; and

To address the above, a number of dummy and numerical variables were designed and
tested in the model to identify the most appropriate one.
The data processing that was undertaken to value the opportunity for beef in Japan is
explained in Table F.2 below. Overall, the ban observations for USA and Canada during
2004 and 2005 and for the UK throughout the whole period were removed due to the
complications that were noticed by using multiple variables that aimed to address the
differing degrees of import restrictions imposed by Japan.
Table F.2.
Data processing
Time series Country
coverage
Methodology
Global market share
of country's exports
of 020130
1998-2011
UK, Australia,
USA, New
Zealand,
Canada, Mexico
Calculated each country's global exports of
020130 as a % of total global trade of 020130 to
help explain the historic levels of imports to Japan
Total trade
(excluding services)
between exporting
countries and Japan
1998-2011
UK, Australia,
USA, New
Zealand,
Canada, Mexico
Calculated each country's total trade with Japan as
a % of the country's total global trade to help
explain the country's trade relationships with
Japan
Wholesale price to
Japan
1998-2011
USA, Canada,
Mexico, UK
Prices to Japan for USA, Canada and Mexico
during years when they were not exporting to
Japan were estimated by running linear regressions
between world export prices by these countries
and prices to Japan. To estimate the UK prices
which has not been exporting during the period
investigated, looked into the average difference in
the price at which each competing country
exported to Japan compared to their average
world export price. Then, calculated the import
weighted average for all countries across the year
and applied it on UK's world export prices of beef
Wholesale price to
Japan with tariffs
added
1998-2011
UK, Australia,
USA, New
Zealand,
Canada, Mexico
The tariffs were tested in the regressions in two
different ways; as a stand-alone variable for each
country separately and by adding them on top of
the wholesale price at which each country
exported beef to Japan. In the latter case, separate
price ratios were created that accounted for the
exporting prices including tariffs
Competition's import
weighted average
prices for 020130
1998-2011
UK, Australia,
USA, New
Zealand,
Canada, Mexico
Reflects the importing competition's weighted
average price by the value of imports. Derived the
import weighted average price of 020130 exports
to Japan for each year and each country, but
excluding the imports of the specific country
Competition's import
weighted average
prices over Japan's
1998-2011
UK, Australia,
USA, New
Zealand,
Divided the two parameters
Parameter Category
type
Trade
data
Price
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182
Parameter Category
type
Time series Country
coverage
retail prices
Trade
barriers
Methodology
Canada, Mexico
Wholesale price to
Japan over Japan's
retail prices
1998-2011
UK, Australia,
USA, New
Zealand,
Canada, Mexico
Divided the two parameters
Wholesale price to
Japan over
competition's import
weighted average
prices
1998-2011
UK, Australia,
USA, New
Zealand,
Canada, Mexico
Divided the two parameters
Tariff rates
2009-2010
UK, Australia,
USA, New
Zealand,
Canada, Mexico
Out of the 14-year period covered in this analysis,
tariff rates were not available on the
WTO/TRAINS/Trade Map databases for two
years. In this case, the tariffs were filled in by
assuming they were similar to the following and
previous years (especially given that tariffs did not
change since 2000)
Competition's export
boost - dummy
variable
1998-2011
UK, Australia,
USA, New
Zealand,
Canada, Mexico
Following a number of efforts to account for
Japan's various import restrictions, decided to
remove the complete ban observations (for 2004
and 2005 for USA and Canada and for the whole
period for the UK) and to include this new
variable that accounts for the 20 month-old age
restriction imposed on cattle beef from USA and
Canada during 2006-2011
Contrary to the 'Other import restrictions' variable
above, which 'penalised' USA and Canada during
this period (when the relevant restriction was
imposed), this variable 'rewarded' their
competition (i.e. Australia and New Zealand) who
were not subject to these restrictions and were
therefore, able to boost their exports to Japan in
order to make up for the decline in the exports of
USA and Canada. It was sensible to make use of
this variable instead, because USA's and Canada's
world export share of beef declined as many other
countries beyond Japan followed similar measures
and the ' Global market share of country's exports
of 020130' variable was able to reflect the impact
of imposing such restrictions
On the contrary, Australia's and New Zealand's
world share of beef exports did not increase even
though their exports increased in the case of Japan
and therefore the use of a dummy variable was
deemed essential to capture this advantage they
had
Last but not least, Mexico, another rival nation to
USA and Canada, who was not subject to the 20
month-old restriction, was not captured by this
variable. The reason was that Mexico was already
trading on particularly preferential terms with
Japan since it is the only country who has been
facing 0% tariffs since 2004 (and therefore the
tariff variable is capturing effectively this
'competitive boost')
The data outlined above reflects the various iterations the project team performed, but
only a number of these variables were shortlisted for running the import demand equation
regression analysis.
183
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Step 4
Regression analysis
The estimation method is a feasible GLS regressor. GLS specifications are flexible
estimation methods that account for various patterns of correlation between the residuals:
cross-section specific heteroskedasticity, period specific heteroskedasticity,
contemporaneous covariances, and between period covariances.
The chosen regressor includes cross-section weights to correct for equation-specific
heteroskedasticity (i.e. that the variance of the residuals may be different for each country);
this method runs a two-stage regression where, in the first stage, weights are estimated in a
regression with equal weights and, in the second round, weights are applied in weighted
least squares.
The regression method takes into account and corrects for possible autoregression of
order 1 in the residuals. There was evidence of positive autoregressive residuals from a low
Durbin-Watson test statistic for the general approach. The results of the estimation
confirm the autoregressive nature of the error term with a highly significant coefficient for
the autoregression parameter.
The method also estimates White robust covariances. The White cross-section method is
robust to cross-section (contemporaneous) correlation as well as different error variances
in each cross-section.
Given all the corrections that the model includes for possible failings of the independent
and identically distributed (iid) assumptions of the model‟s error structure, given that the
final estimated coefficients are highly significant and with the expected signs, and given the
high level of fit (98% R-squared), it gives confidence that this is a robust regression to use
for the forecasting of UK exports.
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184
Table F.3.
Equation chosen to forecast UK beef exports to Japan
Dependent Variable: IMP_VAL
Method: Panel EGLS (Cross-section weights)
Date: 03/02/13 Time: 14:07
Sample (adjusted): 1999 2011
Periods included: 13
Cross-sections included: 5
Total panel (unbalanced) observations: 53
Iterate coefficients after one-step weighting matrix
White cross-section standard errors & covariance (d.f. corrected)
Convergence achieved after 20 total coefficient iterations
Variable
Constant coefficient
Coefficient
Std. Error
t-Statistic
Prob.
14.134
1.162
12.164
0
Exporting country's global beef 020130
exports as a % of world trade of beef
0.766
0.190
4.042
0.000
Competition's export boost (dummy
variable)
0.136
0.073
1.876
0.067
Competition's import-weighted wholesale
price to Japan (post-tariff)
1.018
0.295
3.454
0.001
Share of exporting country's trade with
Japan as % of total country's global
exports
0.784
0.303
2.584
0.013
Autoregressive parameter
0.910
0.040
22.474
0
Weighted Statistics
R-squared
0.988
Mean dependent var
13.525
Adjusted R-squared
0.987
S.D. dependent var
6.011
0.265
Sum squared resid
3.289
Durbin-Watson stat
1.320
S.E. of regression
F-statistic
Prob(F-statistic)
762.041
0
Unweighted Statistics
R-squared
0.979
Mean dependent var
11.379
Sum squared resid
3.684
Durbin-Watson stat
0.961
Inverted AR Roots
0.910
As discussed above, the coefficients of the parameters above have the expected signs. All
parameters have a positive sign indicating a positive relationship with imports demanded.
It appears that the competition's price is the only elastic variable (i.e. its coefficient is larger
than 1.0) and therefore the imports demanded are most sensitive with this variable than the
remaining ones. This means that small movements in the weighted average price by the
competition can have a more severe impact on the beef imports demanded by Japan than a
movement in a certain country's world beef exports share (for example).
Contrary to the valuations for the remaining five products, beef in Japan was the only
product for which no price ratio was included in the selected regression equation and a
stand-alone price parameter was used instead (in this case, the competition's import
weighted average price). Typically, when running regressions, the following price ratios
were investigated:
185
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a
Competition's import weighted average prices over Japan's retail prices;
b
Wholesale price to Japan over Japan's retail prices; and
c
Wholesale price to Japan over competition's import weighted average prices.
As it was stated, Japan only produces c.40% of the beef it consumes and as such, the
imported beef prices should reflect the movements in the domestic retail price in Japan. In
that sense, price ratio 'a)' loses its meaning in the context of the regression since its value
should be staying the same throughout time without fluctuating significantly. In addition
price ratios 'b)' and 'c)' now become similar, however none of them proved adequately
significant according to the results of the regressions run. As such, stand-alone price
variables started being tested and the competition's average import prices proved to be
most relevant and significant.
As per the literature covered in Chapter 7, the idea behind capturing price ratios is to
reflect on relative price movements. However, given that competition's average prices also
reflect on the domestic retail prices in the case of beef in Japan, it can be considered that
relative price movements are being captured by the method chosen.
In addition, contrary to the remaining valuations, Japan is the only case where the income
parameter was not captured. This was because, in the case of Japan, private consumption
and GDP levels have moved very little over the period of 1998-2011 in USD terms (both
figures appear to be 10% higher in 2011 compared to 1998 facilitated by the appreciation
of the Yen compared to the US dollar). During the same time, import levels of beef have
also not moved with 2011 levels being slightly below 1998 levels in USD terms. As such, in
the context of the regression analysis, the income parameter was treated as a secondary
constant coefficient and one was losing significance over the other. As such, in Japan's
case, it was prudent to drop income from the regression, which was thought to be captured
by the constant coefficient.
Step 5
Economic value forecasting
The most suitable import demand equation identified in step 4 was used to estimate the
economic value of UK exports to Japan in the case of removal of the sanitary ban imposed
on UK beef imports.
The economic value for UK exports was calculated for 2016, assuming that it will take 2-3
years for UK/EU trade negotiations to result in the removal of trade barriers and a short
period during which exports will be ramped up. The forecast horizon follows the recent
removal (January 2013) of the sanitary ban for beef from France and Netherlands, which
indicates that negotiations for UK beef may not take as long as currently anticipated. In
addition, EU and Japan have recently announced they are considering entering into
discussions regarding signing an FTA, which could further facilitate discussions around
UK beef. The forecast was calculated in US$ and then converted to GBP using forecast
exchange rates.
Before forecasting for the value of imports in 2016, it was necessary to forecast the values
of the explanatory variables involved to input them in the import demand equation. For
some of them, the forecast values were publicly available, but for others separate
regression analyses had to be run or assumptions had to be made to estimate their value
in 2016.
A scenario analysis was undertaken on some of the variables, assuming that the previous
years' trend will continue (base scenario), whilst high and low case scenarios were also
modelled. Please refer to tables F.4-F.6 for the assumptions made at this stage of
the analysis.
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186
Table F.4.
Explanatory variable
Tariff rate on imports
from competing
countries
Assumptions made for forecasting the parameters used in
the import demand equation
Value forecast for Methodology
2016 under Base
scenario
0% (Mexico
only)
38.5% (all other
countries)
The base case scenario assumes no change on tariff rates; Mexico will
maintain the 0% tariff rate whilst the remaining countries will continue
being subject to a rate of 38.5% which has been the case since 2000
Exporting country's
global 020130 beef
exports as a % of world
trade of 020130 beef
2.535%
The UK's world beef share reached historic high levels in 2011 and the
Base scenario assumes that it will not manage to increase that share any
further by 2016 which may be deemed conservative, given the UK's share
performance in recent history
Share of UK's total
exports to Japan as % of
total UK's global exports
1.509%
Japan's share of total trade for the UK has been declining over the last 10
years but has been stabilising since 2008. As such, the Base scenario
accounted for the CAGR since 2008 and applied it forward to 2016.
Given the recent EU-Japan discussions to negotiate towards an FTA, it is
likely that Japan will grow in importance as a trade partner in the future
Competition's importweighted average
wholesale prices to
Japan (pre-tariff)
$6.19 per kg
Using the domestic prices forecast by FAPRI for each of the competing
countries exporting beef to Japan and running separate linear regression
analyses in each case, estimated the future forecast price by each country
to Japan. Then, assuming that countries will maintain their Japan beef
export share in 2016 at the same level with 2011, estimated the import
weighted average wholesale prices to Japan for 2016. However, it is worth
noting that the price at which a country exports its products and the
quantities imported by another country are in reality linked and interdependent
Competition's importweighted average
wholesale prices to
Japan (post-tariff)
$9.80 per kg
Using figures above
Competition's export
boost (dummy variable)
187
0
Following Japan's permission in 2013 to import beef from cattle younger
than 30 months old from USA, Canada, France and Netherlands (which
in the case of USA and UK corresponds to 80% and above of the
countries' beef capacity), it is expected that when Japan removes the ban
on UK beef, it will be on the same terms as the other EU nations, USA
and Canada (i.e. beef from cattle younger than 30 months). This way, the
UK will be competing with the remaining exporters (including Australia
and New Zealand) on the same grounds (as this import restriction
concerns less than 20% of UK's cattle beef capacity) and therefore the
value of the dummy variable has been assigned to 0
© 2013 Grant Thornton UK LLP. All rights reserved.
Table F.5.
Explanatory variable
Forecasting assumptions for High scenario
Value forecast for Methodology
2016 under High
scenario
0% (Mexico only)
38.5% (all other
countries)
The scenario assumes no change on tariff rates; Mexico will maintain
the 0% tariff rate whilst the remaining countries will continue being
subject to a rate of 38.5% which has been the case since 2000
Exporting country's
global 020130 beef
exports as a % of world
trade of 020130 beef
2.830%
The UK's world beef share reached historic high levels in 2011 and
the High scenario accounts for the annualised growth between 2010
and 2011 (which was below the 5-year CAGR) and applies it annually
until 2016
Share of UK's total
exports to Japan as % of
total UK's global exports
1.549%
Japan's share of total trade for the UK has been declining over the
last 10 years but has been stabilising since 2008. As such, the High
scenario accounted for the 5-year average since 2007
Tariff rate on imports
from competing
countries
Competition's importweighted average
wholesale prices to
Japan (pre-tariff)
$6.19 per kg
Using the domestic prices forecast by FAPRI for each of the
competing countries exporting beef to Japan and running separate
linear regression analyses in each case, estimated the future forecast
price by each country to Japan. Then, assuming that countries will
maintain their Japan beef export share in 2016 at the same level with
2011, estimated the import weighted average wholesale prices to
Japan for 2016. However, it is worth noting that the price at which a
country exports its products and the quantities imported by another
country are in reality linked and inter-dependent
Competition's importweighted average
wholesale prices to
Japan (post-tariff)
$9.80 per kg
Using figures above
Competition's export
boost (dummy variable)
0
Following Japan's permission in 2013 to import beef from cattle
younger than 30 months old from USA, Canada, France and
Netherlands (which in the case of USA and UK corresponds to 80%
and above of the countries' beef capacity), it is assumed that New
Zealand, Australia and the UK will not have any longer any such
competitive advantage in terms of their exports to Japan. In fact, it is
expected that the UK will confront similar import restrictions (along
with France and Netherlands) but which should not pose significant
pressure on UK's exports given that this restriction concerns less than
20% of UK's cattle beef capacity
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188
Table F.6.
Explanatory variable
Tariff rate on imports
from competing
countries
Forecasting assumptions for Low scenario
Value forecast for Methodology
2016 under Low
scenario
0% (Mexico only)
38.5% (all other
countries)
The scenario assumes no change on tariff rates; Mexico will maintain
the 0% tariff rate whilst the remaining countries will continue being
subject to a rate of 38.5% which has been the case since 2000
Exporting country's
global 020130 beef
exports as a % of world
trade of 020130 beef
2.535%
The UK's world beef share reached historic high levels in 2011 and
the Low scenario accounts for the 5-year average since 2007
Share of UK's total
exports to Japan as % of
total UK's global exports
1.216%
Japan's share of total trade for the UK has been declining over the
last 10 years but has been stabilising since 2008. As such, the Low
scenario accounts for the historic CAGR between 2004-2011 and
applies it to 2016
Competition's importweighted average
wholesale prices to
Japan (pre-tariff)
$6.19 per kg
Using the domestic prices forecast by FAPRI for each of the
competing countries exporting beef to Japan and running separate
linear regression analyses in each case, estimated the future forecast
price by each country to Japan. Then, assuming that countries will
maintain their Japan beef export share in 2016 at the same level with
2011, estimated the import weighted average wholesale prices to
Japan for 2016. However, it is worth noting that the price at which a
country exports its products and the quantities imported by another
country are in reality linked and inter-dependent
Competition's importweighted average
wholesale prices to
Japan (post-tariff)
$9.80 per kg
Using figures above
Competition's export
boost (dummy variable)
189
0
Following Japan's permission in 2013 to import beef from cattle
younger than 30 months old from USA, Canada, France and
Netherlands (which in the case of USA and UK corresponds to 80%
and above of the countries' beef capacity), it is assumed that New
Zealand, Australia and the UK will not have any longer any such
competitive advantage in terms of their exports to Japan. In fact, it is
expected that the UK will confront similar import restrictions (along
with France and Netherlands) but which should not pose significant
pressure on UK's exports given that this restriction concerns less than
20% of UK's cattle beef capacity
© 2013 Grant Thornton UK LLP. All rights reserved.
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http://www.ukti.gov.uk/pt_pt/uktihome/pressRelease/120402.html?null
32 European Commission (2006), Doha Round: some recent economic analysis. Memo Brussels, 23 June 2006 on
http://trade.ec.europa.eu/doclib/docs/2006/september/tradoc_129213.pdf
33 Laborde, D., Martin, W., Van Der Mensbrugghe, D., (2011), "Potential Real Income
Effects of Doha Reforms", in Unfinished Business, The WTO's Unfinished Agenda?,
International Bank for Reconstruction and Development/World Bank
http://voxeu.org/sites/default/files/file/unfinished_business_web.pdf
34 OECD Joint Working Party on Agriculture and Trade THE (2012), The Impact of
Regional Trade Agreements on Trade in Agricultural Products
35 (2012), " The 2012 National Trade Estimate Report on Foreign Trade Barriers
(NTE)", Office of the United States Trade Representative (USTR)
36 Ferrantino, M. (2006), “Quantifying the Trade and Economic Effects of Non-Tariff
Measures”, OECD Trade Policy Working Papers, No. 28, OECD Publishing.
http://dx.doi.org/10.1787/837654407568
37 Bora, B. Kuwahara, A. and Laird, S. (2002), “Quantifying the Trade and Economic
Effects of Non-Tariff Measures”, UNCTAD
191
© 2013 Grant Thornton UK LLP. All rights reserved.
38 Gonzalez Mellado, A. Hélaine, S., Rau, M-L. and Tothov, M. (2010) Non-tariff
measures affecting agro-food trade between the EU and Africa, European
Commission, Joint Research Centre
39 Laursen K. (1998), Revealed Comparative Advantage and the Alternatives as Measures
of International Specialisation, December 1998, Danish Research Unit for Industrial
Dynamics
40 Utkulu U., Seymen D. (2004), Revealed Comparative Advantage and Competitiveness:
Evidence for Turkey vis-à-vis the EU/15, Dokuz Eylül University, Economics
Department, İzmir
41 Abdelhak Senhadji (1997), “Time-Series Estimation of Structural Import Demand
Equations: A Cross-Country Analysis”, IMF
42 Warner, A. M. (1992), “Import Demand and Supply with Relatively Few Theoretical
and Empirical Puzzles', Federal Reserve Board”
43 Krugman, P.R and Baldwin R.E. (1987), “The Persistence of the US Trade Deficit”,
Brooking Papers on Economic Activity 1:1987
44 Gujarati, D.N. and Porter D.C. (2004), “Basic Econometrics”, The McGraw−Hill
Companies
Databases
45 Trade Map is a database developed by the International Trade Centre
UNCTAD/WTO (ITC) and contains international trade statistics as well as
information on tariffs
46 UN Comtrade has been developed by the United Nations Statistics Division and
contains trade information
47 The Food and Agricultural Policy Research Institute (FAPRI) is a unique, dualuniversity research program, established in 1984 by a grant from the U.S. Congress, to
prepare baseline projections for the U.S. agricultural sector and international
commodity markets and to develop capability for policy analysis using comprehensive
data and computer modelling systems of the world agricultural market.
48 The Economist Intelligence Unit (EIU) was used to obtain forecast exchange rates,
GDP, private consumption and export figures by country
49 World Bank databases were used to obtain historic private consumption, GDP,
exports, population information as well as Gini coefficients by country. Certain trade
related indices were also collected from World Bank (i.e. Control of Corruption Index,
Logistics Performance Index, Doing Business Index)
50 The OECD-FAO Agricultural Outlook database was developed by the two
organisations and was used to obtain historic and forecast prices, consumption,
production and exports by raw materials and countries
51 The US Department of Agriculture (USDA) was used to understand the retail market
structure in a number of countries as well as historic and forecast prices, consumption,
production and exports by raw materials and countries
52 The Market Access Database (MADB) published by the European Commission was
used to obtain information on non-tariff measures imposed by various countries on
EU exports
© 2013 Grant Thornton UK LLP. All rights reserved.
192
53 The US International Trade Commission (USITC) has compiled the USITC CoRe
NTMs Database that sources data from MADB, USTR (Office of the United States
Trade Representative) and the WTO TPR (Trade Policy Reviews) documents
54 The World Integrated Trade Solution (WITS) is a software developed by the World
Bank, in close collaboration and consultation with various International Organizations
including United Nations Conference on Trade and Development (UNCTAD),
International Trade Centre (ITC), United Nations Statistical Division (UNSD) and
World Trade Organization (WTO). WITS gives users‟ access to major international
trade, tariffs and non-tariff data compilations: a) the UN COMTRADE database
maintained by the UNSD, b) The TRAINS maintained by the UNCTAD, c) The IDB
and CTS databases maintained by the WTO
55 CIA database was used to source Gini coefficients by country
56 IMF database was utilised to source GDP historics and forecasts
57 Data was purchased from Euromonitor International to obtain an understanding for
domestic retail market size for certain product categories and countries and total
consumer food expenditure historics and forecasts by country
58 Trade indices published by the International Chamber of Commerce (ICC)
Assistance provided with the methodology and the regression
analyses run in Chapter 7
59 Dr Paula Ramada, Partner, London Economics
193
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therefore accepts no liability in relation to this information on which this analysis is based.
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opinions contained within this report to any third party whatsoever other than the
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