UNIVERSITY OF GUYANA
GRADUATE SCHOOL OF SOCIAL SCIENCES
An Analysis of the Effectiveness of Foreign Aid Flows to
Guyana using the Autoregressive Distributed Lag
(ARDL) Approach to Cointegration: 1978-2002
A Thesis Presented in Fulfillment of the Requirement
for Master of Social Sciences Degree
Clement Henry
Supervised by: Enid Bissember & Winston Jordan
2007
ABSTRACT
The thesis examined issues related to effectiveness of foreign aid in Guyana. The general
view in development literature is that providing sufficient amounts of capital to
underdeveloped areas would create the conditions necessary for long-term economic
growth and development. However, given the chequered history of foreign aid and the
increasing scarcity of budgetary resources in donor countries, it has become necessary to
reassess the effectiveness of foreign aid and to identify means of maximising its benefits.
The motivation of this study was to ascertain the value of foreign aid as a determinant of
economic growth in Guyana, which has encountered difficulties attracting foreign private
flows because of its economic structure. Identifying the actual effect foreign aid or any
other type of resource has on growth, can generate insight into which development
policies promote sustained economic growth, thus providing the country with better
suggestions for long-term development strategies.
Empirical analysis was conducted, using the autoregressive distributed lag (ARDL)
approach to cointegration. This methodology is useful for small samples, since it is
helpful in avoiding the finite sample bias and is more efficient than the vector
autoregressive (VAR) method. Moreover, the single equation ARDL estimator delivers
super-consistent estimates of the long-run parameters and asymptotically valid t- ratios,
even in the presence of the endogenous explanatory variable.
A careful interpretation of the result suggests that it is difficult to take comfort in the
view that aid guarantees long-run growth. Theoretically, we expected aid, a component
of foreign savings, to boost investment and growth in Guyana, a country, which suffers
from capital resource scarcity. Notwithstanding the long-run result, our analysis indicates
that there was a short term significantly positive relationship between aid and economic
growth. Perhaps the most important implication is in delineating the obstacles in the path
of aid achieving long-run growth. Since it is generally accepted that economic and
political institutions are important to growth, then fundamental improvement is necessary
in this area if Guyana is to capitalise fully on the opportunities that presents themselves in
the aid arena. In order to maximise the development benefits of foreign aid, the
Government of Guyana with the help of the donor community need to strengthen its selfdevelopment capacity, continue to implement structural reforms necessary for sustained
growth, and focus on personnel training to gradually improve institutional
capacity. Government should also seek to provide incentives to retain highly qualified
and skilled personnel to aid in the development drive. In addition, migrants can be
encouraged to be agents of development by contributing to the country’s growth thrust,
through remittances, investment and expenditure, and entrepreneurial activities to achieve
sustained growth.
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This paper also shows that aid can affect poverty and development indicators by
increasing investment in the social sector. As expected, our results also confirm that
domestic savings, foreign direct investment, and export all contributed to long run growth
and that it was important for Guyana to create the environment and implement policies to
increase savings, investment and exports.
Key Terms: Foreign aid, aid effectiveness, economic growth, and autoregressive
distributed lag model
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ACKNOWLEDGEMENTS
I wish to express my sincere appreciation to my advisors, Ms Enid Bissember and Mr
Winston Jordan, for their continuous encouragement, valuable comments and insightful
supervision through the whole process of the thesis writing. I am also indebted to Dr
Michael Scott for his constant encouragement and suggestions throughout this study. I
thank my friends, Linda Giddings, Soren Griffith, and Adel Clarke for their invaluable
assistance with collecting data. I give special thanks to my mother, sisters, and brother
for their belief in me.
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TABLE OF CONTENTS
ABSTRACT........................................................................................................................1
ACKNOWLEDGEMENT……………………………………………………...………3
TABLE OF CONTENT...................................................................................................4
SECTION 1
INTRODUCTION…………………………………………….....6
SECTION 2
PURPOSE AND MOTIVATION FOR THE STUDY………..11
SECTION 3
COUNTRY BACKGROUND………………………………….15
SECTION 4
TRENDS IN FOREIGN AID FLOWS………………………..35
4.1
General Flows……………………………………………………35
4.2
Trends in Aid Flows to Guyana………………………………….43
4.3
Debt Relief as Development Finance……………………………50
4.4
Migrant Remittance Flows………………………………………53
4.5
Recent Initiatives, Issues, and the
Prospects of Aid to Guyana…………………………………..…55
4.6
Conclusion…..………………………………………………......59
SECTION 5
FOREIGN AID AND ECONOMIC GROWTH:
THEORETICAL FRAMEWORK AND A
REVIEW OF EMPIRICAL STUDIES.………………………60
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5.1.
A Brief History of Foreign Aid…………………………………..60
5.2.
Foreign Aid, Economic Growth, and the Dual Gap Theory…......64
5.3.
New Approaches to Studying Aid Effectiveness…...……………67
SECTION 6
EMPIRICAL ANALYSIS………………………………..….…79
6.1.
Modelling the Aid-Growth Regression…………………………..79
6.2.
Model Specification & Data Description………………………...83
6.3.
Data Source……………………………………………………....85
6.4.
Methodology……………………………………………………..86
6.5.
Results …………………………………………………………...88
SECTION 7
CONCLUSION, SOME POLICY IMPLICATIONS
AND NEW RESEARCH EMPHASES ……………………...103
APPENDIX I:
ESTIMATION OUTPUT………….……………...………......108
BIBLIOGRAPHY………………………………….…………….…………………....129
MAP OF GUYANA……………………………….…………….……………….........139
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1.
INTRODUCTION
Traditionally, foreign aid flows were seen as means of stimulating economic growth and
development in developing countries. The Marshall Plan of the USA, which represented
bilateral assistance from the United States to countries in Europe, was instrumental in
rebuilding the shattered infrastructure of those European nations after World War II. This
development led to the establishment of the Bretton Woods institutions, the World Bank
and the International Monetary Fund (IMF). Subsequently, other development institutions
followed such as the Inter-American Development Bank (IDB), the Asian Development
Bank (ADB), the Caribbean Development Bank (CDB), the African Development Bank
(AfDB), and more recently, the European Bank for Reconstruction and Development
(EBRD). Foreign aid’s critical role in igniting economic growth and promoting
development became the central lesson from the Marshall Plan. Impressed with the
success of the Marshall Plan, policy makers and development practitioners emphasised
the crucial role of capital in catalysing growth and fostering development.
The
conviction was that providing sufficient amounts of capital to underdeveloped areas
would create the conditions necessary for long-term economic growth and development.
This position has been increasingly challenged.
Academicians and policy makers have cast doubts on the role of foreign aid in promoting
development, prompting further academic work and political debate on the effectiveness
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of foreign aid. On the one hand, there are some who believe that aid can be effective,
while on the other, there are those who are resilient agnostics with respect to the
effectiveness of aid.
Suffice it to say at this stage that the flow of foreign aid to
developing countries has had a chequered history; as a result, there has been growing
scepticism in donor countries over the contribution of aid to economic growth in
developing countries. Bhagwati and Eckhaus (1970) assessment aptly sums up the aid
scenario:
Foreign Aid programmes for providing assistance to less developed
countries have fallen on hard times. The nominal amounts of aid pledged
by developed areas have recently been falling and the real values of
economic assistance have fallen further. This time due in part to the
diversion of attention of donor countries to other foreign policy issues. It
is due partly to their pre-occupation with their own domestic problems.
There has, however, also been a growing disenchantment with the
potential for development in the poor countries and also with the role
foreign aid can play in the development. Optimistic expectations of rapid
growth in less developed countries have given way to sceptical evaluations
of their actual performance. The contribution of foreign aid to
development has also been evaluated more sceptically and its possible
disincentive effects are now being emphasised.1
Notwithstanding Bhagwati and Eckhaus’ critical assessment, a number of poor countries
still view aid flows as critical components of their development strategy, even though the
magnitude of aid flows has been an increasingly sensitive issue in donor countries’
budgetary discussions. A major condition for the sustainability of aid flows to developing
1
J. Bhagwati and R. Eckaus (editors), 1970, Foreign Aid. (Hardmondsworth: Penguin), p. 7.
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countries is a belief in its efficacy. Such a belief rests on seeing positive results and
improvements in the use of aid resources.
Small countries like Guyana face peculiar constraints in attracting private capital. Small
size coupled with structural inefficiencies reduces the relative attractiveness of these
economies to private capital. A study by Lensink and White (1998)2 revealed that private
capital, all else being equal, is more likely to flow to countries with larger GDPs. Even
though a recent work3 has convincingly challenged the argument that small states are less
likely to attract private capital flows, foreign aid still remains important to many of them.
Foreign aid has been instrumental in helping a number of countries realise rapid
economic growth and development.
Botswana, South Korea, and Costa Rica are
examples of countries, which were able to achieve respectable improvements in per
capita GDP with the assistance of foreign aid. Foreign aid flows to Botswana, South
Korea, and Costa Rica, during the period 1970-1989, averaged 19.9, 3.7, and 8.1 percent
of gross national product (GNP), respectively; while private capital flows were
substantially lower, averaging only 4.7, 0.6, and 4.3 percent of GNP, respectively. Per
capita GDP improved from US$436 in 1970 to US$2,405 in 1989 for Botswana; from
US$1,913 in 1970 to US$6,133 in 1989 for South Korea; and from US$2,518 in 1970 to
2
R. Lensink and H. White, 1998, “Does the Revival of International Private Capital Flows Mean the end of
Aid? An Analysis of Developing Countries Access to Private Capital,” World Development, Vol. 26, pp.
1221-1234.
3
W. Easterly and A. Kraay, 1999, “Small States, Small Problem? Income, Growth, and Volatility in Small
States,” World Development, Vol. 28, pp. 2013-2027.
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US$3,128 in 1989 for Costa Rica. But other examples show that foreign aid can have
little or no effect on growth and development, as in the case of Zambia. For the period
1970 to 1989, foreign aid flows to Zambia averaged 10.9 percent of GNP, while private
flows averaged 3.3 percent of GNP. However, per capita GDP for Zambia declined from
US$569 in 1970 to $US403 in 1989. In light of this apparent paradox, the impact of
foreign aid on growth requires careful country-specific study, since the results of such
investigation can greatly influence donors’ perception on the relative importance of aid in
a particular context.
It is against this background that the present study examines the effectiveness of foreign
aid in Guyana in order to illuminate its impact on economic growth. The study has six
specific objectives: to empirically assess the impact of foreign aid on Guyana’s economic
growth for the period 1978 – 2002; to identify trends in the volume and composition of
foreign aid to Guyana; to examine policy and institutional issues relating to the effective
utilisation of foreign aid; to review existing mechanisms and structures in the
management and coordination of aid; to explore ways to improve the management of
foreign aid to Guyana; and to isolate policy lessons and make recommendations for small
economies such as Guyana.
Some words of caution are relevant here. Even though aid is primarily for development,
we use economic growth as a proxy variable for economic development, making it our
dependent variable in the regression. Although related and sometimes used
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interchangeably, economic growth and economic development are distinct phenomena.
On the one hand, economic development has a qualitative dimension and encompasses
the reduction of poverty and improvements in nutrition, health, education, and standard
of living. Economic growth, on the other hand, refers to quantitative changes, and it
occurs when output increases faster than the population. However, growth is a necessary
pre-condition for economic development. Finally, the results must be taken with the
understanding that the time period utilised in the analysis is relatively short and concerns
have been expressed regarding the reliability of data on developing countries.
The rest of the study is structured as follows: Section two outlines the rationale for
undertaking this study. Section three presents a description of the country characteristics
during the period under review. Section four outlines general trends and issues in foreign
aid flows to developing countries and then it focuses on trends in aid flows to Guyana.
Section five critically reviews the recent theoretical and empirical literature on aid
effectiveness. It gives a succinct history of foreign aid and discusses the literature related
to the impact of aid on growth. In Section six a theoretical aid-growth model is developed
and estimated. This section provides new evidence regarding the impact of aid on growth.
Section seven concludes the overall research by summarising and analysing the main
findings, identifying key policy issues, and suggesting areas for future research work.
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SECTION 2 PURPOSE AND MOTIVATION OF THE STUDY
The purpose of this research is to critically examine issues related to the management and
effectiveness of foreign aid in Guyana and to recommend desirable directions for the
future. In doing so, the paper will examine recent empirical research on the effectiveness
of foreign aid and conduct an econometric analysis using time series data.
The motivation of this study is to ascertain the value of foreign aid as a determinant of
economic growth in Guyana, which has encountered difficulties attracting foreign private
flows because of its economic structure. Given the chequered history of foreign aid and
the increasing scarcity of fiscal resources in donor countries, it has become necessary to
reassess the value of foreign aid in promoting sustained growth and development.
There are other compelling motivations for new research in this area. Aid effectiveness
research cannot unambiguously demonstrate major benefits from the aid given in the past
few decades, and multilateral financial institutions such as the World Bank have
acknowledged that many of their projects do not meet their own success criteria.
Simultaneously, political changes have transformed the global aid scene. The end of the
Cold War made it less necessary for bilateral donors to use aid to achieve political
balance or advantage between recipient countries leading to several major donors
reducing the size of their foreign aid commitment.
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Summarily, four major factors have contributed to the decline in aid commitments and
disbursements:
(i) a growing feeling that private sector activity and investment may be more effective in
bringing about progress;
(ii) examples of ineffective and unaccountable aid-funded activities;
(iii) bureaucratic impediments arising from implementation through governmental
institutions in recipient countries; and
(iv) internal political factors in donor countries where taxpayers and the electorate have
become concerned about funds being sent overseas, rather than being used at home where
there is growing needs.
The choice of focus can be justified on several grounds. Because of the increasing
recognition among development specialists for foreign aid to catalyse the process of
economic growth and development in developing countries, a lot of work is needed to
increase understanding of the economic behaviour of this type of resource flow on
economic growth and development. Even though there is a plethora of information on
this subject, it is based on cross-section studies with a number of shortcomings. Newlyn
rightly affirms that cross-country functions which are estimated using data from a number
of countries portray a functional relationship that can only be suggestive as to the
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individual country’s behaviour.4 Therefore, to use cross section data would only allow us
to make some general observations on the effectiveness of aid flows to Guyana. We
therefore opt to use time series analysis, which gives an estimate of the functional
relationship within the time period covered by the annual observations and therefore,
reflect country specific behaviour during the particular period.
The appropriateness of country-specific studies over cross-country studies has long been
recognised by prominent economists such as White (1992). In our research, we did not
find any study that explored the potential causal relationship between foreign aid and
economic growth using time series data for Guyana. This study attempts to fill that gap
in the literature.
To conclude, the issue of aid effectiveness appears to be paradoxical. On the one hand,
some countries remain poor despite massive inflows of aid. On the other hand, some
countries manage to increase growth with relatively modest amounts of aid. In light of
this apparent contradiction, the impact of foreign aid on growth requires careful study,
since the results of such investigation can influence donors’ perception of the relative
importance of aid flows to developing countries. In light of the scepticism about the
effectiveness of aid, it is an appropriate time for aid recipients and donors alike to bring
their foreign aid experience under scrutiny. A demonstration of aid’s effectiveness can
4
W. T. Newlyn, 1973, The Financing of Economic Development, (Oxford: Oxford University Press), p.
127.
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serve to increase support for it among both the general public and political leaders,
thereby contributing to increases in its volume and better utilisation.
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SECTION 3 COUNTRY BACKGROUND
Guyana is a country located on the northern coast of South America, bordering the
Atlantic Ocean to the north, between Suriname and Venezuela, to the east and west
respectively, and Brazil to the south. The official name of the country is the Co-operative
Republic of Guyana.5 It is the only English-speaking country on the South American
continent and is a member of the Caribbean Community (CARICOM). Though
physically a part of South America, culturally, Guyana is more Caribbean than Latin
American. Covering an area of 214,970 square kilometres, the country’s terrain is mostly
rolling highlands, together with the low coastal plain in the north and the savannah in the
south. The coastal plain, which is 2.4 metres below sea level at high tides, is where the
country’s capital, Georgetown, is situated and where most of the commercial activities
take place. The hilly sand and clay area is noted for its white sand and bauxite ore, the
highland region is mainly mineral rich dense rainforest, and the interior savannah is
characterised by grasslands interspersed with trees, lakes, and rivers. The local climate is
tropical and is generally hot and humid, though moderated by the north-eastern trade
5
Here we present a succinct geographic and demographic description of Guyana. For the reader whose
interest may have been awaken and desires a more elaborate discussion on the geography, politics, people,
and culture of Guyana see Deryck Bernard, 1999, A New Geography of Guyana, Macmillan Publishers
Limited; Cheddi Jagan, 1972, West on Trial, My fight for Guyana’s Freedom, New York: International;
and Ovid Abrams, 1998, Metegee: History and Culture of Guyana, Eldorado Publications.
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winds along the coast. There are two rainy seasons, the first from May to mid-August,
and the second from mid-November to mid-January.6
Guyana has a multi-racial population, which according to the 2002 Guyana Population
and Housing Census, is approximately 751,223 comprising mainly of East Indians (43.4
percent), Africans (30.2 percent), Mixed (16.7 percent), Amerindians (9.2 percent), and
Europeans and Chinese (0.5 percent). The population is spread over 10 administrative
regions, averaging 3.5 persons per square km. The bulk of the population resides in
region 4 (41.3 percent) and region 6 (16.4 percent). Population density is highest in
region 4 (139 persons per square Km), and lowest in region 9 (0.3 persons per square
Km). The urban centres contain 28.4 percent of the population, while 71.6 percent of the
total population is considered rural.
People of working age, 15 years and above,
represent two-thirds of the total population (484,042 persons). 56 percent of the working
age population participates in the labour force. The report shows that for every 100
persons between the ages of 15-64, there are 90 dependents (0-14 and 65 and above).
Guyana achieved political independence from the United Kingdom in 1966. During the
early post-independence period, Guyana's economy was dominated by a narrow range of
export commodities - sugar, rice, and bauxite - whose production and marketing was in
the hands of a small number of foreign-owned enterprises. Two British companies,
6
US Department of State, Bureau of Western Hemisphere Affairs, April 2001, “Background Note:
Guyana” online, available at < http://www.state.gov/r/pa/ei/bgn/1984.htm>
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Booker McConnell and Jessel Securities, controlled the largest sugar estates. Two other
foreign companies dominated the mining sector: the Demerara Bauxite Company, a
subsidiary of the Aluminum Company of Canada (Alcan); and the Reynolds Bauxite
Company, a subsidiary of the Reynolds Metals Company of the United States. Foreign
companies also controlled the major banks, and indeed other aspects of the economy. In
fact, as Jordan (1993) informs, the only industry of consequence that remained in
domestic hands was rice, and even here the colonial government sought to regulate and
control through the establishment of regulatory authorities.
The World Bank (1993) elucidates that during the 1970s, the Government of Guyana
pursued a policy of increased intervention into all aspects of domestic economic
activities. Jordan (1993) explains that prior to this period, the government played a
relatively passive role in the national economic life, performing regulatory functions, and
where possible providing economic and social infrastructure to support development.
However, he further states that the private sector, which was dominated by foreign
companies, failed to live up to its role as being the main agent for economic
transformation, and thus the economy remained relatively undiversified. Disenchanted
with the private sector’s inability to fulfil its role, the Government altered its strategy and
adopted a development paradigm referred to as “cooperative socialism,” which espoused
state ownership and management of the major productive centres and the equitable
distribution of the gains of production. In keeping with this paradigm, the government
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sought to reduce foreign domination in the local economy, since it was believed that
foreign ownership of the major productive centres of the economy was the main obstacle
to economic transformation and progress. Griffith (2002) makes the point that “Too much
control of the economies have been exercised from abroad… particularly by the
international corporations in the form of foreign direct investment. Too much reliance for
economic expansion has been placed on foreign private investment.” 7 Working under the
premise that state control of the major centres of production is crucial to economic
development, the Government of Guyana brought the major productive centres (sugar,
rice, bauxite, and gold) under its control. Government control over the economy further
intensified and widened to all sectors of the economy, including the financial sector with
the nationalisation of foreign-owned banks. It also instituted foreign exchange rationing
and price controls and imposed restrictions on external current and capital accounts
transactions. According to the World Bank (1993), by 1988, the Government of Guyana
controlled over 80 percent of the recorded trade and 85 percent of the total investment
through nationalisation and localisation.
The resulting resource misallocation, a corollary of the paradigm shift in government’s
management of the economy, was aggravated by a combination of factors including
external shocks due to increases in petroleum prices, declining terms of trade, and an
overly aggressive expansion of government spending and led to a sharp decline in real
7
W. Griffith, 2002, “Tale of Four CARICOM Countries,” Journal of Economic Issues, Vol. xxxvi Number
1, p. 85.
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economic activities. Jordan (1993) gives a vivid description of the decline of the
economy up to 1987. He reports that the public sector deficit widened from an average of
-19.9 percent of GDP for the period 1976-80 to an average of -48.4 percent in 198487(see table 1). The deficit on current account of the balance of payments worsened from
an average of 7.1 percent of GDP for the period 1971-75 to an average of 32.8 percent for
the period 1981-83. The trade balance, which averaged 5.5 percent of GDP over the
period 1971-75, slumped to an average of -7.1 percent over the period 1981-83. Real
gross domestic product growth declined from an average of 4.0 percent during1971-75 to
an average of -0.7 percent in the period 1976-80. It declined even further during the
period 1981-83, to an average of -6.7 percent, before improving to an average of 0.8
percent in 1984-87.
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Table 1: Guyana: Selected Macroeconomic Indicators (1971-1987)
Indicators (as percentage of Real
1971-75
1976-80
1981-83
1984-87
Domestic Expenditure
102.5
112.1
118.6
113.4
Public Sector
34.5
47.5
49.1
56.7
Private Sector
67.1
64.6
65.5
56.6
Public Sector Deficit
n.a.
-19.9
-42.5
-48.4
Public Savings
n.a.
1.8
-21.4
-25.3
Central Government
2.5
-6.7
-17.9
-34.9
Public enterprises
n.a.
8.5
-3.6
9.6
Balance of Payments
2.2
-11.5
-25.4
-33.4
Current account
-7.1
-19.9
-32.8
-26.2
Trade Balance
5.5
-1.7
-7.1
-0.2
Real GDP (at factor cost) –
percentage
change
(annual
averages)
4.0
-0.7
-6.7
0.8
GDP)
n.a. Not available
Source: “Guyana: Socioeconomic Report,” IDB in W. Jordan. (1993) Lessons of
Experience from Implementing Structural Adjustment Programmes in a Highly Indebted
Country, Tales from Guyana, Penn State University (Unpublished) p. 22.
As the effects of the rising fuel prices intensified, coupled with the poor performance of
the three key export sectors,8 there emerged a large build-up of arrears on the external
debt. Guyana’s debt reached unsustainable levels in the 1980s that resulted in the country
defaulting on its debt obligations. Data from the World Bank (1993) reveal that by 1988,
8
Three key sectors referred to are bauxite, sugar, and rice. Overall, terms of trade deteriorated by over 30
percent for the period 1980 -86.
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external payment and arrears reached a mammoth US$1133.9 million compared to
US$45.4 million in 1980. External debt stock to GDP ratio rose from 88.3 percent in
1978 to 226.5 percent in 1988, and debt stock to export ratio reached 391.2 percent in
1988. Scheduled debt service to GDP ratio was estimated at 50.6 percent of GDP and
87.4 percent of exports of goods and non-factor services in 1988. However, actual debt
service was only 8.6 percent of exports of goods and non-factor services in that year and
averaged 16.5 percent of exports of goods and non-factor services for the period 1978 –
1988. The implications of the build-up of debt and arrears on development in Guyana
were far reaching. At a time when there were numerous budgetary constraints,
considerable amounts of budgetary expenditure would have had to be earmarked for
external debt servicing. These allocations have very high social opportunity costs, as in a
sense that they siphon away funds that should be spent on improving basic health and
education. Conversely, debt default by the government makes it difficult for the
government to raise debt financing since it has a negative impact on the country’s credit
worthiness and can result in the country being denied further support from donors.
The persistent decline in the performance of the Guyanese economy led to significant
reversals in a number of development indicators. The World Bank (1993) indicators
reveal that real daily minimum wage declined from $11.55 in 1980 to $5.94 in 1988.
Crude death rate worsened from 7.5 per 1000 in 1978 to 8.5 per 1000 in 1985. The IDB
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(2002) estimated the poverty rate to be as high as 65 percent of the population in 1988,
and 75 percent in 1989.
In 1988, faced with the failure of the planned economy, in part reflected in large and
rising external payments arrears, the threat of being unable to access international capital,
and a growing underground economy,9 Guyana launched the Economic Recovery
Programme (ERP). The comprehensive ERP combined macroeconomic stabilisation
policies and far-reaching structural reforms to restore sustainable output and employment
growth in the context of a market-based economy. The government throughout the early
1980s made several attempts to promote stabilisation and implement structural
adjustment programme. But it was not until mid-1988 that the Government of Guyana
with the assistance of the international financial institutions, introduced the Economic
Recovery Programme (ERP), aimed at reducing macroeconomic imbalances, reduction of
public sector involvement in major economic activities, trade liberalisation, as well as
restoring credit worthiness. In March 1989, the relevant negotiation between government
and the Multilateral Financial Institutions were completed and the stage was set for the
full implementation of the reform measures set out in the programme.
The implementation of the fundamental economic and structural reforms in Guyana
needed substantial external financial assistance especially for the financing of critical
9
C. Thomas, 1989, provides estimates of the underground economy ranging from 26 to 52 percent of the
official economy in 1982 and 33 to 99 percent in 1986. E. Faal, 2003, reports that the size of the
underground economy averaged 47 percent in the 1990s.
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imports and the need to meet high priority debt obligations. A Support Group of ten
bilateral donors led by Canada and including the United States, the United Kingdom,
Japan, France, and Trinidad and Tobago, was able to mobilise a substantial sum of
interim financing allowing Guyana to successfully clear its arrears to the Multilateral
Financial Institutions by 1990 and create the opportunity for renewed inflows of official
financing. Financing was in the form of debt rescheduling, project financing, balance of
payments support, and debt and interest relief. Even though the funds received were
useful in helping Guyana fulfil its obligation to the Multilateral Financial Institutions,
ultimately it did not reduce debt service. The IDB (2002) posits that debt service ratio of
Guyana at the end of 1990 was the highest in the world at 74.5 percent of GDP and the
outstanding stock of debt to GDP ratio was 738 percent.10
Despite the implementation of the recovery programme to foster growth and reduce
imbalances, the economy by the end of 1990 continued to experience economic
difficulties, due in part to delays in the implementation of policies and the necessary
external financial inflows. In 1990, real gross domestic product declined by 4.7 percent
and inflation reached 63.6 percent due to exchange rate adjustment and price
liberalisation.11 The balance of payments current account deficit widened (see table 2) by
30 percent in 1990 (US$113.3 million in 1989 to US$ 147.8 million in 1990) due to
10
The reader should be careful when interpreting these indicators or when making cross country
comparison because of the presence of a large underground economy in Guyana, which affects the
compilation of the official GDP. Currently steps are being taken to improve the coverage of GDP.
11
Bank of Guyana, 1990.
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significant increase in the merchandise trade deficit caused by increases in imports.
However, the capital account improved (deficit was reduced from US$68.9 million in
1989 to US$47.3 million in 1990) and could have been better were it not for an increase
in amortisation payment. The overall deficit was financed by balance of payment support
and debt relief, which together with renewed disbursement from the Multilateral
Financial Institutions and bilateral donors resulted in the build-up of gross international
reserves equivalent to five weeks of imports. It should be noted that net private inflows
remained low in the 1988 – 1990 period.
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Table 2: Summary Balance of Payments (1988 -1991) (US$ Million)
1988
Current Account
1989
1990
1991
-93.6
-113.3
-147.8
-135.8
-1.0
-7.7
-45.7
-13.6
Exports, f.o.b.
214.6
204.7
203.9
238.6
Imports, c.i.f.
-215.6
-212.4
-249.6
-252.2
Services (net)
-112.0
-127.2
-130.4
-144.2
Transfer (net)
19.4
21.6
28.3
22.0
-22.8
-68.9
-47.3
76.6
-27.8
-64.1
-56.1
-20.4
-27.8
-61.4
-56.1
-20.4
0.0
-2.7
0.0
29.0
Financial sector (net)
0.3
-14.0
3.7
..
Private Sector (net)
4.7
9.2
5.1
68.0
10.7
1.0
2.1
-13.5
-105.7
-181.2
-193.0
-72.7
105.7
181.2
193.0
72.7
Bank of Guyana net foreign assets
32.2
29.5
-18.8
-40.4
Public sector Arrears
70.0
-156.0
-265.3
..
Private Sector arrears
3.5
9.6
-101.3
..
..
298.1
578.4
113.1
Merchandise Trade (net)
Capital Account (net)
Non-Financial Public Sector (net0
Medium & long-term Loans (net)
Short Term Debt (net)
Errors and Omission
Overall Balance
Financing
Other (Debt relief & Balance
of Payments
Support)
Source: Bank of Guyana
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Guyana’s Economic Recovery Programme, by remedying some of the major economic
pathologies that engendered the recession, was effective in halting the economic
downturn and generating growth by 1991. After a period of prolonged negative or low
economic performance, a 6.1 percent growth was recorded that year. There was also
significant improvement in the balance of payments performance. Improvement of the
export sector and continued capital inflows from the Multilateral Financial Institutions, as
well as in the form of foreign direct investment were the major determinants of the
strengthening of the balance of payments. The overall balance off payments deficit in
1991 was US$72.7 million compared with a deficit of US$193.0 million in 1990, which
represented an improvement of 62.5 percent (see table 2). The current account showed a
very small improvement of 6.2 percent from US$ -147.8 million in 1990 to US$ -135.8
million in 1991. The capital account recovered dramatically from a deficit of US$47.3
million in 1990 to a surplus of US$ 76.6 million in 1991. This signified a healthy inflow
position combined with a lessening of outflow due to debt rescheduling and debt relief.
The improvements in the economy that begun in 1991, due to renewed capital inflows
from official and private sources, continued during 1992 to 1997 period. The growth rate
of real GDP averaged 7.3 percent, mainly due to the resurgence export-related production
(particularly sugar and rice). Inflation showed a significant decline from 90 percent in
1989 to 28 percent in 1992, and 3.6 percent in 1997.12 The balance of payments current
12
The IMF Online Statistics, Accessed November 2005
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account deficit declined steadily until 1996 (see table 3). Increased confidence in the
economy led to a boost in foreign and private investment, particularly in bauxite, gold,
and forestry industries. The current account deficit narrowed from 43.2 percent of GDP
in 1992 to 9.2 percent of GDP in 1996. Gross international reserves improved to 5
months of imports of goods and non factor services in 1996, before declining to 4 ½
months in 1997. However, in 1997 the current account deficit rose to 14.6 percent from
9.2 percent in 1996 mainly due to sharp decline in export prices. The capital account
surplus fell in 1993 and 1994, largely because of a reduction in private capital flows
following the completion of major privatisation projects in the timber and gold sectors;
but it rebounded from U$22.9 million in 1994 to US$125.7 million in 1997. In addition
public sector debt was reduced from 623 percent of GDP in 1992 to 285 percent of GDP
in 1997.
During the period 1998-2002, adverse weather conditions, decline in export prices,
slower implementation of reforms, and ethnic based political conflict all contributed to a
reversal of some of the economic gains of the earlier period. Although inflation remained
low, averaging 5.2 percent, GDP growth plummeted to an average of 0.4 percent per
annum for this period (see Table 4). Growth rates were negative in 1998 and 2000.
During 1997 - 2002, the government and civic society begun a process which culminated
in the design of the Poverty Reduction Strategy Paper (PRSP) aimed at combating
poverty. The PRSP comprised measures to stimulate job-generating economic growth,
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create stronger institutions and better governance, develop social capital, and foster
investment in physical infrastructure
Table 3: Selected Economic Indicators 1992-1997
Indicators
1992
1993
1994
1995
1996
1997
In millions of U.S. dollars
Current Account Balance
-146.7
-137.9
-100.8
94.9
-53.8
-105.1
Exports f.o.b.
381.7
414.0
463.4
495.7
574.8
593.4
Imports c.i.f.
-442.7
-483.8
-504.0
-536.5
-595.0
-641.6
Trade balance
-61.0
-69.8
-40.6
-40.8
-20.2
-48.2
Net services & unrequited transfers
-85.7
-68.1
-60.2
-54.1
-33.6
-56.9
Capital account balance
123.6
78.1
22.9
28.0
59.5
125.7
of which, medium long term capital
126.6
71.7
26.7
26.2
-552.9
90.0
Public sector
-11.3
8.4
-20.1
-27.2
-611.9
38.0
Private (net)
137.9
63.3
46.8
53.4
59.0
52.0
-39.3
-49.7
-63.9
-68.9
-1.4
4.0
7.8
8.2
8.5
5.0
7.9
6.2
Overall Balance of payment
Real GDP- annual growth rate at
factor cost
% of GDP
Total Public sector debt
623.0
536.1
464.4
380.3
263.5
285.0
Current account balance
43.2
-29.6
-19.5
-19.1
-9.2
-14.6
Gross official international reserve
In months of imports
4.1
4.9
5.1
4.6
5.2
4.6
Source: Bank of Guyana; and IMF Online Statistics
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Table 4: Selected Macroeconomic Indicators 1998-2002
Indicators
Real GDP growth (%)
GDP per Capita GDP per capita
(constant 2000 US$)
1998
1999
-1.7
2000
2001
2002
3.0
-1.4
3.4
-1.1
932.7
956.2
939.0
967.1
952.4
-2.1
4.6
2.5
7.5
-1.8
6.1
3.0
2.7
-1.5
5.3
Real GDP per capita growth
(annual %)
Inflation Rate (consumer Prices)
Source: World Development Indicators, 2005
Several indicators highlight the progress that was achieved by Guyana as a result of the
policy reform under the Economic Recovery Programme and accompanying increased
inflows (see table 5). Economic growth showed a substantial increase and current account
deficit was reduced. Inflation and debt service-to-export ratio were also reduced
considerably. There was significant improvement in the production of sugar, the
country’s main export earner. There was also progress in a number of the development
indicators including health and education. At the same time, however, there was a fallout
from the ERP. The reform measures brought about added hardship to the Guyanese
populace in the form of loss of public sector jobs and income due to retrenchment from
public enterprises, reduction in real wages, and rising commodity prices. Central
Government employment was reduced by 56 percent in 1990, from 42,000 to 18,656.
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Consumer price indices increased by 39.4, 61.8, and 66.7 percent in 1988, 1989, and
1990 respectively. 13
Table 5 Selective Indicators Showing Development
Indicators
Prior 1991
After 1991
Real GDP growth
Averaged – 3 % in 1980s
Averaged 5.6 in 1990s
Inflation rates
Averaged 70 % over 1987
-1991
Averaged 7 % over 1995 1999
Current Account Deficit
Averaged 26.2 % of GDP
in 1984-87
Averaged 15.5 % of GDP
over 1999 - 2002
External Debt
US$ 1940 million in 1990
US$1422 million in 1999
Debt service to exports ratio
73.2 % in 1990
15.1 % in 1999
Sugar production
132,000 tonnes in 1990
$321,000 tonnes in 1999
% of population with access to
safe drinking water
85 % in 1990
92 % in 1999
Education as a share of budget
1.9 % in 1990
11.9 % in 1998
Adult Literacy Rate
95.4 % in 1985
98.4 in 1999
Health care expenditure per capita US$ 19 in 1990
US$ 45 in 1998
Under 5 mortality rate
90/100,000 in 1990
79/100,000 in 1998
Life expectancy at birth
64.2 years in 1990
64.6 years in 1998
Population access to health care
87 % in 1990
89.2 % in 1998
Poverty estimates
65 % in 1998
35 % in 1998
UNDP Human development
Index
Real GDP per capita (PPP$)
.589 in 1991
.704 in 2001
Averaged $1480 over
1985-88
$3640 in 1999
Source: IDB 2002 and IMF Online Database
13
The World Bank, 1993.
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In order to mitigate the social cost of the adjustment process, the government established
the Social Impact Amelioration Programme (SIMAP) in July 1988, which was an
institutionalised response to target the poor and vulnerable groups in the population,
including the urban unemployed, small farmers, pregnant and lactating mothers, children
under five years, and pensioners. Although the response was disappointing at the
beginning, donors ensured an increase in the flow of aid, subsequently, to tackle the
social maladies associated with structural adjustment.
Guyana’s protracted economic difficulties and diminished standard of living have exacted
a toll on the population as evidenced in the mass migration of persons at all levels and
varying skills. Orozco (2002) states that a large number of Guyanese (estimates are as
high as 500,000 to 1,000,000) emigrated, contributing to a loss of skilled personnel and
continuing reliance on unqualified workers. Mishra (2006) estimates that Guyana’s
workforce with tertiary education was reduced by 89 percent due to migration to
Organisation for Economic Cooperation and Development (OECD) member countries.
This high migration rate suggests that potentially migration can affect the prospect of
growth by creating critical labour and management shortages. On the flip side, Guyana
has benefited from transfers from abroad in the form of remittances from its migrant
population. Nevertheless, Mishra (2006) used welfare calculations to suggest that total
loss to the economy due to migration, outweighs the remittances to the country.14
14
Mishra uses official data which fail to reflect the true magnitude of remittances.
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There is now heightened awareness that the quality of a country’s governance system is a
key determinant of its ability to pursue sustainable economic growth and development.
Consequently, governance has taken an increasingly important role as a criterion for
economic success in the developing world and Guyana is no exception. The inclusion of
the concept of governance in the development agenda reflects the growing concerns over
the impact mismanagement and political instability has on aid effectiveness. The concept
of governance encompasses “the form of political regime, the process by which authority
is exercised in the management of a country’s economic and social resources for
development; and the capacity of governments to design, formulate and implement
policies and discharge functions.”15 Well-institutionalised governance systems are more
likely to produce, over the long run, sustainable economic growth and development,
because they provide effective, stable institutional and procedural mechanisms to
moderate social conflict and induce compromise, and lead to greater efficiency in
government’s action and a more efficient allocation of resources. Guyana has a history of
political division, poor governance, limited implementation capacity, and weak
institutions. During the 1980s, there was a widespread allegation of rigged elections,
corruption, ineffective public sector, and a lack transparency and accountability in
governance. Even though significant changes were made in transforming this situation
during the ERP years, and particularly after free and fair elections in 1992, official
statistics show slippage in governance indicators by the end of 2002 (table 6). Between
15
C. Santiso, 2001, “Good Governance and Aid Effectiveness: The World Bank and Conditionality” The
Georgetown Public Policy Review, Vol. 7 Number 1 Fall 2001, p. 5.
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1996 and 2002, there was less voice and accountability, the country was more politically
unstable, government was less effective, there has been a decline in regulatory quality, a
break down in the rule of law, and an increase in corruption (Kaufmann, et al, 2005).
Table 6: Governance Indicators for Guyana 1996-2002
Governance Indicators
Year Percentile rank
(0-100)
Voice and Accountability 2002 69.0
2000 73.3
1996 73.3
2002 32.4
Political Stability
2000 35.2
1996 49.4
Government Effectiveness 2002 46.3
2000 48.9
1996 47.5
2002 42.3
Regulatory Quality
2000 46.5
1996 60.8
2002 38.3
Rule of Law
2000 54.5
1996 57.8
2002 39.3
Control of Corruption
2000 43.0
1996 43.3
Estimate
-2.5 +2.5
+0.65
+0.91
+0.90
-0.39
-0.42
+0.10
-0.30
-0.16
-0.28
-0.37
-0.04
+0.22
-0.46
-0.14
+0.01
-0.48
-0.37
-0.31
Source: Kaufmann, et al, (2005), Governance Matters III; Governance Indicators 1996-2002
In this section, we presented a general background and the socioeconomic experience of
Guyana. The country’s economy has moved through several economic crises since 1978,
before embarking on a sustained period of economic growth (1991-1997), followed by a
sustained period of decline (1998-2002). Part of this success has been associated with the
government’s commitment to achieve economic development combined with increase
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inflows from official and private sources. The series of policy reforms undertaken by the
government during the reform period attracted increased flows of foreign assistance,
especially by multilateral donors such as the IMF, the World Bank, and the InterAmerican Development Bank. Bearing in mind that the country-specific behaviour of aid
flows is the central issue addressed in this study, the vicissitudes of Guyana’s experience
during the period under examination only serve to strengthen the argument for country
specific studies in assessing the effectiveness of foreign aid.
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SECTION 4 TRENDS IN FOREIGN AID FLOWS
Official development aid, comprising grants, and concessional and non-concessional
loans from bilateral and multilateral agencies, is an important source of financing for
development in developing countries. Aid is only one of the many sources of capital
flows into developing countries; however, it is the largest part of official flows. In this
section, we will examine recent trends in the flow of official aid. In doing so, we will first
highlight trends in aid flows globally and then focus on those specific to Guyana.
4.1
General Flows
According to the OECD, since the early 1970s, there has been an upward trend in the
volume of foreign aid, which peaked in 1991 when net flows reached US$71.2 billion16
in real terms (see Figure 1). The late 1980s and the early 1990s stand out as the period of
the most rapid growth in aid disbursements. Thereafter, until 2000 they declined or
stagnated. Two reasons proffered are the increased pressures on donors’ fiscal balance,
which reduced aid budgets; as well as the ending of the Cold War, which reduced the
need for “strategic” flows. Aid has only increased significantly again in 2001–2003, due
in part to growing allocations to debt relief (see figure 2), in response to civil society’s
16
All the data shown in this section, unless otherwise stated, are taken from the OECD online data base.
All dollar amounts are in constant 2003 prices. Net flows are the actual international transfer of resources
from donor to recipient, less any repayments on official development assistance loans from previous
periods. Total net aid is simply the sum of bilateral and multilateral aid.
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clamour for debt relief for poor developing countries17 and the new initiative for Heavily
Indebted Poor Countries (HIPC).18 So far the trend indicates that the amount of
development aid decreases as the amount of debt relief increases. Aid flows averaged
US$ 59.4 billion in real terms over 1990-2004 (years with high debt relief), while aid
flows averaged US$61.2 billion in real terms over 1980-1989.
Figure 1 Total Net ODA Flows to Developing Countries (1970-2004)
80000.0
70000.0
60000.0
Amount
50000.0
40000.0
30000.0
20000.0
10000.0
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
19
76
19
74
19
72
19
70
0.0
Year
17
Jubilee 2000, an international grass roots movement with a presence in more than 40 countries, has been
advocating for a debt-free start to the millennium for indebted poor countries.
18
HIPC Initiative is a framework adopted jointly by the IMF and the World Bank in 1996 for action to
resolve the external debt problems of heavily indebted poor countries. The Initiative envisages
comprehensive debt relief by the international financial community—including the multilateral
institutions—to achieve debt sustainability, provided a country builds a track record of strong policy
performance. The framework was strengthened in 1999 (enhanced HIPC Initiative) to provide faster,
deeper, and broader debt relief.
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Figure 2 Debt Relief to Developing Countries (1988-2004)
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
For developing countries as a whole, the majority of foreign aid has come from bilateral
sources (see figure 3). Between 1992 and 1997, total aid contribution from the
Development Assistance Committee (DAC) member countries to developing countries
and multilateral institutions fell steadily from 0.33 percent of their combined GNP to a
record low of 0.22 percent. Data from the Organisation for Economic Cooperation and
Development (OECD) show a temporary reversal of this trend in 1998 when aid flows
rose by US$3.6 billion (8.9 percent in real terms).
Total aid contribution from DAC
member countries in 1998 represented 0.24 percent of their combined GNP. Fourteen of
the 21 DAC member countries reported a rise in aid contributions in real terms, in 1998;
the most significant increases came from Italy, Japan, and the United States.
Nevertheless, much of this increase was support to Asian economies affected by the
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financial crises. Japan reported a US$1.2 billion rise in net aid flows in 1998, reflecting a
surge of aid to countries affected by the Asian crisis.
Some part of the rise in aid
reflected the commitment by some countries to increase their aid flows. The firmest
commitment seemed to be that of the United Kingdom, its aid in 1998 rose by 7.8 percent
in real terms. The emergence of the transition economies of Eastern Europe, which
resulted in some amount of diversion of aid away from developing countries, also
accounted for the decline in aid flows to developing countries. Aid contribution from
DAC countries continued the upward trend from the late 1990s. Real aid contribution
from DAC member countries in 2004 was 25 percent higher than in 2000. In 2000, aid
contribution was US$40.4 billion, while in 2004 aid contributions reached US$50.3
billion. The United States and the United Kingdom showed notable increases in their aid
contributions. Aid flows from multilateral sources remained relatively stable in the
1990s, while aid flows from non DAC member countries dropped significantly in the
1990s and remained low throughout that decade. In recent times there has been a modest
resurgence in flows from non DAC member countries, especially China.
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Figure 3 Net ODA Flow to Developing Countries by Category of Donor (1970-2004)
60000.0
50000.0
Amount
40000.0
Multilateral Total
30000.0
DAC Bilateral Total
Non DAC Bilateral Total
20000.0
10000.0
19
70
19
72
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
0.0
Year
Figure 4 Destination of ODA Flow (net) by Region
Africa,Total
Asia,Total
Middle East
Europe
South America,Total
70000
60000
50000
40000
30000
20000
10000
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
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Figure 4 shows that the majority of aid flows have gone to Africa and Asia in the last
fifteen years, while flows to South America remained small. In 2003 and 2004 flows to
the Middle East have grown, reflecting recent US interest in the region in its antiterrorism campaign. According to the Global Development Finance (2004) around 50
percent of the aid to Africa since 2001 was delivered through debt relief. Because of the
levels of poverty in Asia and Africa substantial contributions have gone to these regions,
particularly in the form of emergency humanitarian aid and assistance programmes in
such areas as poverty alleviation, education, human resources development,
environmental conservation, health care, and industrialisation.
Grants were the largest category of all official development flows throughout the 1990s,
(See Figure 5) peaking at US$35 billion in 1991. Net concessional flows declined during
the period 1990-2001, with its lowest value being US$9.5 billion in 1997. The fact that
grants dominate flows to developing countries is indeed a good sign, since with grants
recipients have no obligation in terms of repayment. The small value for concesssional
flow may also indicate outflows for debt servicing. Technical assistance remained quite
steady during the period 1990-2001.
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Figure 5 Net ODA Flows to Developing Countries byType
40
35
Amount in US$ Billion
30
25
20
15
10
5
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
Year
Grants
Concessional Loans
Technical Cooperation
Source: Global Development Finance 2005 CD-ROM
The United Nations (UN) has advocated that donor countries set a target level of aid
contribution equal to 0.7 percent of their GNP. The majority of DAC member countries
do not meet this target. In 2004, only five countries reached or surpassed the UN target:
Denmark contributed 0.84 percent, Norway 0.87 percent, Netherlands 0.74 percent,
Luxembourg 0.85 percent, and Sweden 0.77 percent. Even though the data show some
positive trends, this does not mean that developing countries will get more aid for
development projects.
A substantial amount of aid is now going to areas such as
Pakistan, Afghanistan, and Iraq in the aftermath of September 11 2001 event. There was
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also rising outlays of humanitarian aid in response to emergencies as opposed to aid for
long-term development.
To conclude, there has been a noticeable upward trend in the volume of foreign aid to
developing countries in the last five years. A significant portion came in the form of debt
relief. However, recent trends show that new disbursements decrease with increases in
debt relief. From the demand side, this situation does not augur well for developing
countries, in need new financial resources to fund development projects, especially in the
productive sector to realise sustained growth. The data also indicate that the majority of
foreign aid came from bilateral sources, and in the last five years there has been a clear
upward trend in aid from these sources. Despite the data reflect increases in aid volume,
this does mean that developing countries like Guyana will get more aid, since a
substantial portion is now diverted to other recipients that are now allies in the counterterrorism fight and to meet the growing demand for humanitarian aid in light of recent
natural disasters. These developments make it imperative for the Government of Guyana
to seek to form strong lobby groups and forge strong diplomatic links to secure generous
bilateral partners in its development drive.
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4.2
Trends in Aid Flows to Guyana
Looking closely at Guyana, it is evident that aid flows has not followed the same trend as
the aggregate trend of the rest of the Developing World. Net aid flows to Guyana were
lower in the 1980s, averaging US$64.8 million in real terms, compared to an average
US$128.5 million in real terms over the period 1990-2004, mainly due to the
government’s state-led inward-oriented policy, which was opposed to the market oriented
policy promoted by DAC bilateral and multilateral donors. Even if debt relief was
deducted from aid flows over the period 1990-2004, average flows (at US$85.0 million)
was still greater than that of the 1980s. With the introduction of structural adjustment
policies aid flows rose substantially in 1990s. Figure 6 gives a picture of volume of aid
flows to Guyana from 1970 to 2004. The chart shows peaks in 1990 and 1997. The peak
in 1990 was as a result of increased net inflows from multilateral sources to fund
Guyana’s arrears to multilateral financial institutions (see table 7 & figure 8).
A
significant amount of debt forgiveness accounted for the peak in 1997 (see figure 7).
Debt relief19 was a significant part of official flows in 1991, 1997, 1998, and 1999.
19
Debt relief here is being treated as stock of debt relief, that is, actual reduction in debt stock. Flow relief
was also given during the period, in the form of reduction of the interest rate and lengthening of the
repayment period.
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Figure 6 Total Net Aid Flows to Guyana 1978-2004
350
300
Amount
250
200
150
100
50
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
0
Year
Figure 7 Total Net Aid Flows to Guyana (Highlighting the share of Debt
Forgiveness) (1990-2004)
Net Aid flow s minus Debt Relief Grant
Debt Forgiveness Grant
350
300
250
200
150
100
50
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
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Multilateral Financial Institutions accounted for the majority of net flows, especially in
the 1980s (see figure 8). Surprisingly, flows from DAC Bilateral donors dwarfed those
from multilateral sources in 1997 reaching 233.5 million in real terms, due to debt relief
under Naples terms.20 However, flows from multilateral and bilateral sources appear to
converge from 1999. Guyana’s major DAC bilateral donors are the United States, the
United Kingdom, and Canada. These three donors contributed 96.5, 88.8, and 89.1
percent of total DAC bilateral flows (net) to the country in 1992, 1997, and 2002
respectively. In the early 1990s, the World Bank and the International Monetary Fund
were the major contributors of aid to Guyana, as they supported Guyana’s economic
recovery programme (see table 7). In recent times, the Inter-American Development
Bank (IDB) has assumed the role of the leading contributor of aid to Guyana. Since
1996, the IDB has given more aid to Guyana than any other multilateral financial
institution.
20
Naples terms refer Concessional debt-rescheduling terms for low-income countries approved by the Paris
Club in December 1994 and applied on a case-by-case basis. Countries received a reduction of pre-cut-off
date commercial (non-ODA) debt of up to 67 percent in net present value terms. These terms, along with
comparable action by other non-multilateral creditors, are known as traditional debt-relief mechanisms
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Figure 8 Net ODA flow to Guyana by Category of Donor (1978-2004)
Multilateral total
DAC Bilateral donors
Non DAC Bilateral Donors
250
200
150
100
50
-50
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2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
1979
1978
0
Table 7 Net ODA flows from Major Multilateral Donors
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
World
Bank
(IDA)21
65.8
46.2
4.22
32.57
12.52
16.37
15.63
19.22
9.5
7.16
6.01
8.63
6.66
IDB special fund
CDB
SAF+ESAF+PRGF(IMF)
22
4.24
1.88
25.06
21.18
14.75
17.52
54.05
31.49
19.44
34.38
59.27
57.06
27.91
0
4.78
3.6
-1.17
-1.64
0
0
0
2.97
3.14
4.36
5.36
5.02
45.94
26.23
27.21
13.85
13.76
13.1
14.06
8.94
-8.35
-10.94
-17.97
-23.88
-10.2
Figure 9 highlights the composition of aid commitments to Guyana. Data from the
OECD-DAC Creditor Reporting System indicate that project aid dominated allocated aid,
except in 1990, 1991, and 1997. A substantial amount of project aid was allocated to the
social sector (figure 10).
Some amounts of aid were also allocated for rebuilding
economic infrastructure and for the productive sectors.
21
The International Development Association (IDA) is the part of the World Bank that helps the earth’s
poorest countries reduce poverty by providing interest-free loans and some grants for programmes aimed at
boosting economic growth and improving living conditions
22
Structural Adjustment Facility (SAF)/Enhanced Structural Adjustment Facility (ESAF) - the SAF,
established in 1986 and no longer operational, and the ESAF, established in 1987 and extended and
enlarged in 1993, were the concessional loan windows of the IMF. Poverty Reduction and Growth Facility
(PRGF) a facility agreed in late 1999 replaced the Enhanced Structural Adjustment Facility (ESAF) as the
IMF's concessional lending arm; its goal is to make poverty reduction efforts among low-income members
a key and more explicit element of a renewed growth-oriented economic strategy.
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Figure 9 Composition of Aid Flows to Guyana 1990-2004 (Commitments)23
Project Aid (Sector Allocable)
Programme Aid
Debt Relief
300.0
250.0
Amount
200.0
150.0
100.0
50.0
0.0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Year
Figure 10 Distribution of Project Aid by Sector (commitment)
Social Sector including Health and Education
Environment Protection
Econonic Infrastructure
Production sectors
200
180
160
Amount
140
120
100
80
60
40
20
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Year
23
Commitments do not indicate actual disbursements. We use these figures in the absence of
disaggregated disbursement figures.
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Programme aid comprised budgetary support, food security, and other commodity
assistance. The bulk of allocated programme aid over the period 1990-94 was earmarked
for budgetary support. Budgetary support was the major part of allocated programme aid
in 1998, 2002, and 2004. Food security was a major part of allocated programme aid
over the period 1995-97 and 1999-2001.
Figure 11 Distribution of Programme Aid by Type
General Budget Support
Food Security Assistance
Other Commodity Assistance
160
140
Amount
120
100
80
60
40
20
0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
In sum, Guyana has received considerable amounts of foreign aid since the introduction
of structural adjustment programme. However, a significant amount came in the form of
debt forgiveness (an issue we will address in the next subsection). We noticed from the
data that the majority of foreign aid allocations were in the form of project aid, of which a
substantial portion was allocated to the social sector. This may explain the noticeable
improvements in the social indicators we alluded to in section 3. It should be noted
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however, that aid allocation to the productive sectors did not compare favourably with
investment in the social sector. Since investment in the productive sectors is a strong,
positive correlate of growth of output, ceteris paribus, it is vital that more aid be directed
to productive investment.
4.3 Debt Relief as Development Finance
In order to assess the usefulness of debt relief in the process of economic development, it
is important to determine the effect of debt on economic growth for the typical
developing country. In theory, the service of external public debt (outflows for payments
on interest and repayment of principal)—to be distinguished from the stock of external
debt—may affect growth by discouraging private investment or altering the composition
of public spending. Higher external debt servicing, ceteris paribus, can increase a
country's budget deficit, thereby reducing public savings. This, in turn, may either drive
up nominal interest rates or crowd out the credit available for private investment, thereby
depressing economic growth. Large debt-service payments can also inhibit growth by
squeezing the public resources available for investment in infrastructure and human
capital. Money freed by debt relief can be used for poverty reduction programmes and
sustainable development. Guyana became a recipient of debt relief from as early as 1991.
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In 1996, the international financial community recognized that the external debt situation
for a number of low-income countries had become extremely difficult and affected their
prospects for economic development. In September that year, the Interim and
Development Committees of the IMF and the World Bank endorsed a programme, jointly
proposed by the two institutions to address the situation. That programme, referred to as
the Initiative for the "Heavily Indebted Poor Countries" (HIPC), was designed to provide
debt relief to eligible countries following sound economic policies, to help them reduce
their external debt burden to sustainable levels. The 1999 Enhanced HIPC Initiative was
aimed at reducing the net present value of debt at the decision point to a maximum of 150
percent of exports and 250 percent of government revenue. To qualify for debt relief, the
country had to adopt adjustment and reform programmes supported by the IMF and the
World Bank and pursue those programmes for three years. During that time, the country
was expected to receive debt relief from Paris Club24 creditors and other official bilateral
and private creditors, as well as traditional concessional assistance from all the relevant
donors and multilateral institutions. Non-Paris club bilateral and commercial creditors
were expected to provide treatment comparable to that of the Paris Club creditors. 25 Of
these creditors, China, India, and Libya have indicated their intention to provide debt
relief in the context of the enhanced HIPC Initiative. According the IDB (2002), under
24
The Paris Club is an informal group of official creditors whose role is to find co-ordinated and
sustainable solutions to the payment difficulties experienced by debtor nations.
25
IMF & IDA (2003) inform that government bonds (formerly the debt of Guymine) with a face value of
US$27.5 million, which were bought by Citizens Bank and became domestic debt is not subject to debt
relief
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the original HIPC, Guyana received significant debt relief amounting to US$256 million
in net present value (NPV). By 2000, Guyana’s debt to government revenues ratio was
reduced to 348 percent from about 543 percent in 1998. Debt relief under the enhanced
HIPC Initiative from all of Guyana’s creditors amounted to US$329 million in NPV. By
the end of 2002, the total debt relief under the original and enhanced HIPC Initiatives
reduced Guyana’s debt stock by 54 percent. Debt relief, in addition to bilateral assistance
beyond HIPC relief, lowered Guyana’s debt to government revenue ratio to about 213
percent in 2003, 37 percent below the sustainability threshold for countries that qualify
under the fiscal window.
To summarise, we highlighted that theoretical concepts state that debt relief can lower
external debt servicing, thereby making more resources available for investment in longterm growth and fund poverty alleviation strategies. In this regard favourable debt relief
extended to Guyana in the last decade should be seen as useful in creating the necessary
conditions conducive to economic growth. It is therefore, now important for government
to continue to improve its track record of economic policy reforms necessary for growth
so as to acquire further debt relief and attract new official inflows; while simultaneously
ensuring that the country does not violate the prudential standards of creditworthiness.
Government, therefore, has to be very careful that debt relief is not accompanied by new
borrowing which restore the old ratio of debt to GDP or debt to export. In this regard
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government should set debt ratio targets, that is, seek credit in which its debt to GDP ratio
is at some manageable proportion.
4.4
Migrant Remittance Flows
Generally, in developing countries net factor payment to foreigners tends to be high,
mainly due to payments on foreign debt. For some of these countries remittances in the
form of labour income from residents working abroad is a major source of foreign
exchange and may even offset the interest payments to foreigners. It is because this type
of finance has assumed major importance in Guyana’s economy that we turn our
attention to it.
According to the Global Development Finance (2003) global flows of remittances have
become a larger and more important source of external finance for poor countries, in the
last five years. Remittances are also more stable than private capital flows, which often
move pro-cyclically -raising incomes during booms and depressing them during
downturns. By contrast, remittances are less volatile, and may even rise, in response to
economic cycles in the recipient country. The report further states that remittance flows
are the second-largest source, behind FDI, of external funding for developing countries.
In 2001, workers’ remittance receipts of developing countries stood at $72.3 billion,
much higher than total official flows and private non-FDI flows, and 42 percent of total
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FDI flows to developing countries. Remittances, simply put, are sums of money that a
migrant worker sends back to his or her country of origin. The sum of money can serve to
augment the income of the receiver and increase the recipient country’s foreign exchange
reserves. Remittance transfers are a crucial source of income to developing countries’
economies, as well as to millions of individual households. The literature on remittances
has shown that these flows have an important macro-economic impact. Remittances often
provide a significant source of foreign currency, increase national income, finance
imports, and contribute to the balance of payments. High levels of remittances can serve
to improve the standard of living of households, which can also trigger a positive effect
for the local economy due to increased consumption and investments. Jamaica is an
example of a country whose economy has benefited from inflows of remittances.
According to the Jamaican Gleaner (03-2003), in 2002 remittances were the largest
source of net foreign exchange, exceeding those earned from tourism and accounting for
12.2 percent of Jamaica's gross national product. Orozco points out that Guyana has
benefited in large way from remittances. He further adds that remittances along with
bank deposits from Guyanese living abroad are both an important source of foreign
exchange and has increased national saving rates. Even though official statistics report
workers remittances and migrant transfers at around US$55 million in 2001, Orozco
(2003) estimates these flows to be almost US$90 million. He reports that in that year
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remittances to Guyana26 were 16 percent of merchandise exports, 83 percent of official
development assistance, 134 percent of foreign direct investment, and 13 percent of GDP.
All in all, remittances have become an important and stable source of development
finance for developing countries in the last decade. Remittances have improved the
standard of living of households and have simultaneously had a positive macroeconomic
impact. Remittances flows, indeed, can result in higher rates of inflation, but this not
always so, since timely and prudent government intervention can eliminate the
disincentive effects of remittances.
4.5 Recent Initiatives, Issues, and the Prospects of Aid to Guyana
Recent initiatives have improved the prospects for increase in aid volume to Guyana. At
the Millennium Summit in September 2000, the world's leaders set seven goals (known
as the Millennium Development Goals) for the international community to meet by the
year 2015 that add up to a determined agenda for reducing poverty and its causes and
manifestations. An eighth goal related to the development of global partnership for
development was later added. A United Nations Development Programme (UNDP)
sponsored conference bringing together government officials from around the world and
representatives from the international financial institutions to discuss the challenges of
26
Using his estimates, which were computed using data from commercial banks and money transfer
companies.
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increasing financing for development was held in Monterrey, Mexico, in March 2002. At
this session the participants affirmed that a substantial increase in ODA and other
resources will be required if developing countries are to achieve the internationally
agreed development goals and objectives in the Millennium Declaration. Donors’
pronouncement that most of the new funding will go to poor developing countries, augurs
well for Guyana. In addition, in the last five years Guyana has received development
assistance from non-traditional donors, particularly China and India. Guyana has also
received “in-kind” aid from Cuba, in recent times.
These new developments are
encouraging, especially in light of declining aid from traditional bilateral donors.
Beginning in 2004, the United States’ President, George W. Bush, established a
Millennium Challenge Account (MCA) aimed at providing substantial new foreign
assistance to low-income countries with good governance, investing in their people, and
encouraging economic freedom. Pasicolan and Fitzgerald (2002) elucidate that the
significance of the proposed programme lies partly in its scale: the proposed $5 billion
annual budget represents a near doubling of US bilateral assistance aid that focuses
strictly on development objectives.
However, even more important than its size,
however, is that the MCA brings with it the opportunity to improve significantly the
allocation and delivery of U.S. bilateral assistance because it has narrower and more
clearly defined objectives, aims solely at supporting economic growth and development;
and providing assistance to only a select group of low-income countries that are
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implementing sound development policies. The MCA also engenders lower bureaucratic
and administrative costs than other aid programmes and recipient countries have greater
say in programme design, implementation, and evaluation to improve programme
efficiency and effectiveness.
Another recent development is the Global Fund to Fight AIDS, Tuberculosis, and
Malaria, established in Geneva, Switzerland, in January 2002. The Global Fund to Fight
AIDS is a public-private partnership intended to attract and rapidly disburse new
resources to developing countries for the struggle against infectious disease. The Fund is
a financing vehicle, not a development agency, and it makes grants in developing
countries aimed at reducing the number of HIV, tuberculosis, and malaria infections, as
well as the illness and death that result from such infections. In addition, the World Bank
has dramatically expanded its support for HIV/AIDS programmes, and intensified its
activities as a cosponsor of the Joint United Nations Programme on HIV/AIDS
(UNAIDS). The Bank’s finance, influence, country presence, multi-sector scope, analytic
skills, and ability to support effective implementation, provide a unique capacity to
contribute to the global effort against AIDS.
Next, there is the Multilateral Debt Relief Initiative (MDRI), the latest development in
debt reduction for poor countries from the World Bank, the IMF, and the Regional
Development Banks, aimed at providing full debt reduction for about forty qualifying
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countries. Debt relief proponents see this as a significant scheme in reducing the debt of
low-income countries. Prior to this initiative, HIPC countries were getting cancellation of
almost all of their bilateral debts but far less cancellation of multilateral debts, thus, this
focus on multilateral debt is an encouraging development.
The international community has also committed itself to improving the quality of aid,
through various initiatives, notably the Rome Declaration on Harmonisation. The
deliberations focused on an international effort to harmonise the operational policies,
procedures, and practices of donor institutions with those of partner country systems to
improve the effectiveness of development assistance, and thereby contribute to meeting
the Millennium Development Goals (MDGs). Another positive feature is the increase in
the grant element of flows. In the 1980s, the average grant element of official loans to
Guyana was 38 percent, compared to 68 percent over the period 1990-2002. Increase
concessionality reduces the possibility of unsustainable debt.
The relatively large amounts of aid finance flowing to Guyana require careful
management. However, there is a growing local perception, expressed in public
consultations27 (Renshaw, 2006), that these flows are failing to contribute to growth and
poverty alleviation because of poor choice of development projects, weak
implementation capacity, sub-standard work by contractors, and corruption. The World
Bank (2003) stresses “if Guyana’s three decades of large aid flows had been used
27
Similar views have been expressed at the consultation on the PRSP.
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effectively…per capita incomes would most likely be now close to the top of the
Caribbean range.”28
Summing up, there are a number of new initiatives that can improve the quality and
quantity of aid flows to Guyana. This is encouraging in light of Guyana’s need for more
resources to fund its development programmes aimed at sustaining growth.
4.6
Conclusion
What can we infer from the trends in foreign aid and remittances flows to Guyana?
There appear to be one inescapable conclusion from the preceding data. Given the
magnitude of these flows, it is highly likely that they would have a significant
macroeconomic impact. While the size of aid flows is to be welcomed, there remain
considerable challenges that both international donors and the Government of Guyana
must address so that the country can derive optimum benefits from it.
28
The World Bank, 2003, p 18.
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SECTION 5 FOREIGN AID AND ECONOMIC GROWTH: THEORETICAL
FRAMEWORK AND A REVIEW OF EMPIRICAL STUDIES
There is a large and growing body of literature that examines how foreign aid affects
economic growth.
This section will provide a brief survey of the major works on this
topic. As far as possible, we will attempt to present them following a chronological
sequence. Both theoretical and empirical models have been developed to capture the
impact of aid on economic growth and other macroeconomic variables such as savings
and investment.
The last twenty years have witnessed new approaches to the
understanding of the relationship between foreign aid and economic growth, especially,
the importance of policy and institutional variables such low inflation, trade openness,
and democratisation. Before we review the literature on aid effectiveness, we present a
succinct history of foreign aid.
5.1
A Brief History of Foreign Aid
There are two major events in the evolution of aid. One, the Marshall Plan, which
represented bilateral assistance from the United States to countries in Europe to aid in
their reconstruction after World War II, and two, the setting up of the United Nations and
the Bretton Woods institutions (World Bank and the International Monetary Fund), which
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represented the multilateral approach to development assistance. The primary objective
of those initiatives was the reconstruction of war-ravaged Europe.
Spero (1981)29 states that during the 1940s, developed countries in a position to transfer
funds to developing countries, rejected aid as an instrument of development. Policy
makers in the United States believed that domestic efforts in low-income countries, not
external capital, were the primary means of economic development. Whenever there was
a need for external capital to enhance growth and development, it was believed that this
capital should have been private. Thus, to raise the level of growth and development, less
developed countries were expected to take steps to stimulate the flow of private capital.
Doing so required, among other things, a favourable investment climate, which meant
minimising the role of the public sector in economic activities, following internationally
accepted fiscal and monetary policies, and rejecting expropriation. While recognising the
need for some amount of official external finance, it was believed that such financing
should be limited in amount and should be offered on market or hard, not concessional or
soft, terms.
With the institutionalisation of the Cold War, when the strategic significance of
developing countries became fully appreciated, developed nations changed their policy
with respect to aid to those countries. Because of the Soviet Union’s interest in forming
29
Joan Spero, 1981, The Politics of International Economic Relations, (New York: St. Martin’s Press), p.
148.
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strategic alliances with developing countries, policy makers in the United States began to
consider aid as a means of cementing alliances with those same countries. The change of
heart in United States policy with respect to foreign aid was matched by a similar change
in policy in other developed countries.
A corollary of this shift in the foreign policy of developed countries was the expansion of
bilateral and multilateral aid programmes. The United States’ demand for burden sharing
was one factor behind the establishment of bilateral aid programmes at the end of the
1950s and into the 1960s, and was the impetus behind the formation of the Development
Assistance Group in 1960, which later became the Development Assistance Committee
(DAC) in 1961, to monitor aid performance and the latter’s adoption of the 0.7 per cent
of GNP as a target for aid contribution.30
Ravi Kanbur (2003) provides a useful account of the history of aid during the decades of
the 1960s, 1970s, and 1980s. He explains that the 1960s and 1970s saw the expansion of
bilateral assistance, as did the assistance from multilateral institutions, particularly the
World Bank. New multilateral agencies were set up so as to reduce the coordination and
other problems of a multitude of individual aid programmes. Kanbur explained that
instead of just focusing on growth of overall national income, the attention shifted to
poverty and the social sectors. The 1980s, he said, saw the peak of the “structural
30
Peter Hjertholm and Howard White, 2000, “Survey of Foreign Aid: History, Trends and Allocation,”
Online: http://www.econ.ku.dk/wpa/pink/2000/0004.pdf
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adjustment” aid doctrine, where transfers were made increasingly in the form of
budgetary support. The Latin American debt crisis of the early 1980s was a part of the
development aid discourse. Support for debt relief was conditioned on policy reforms.
The 1990s was the decade that witnessed a change in donors’ motivation for giving aid
from geo-political concerns to focus more on economic growth and development, and
poverty reduction. Until the 1990s, Cold War concerns, rather than economic growth and
development, was the primary motivation for foreign aid. The end of the Cold War saw a
reduction in the volume of foreign aid and recipients’ ability to manoeuvre among
donors. The donors most involved in the Cold War, the United States and the Soviet
Union, reduced their budget with the end of the ideological clash. Another change in the
aid scenario occurred when many OECD countries, in an effort to lower their fiscal
deficits, reduced their aid contribution. Finally, the emergence of the Eastern European
countries, after the break-up of the former Soviet Union, resulted in the diversion of some
amount of aid from the traditional recipients. While new recipients were added, no new
source of aid was found, leaving virtually the same amount of aid to be shared amongst
an increasing number of countries. Because of strategic alliances, countries of Eastern
Europe were now favoured compared to countries like Guyana
In sum, prior to the institutionalisation of the Cold War, policy makers in developed
countries rejected the notion of giving aid to developing countries to fund their
development, believing rather that domestic efforts were more critical to their
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development thrust. However, Cold War geo-politics resulted in a reversal in the policy
of developed countries with respect to aid to developing countries. With the end of the
Cold War, developed countries reduced their aid contributions and at the same time there
was some amount of diversion of aid flows away from traditional aid recipients to new
recipients, mainly the newly independent Eastern European states.
5.2
Foreign Aid, Economic Growth and the Dual Gap Theory
The importance of foreign aid to economic growth can best be recognised from an
understanding of the dual gap theory. The dual gap theory states that foreign resource
inflows allow a country to invest more by making more finance available (narrowing the
saving-investment gap) and by providing foreign exchange (relaxing the foreign
exchange gap). In this model, aid acts as an increment to investment, relaxing either the
savings or foreign exchange constraint, and leads to growth. The traditional dual gap
theory, which builds upon the Harrod–Domar model, assumes that foreign resource
inflows will act as a supplement to domestic savings and hence accelerate growth.
Gap studies assume that aid plays an important role in accelerating economic growth in
developing countries. For example Newlyn (1977), echoing Chenery and Strout, argues
that in the early stages of development, domestic savings in many developing countries
are too low to mount an adequate investment effort, therefore external capital resources
are necessary to allow the country to grow. Foreign aid is considered therefore to be of
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major importance, since it has the potential to raise investment and absorptive capacity if
it is efficiently used to stimulate developing countries to make the necessary economic
adjustments. White (1992) points out that the dual gap model assumes that governments
want to maximise investment.
However, economic practice has demonstrated that
governments may use this opportunity to increase non-developmental expenditures, lower
taxes, or reduce borrowing.
Hollis Chenery and Alan Strout (1966)31 develop an intellectual framework from which
to judge the effectiveness of foreign aid in simulating economic growth in developing
countries. They believe that external capital can be effective in removing the savings
constraint and the foreign exchange constraint. They argue that domestic savings in most
developing countries are not sufficient to finance and support the huge needs for
investment required for economic development. Thus, the resort to foreign capital is
inevitable to fill this insufficiency by boosting domestic savings, hence investment and
production.
Chenery and Strout find that recipients of foreign aid achieve average
growth rates higher than they would in the absence of such inflows. These authors
provide a list of policy prescriptions for both donors and recipients. They suggest that
donor countries should tie future aid levels to the recipients’ effectiveness at increasing
their level of domestic savings and investment rates. For the recipients, they suggest that
they must undertake institutional reforms to ensure their success at economic
31
W. T. Newlyn, 1977, pp. 93-96.
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development. Specifically, efficient tax collection, and private savings, investment, and
export promotion were the policy prescription for aid recipients.
Griffin (1970)32 provides a contrasting view of foreign aid and its contribution to
economic growth in developing countries. He argues that aid depresses domestic savings
and an increase in aid would generate less than one-for-one increase in investment.
Griffin states that an anticipated aid inflow would be treated as an increase in income and
so allocated between both savings and consumption. As such there is no longer a one-toone relationship between aid and investment. Aid here is seen as a free resource, which
may be allocated as the recipient sees fit.
Gustav Papanek (1973) analyses the effect of foreign aid on growth. He uses data
covering the period 1955-1965 for a sample of thirty four (34) Least Developed
Countries (LDC), in a linear regression model to measure the effect of foreign aid on
economic growth. Papanek regresses savings, foreign aid, foreign direct investment, and
other foreign inflows on the annual growth rates of gross domestic product. His results
indicate that foreign aid possesses a statistically significant relationship with economic
growth. Even though he claimed that the results were only suggestive, it appeared to
32
K. Griffin, 1970, “Foreign Capital, Domestic and Economic Development” in H. White “The
Macroeconomic Impact of Development Aid: A Critical Survey,” Journal of Development Studies, Jan.
1992 Vol 28 No. 2. pp. 6-8.
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have overturned the negative results of Griffin (1970). Papanek explained his results by
pointing to the role of aid in filling the two gaps mentioned by Chenery and Strout.33
The gap-model envisages a positive role for foreign aid, because aid supplements
domestic savings and export earnings, thus raising investment and imports and,
consequently, growth.
However, because of a number of criticisms levelled at the gap
model in its original form, the focus of aid effectiveness research shifted away from the
gap model towards more sophisticated models based on new growth theories, where
economic policies and institutional development were seen as important determinants of
growth performance. In the next subsection we will review some of these studies and
provide a synthesis of the arguments.
5.3
New Approaches to Studying Aid Effectiveness
The recent literature on the effectiveness of aid reflects developments related to the wider
literature on comparative growth performance.
More recent empirical works have
focused on the effect of the macroeconomic environment on the utilisation of foreign aid.
For example Boone (1996) hypothesises that the effectiveness of foreign aid is a function
of political regimes, while Burnside and Dollar (1997) propose that the institutional
quality of foreign aid recipient affects its effectiveness. A new role for aid has been
33
W. Newlyn, 1977, p. 133.
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ascribed. It was now seen as income transfer, compensating for imperfect capital markets
and creating self-sustaining growth.
Mosley et al. (1987)34 examine the effect of aid on the spending pattern of the public
sector of the recipient country. They apply both Ordinary Least Square (OLS) and Three
Stage Least Square (3SLS) regression technique to estimate the impact of aid on growth
using data averages over the period 1970–1980 for sixty three (63) countries. Neither
method yields a statistically significant correlation between aid and growth. The authors
conclude that this result indicates the possible leakage of aid to non-productive
expenditures in the public sector and the crowding out of private investment in the private
sector. They recommend that donors concentrate development aid on countries that meet
certain criteria for high effectiveness of aid such as the estimated rate of return on
investment, proportion of aid allocated to ‘non-productive’ recurrent expenditure,35 and
the estimated impact of development aid on the private sector. These authors affirm the
fungibility of aid within the public sector as the factor that negates aid effectiveness.
34
P. Mosley, J. Hudson, & S. Horrell (1987). “Aid, The Public Sector and The Market in Less Developed
Countries,” in M. Tsikata, 1998, “Aid Effectiveness: A survey of the recent empirical literature,”
(International Monetary Fund, Policy and Review Department), p. 11.
35
High proportion of aid used for recurrent public expenditure negatively affects the impact of aid on
growth.
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In a follow-up study,36 seeking to examine the role policy orientation plays in
determining the effectiveness of aid, they include an index of policy orientation in the
aid-growth regression. They reason that aid effectiveness and policy orientation depend
on the stage of development of the recipient country, which they argue can explain the
lack of significant association between aid and growth observed in cross country
regressions. They propose the following four stages of aid effectiveness:
(i)
low aid, low growth stage where a near subsistence economy is cut off from
aid because of war, political instability, or economic mismanagement, a
typical example is Haiti;
(ii)
high aid, low growth stage in which increased aid flows have no immediate
impact because of gestation lags etc, Uganda is a typical example;
(iii)
high aid, high growth stage in which aid flows remain high, and became more
effective as lags unwind, a typical example is Botswana; and
(iv)
low aid, high growth stage in which aid diminishes but growth continues at a
high pace, Barbados is a typical example.
The conclusion of these authors is that the impact of aid on growth is specific to a
country (linked to the fungibility of aid in the public sector) and to the country’s stage of
development.
36
P. Mosley, J. Hudson, & S. Horrell, 1992, “Aid, The Public Sector and The Market in Less Developed
Countries: A Return to the Scene of the Crime,” in M. Tsikata, 1998, “Aid Effectiveness: A survey of the
recent empirical literature,” (International Monetary Fund, Policy and Review Department), pp. 11-12.
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Another approach is adopted by Boone (1996).37 He seeks to relate the effectiveness of
foreign aid programmes to the political regime of recipient countries. Boone employs
data covering the period 1970-1992 for a sample of fifty six (56) least developed
countries to examine the issue of aid effectiveness. After constructing a three-part regime
typology, he argues that various regime types will utilise foreign aid in different manners.
An elitist government will maximise the welfare of a fixed ruling coalition; the
egalitarian government tries to maximise the welfare of poor households in an attempt to
ameliorate poverty; and the laissez-faire government will maximise the welfare of a
minimum fraction of the population. He utilises an augmented version of Robert Barro’s
model of government decision-making, where government uses taxation to raise funds for
public goods. In Barro’s framework,38 a generous government determines the level of
taxation by maximising the utility of a representative household.
To determine if
particular forms of government use foreign aid more effectively than others, Boone
regresses, first an interaction term of foreign aid and an indicator ranking political rights,
then an interaction term of foreign aid on each of the following: consumption, policy and
welfare indicators. Boone finds that models of elitist political regimes best predict the
impact of foreign aid. He contends that aid does not significantly increase investment and
growth, nor benefit the poor as measured by improvements in human development
37
P. Boone, 1996, “Politics and the Effectiveness of Foreign Aid,” European Economic Review 40, pp.
289-329.
38
R. Barro. (1990), “Government Spending in a simple Model of Endogenous Growth”, Journal of Political
Economy, 98 (2): pp. 103-125.
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indicators, but it does increase government consumption. Even though in some instances
increased government consumption can have a positive impact on the economy, the
author shows that the increase consumption in this study is not useful, given that aid does
not improve human development indicators.
Lensink and White (1999) in critiquing Boone’s work, feel that it suffers from a number
of methodological shortcomings which render his result irrelevant for most developing
countries. Lensink and White explain that Boone assumes that all countries are in steady
state long run equilibrium when in reality this is not the case. Boone’s uses instrumental
variables in his model (so as overcome the simultaneity problem), thus the effects of aid
only refer to the steady state effects of aid; and the much more important transitional
effects of aid were ignored due to his choice of instruments.
Lensink and White
conclude, “This assumption makes Boone’s results of little value since most developing
countries will still be on a transition path towards the steady state.” 39
Burnside and Dollar (1997)40 examine the influence of recipient country’s policy
environment on the effectiveness of foreign aid with respect to economic growth. Their
model reflects a modified neoclassical framework in which aid acts as an income transfer
to compensate for the imperfect capital markets. In this framework, aid can only be
39
R. Lensink and H. White, 1999, “Aid, Dependence, Issues and Indicators,” p. 61.
40
C. Burnside and D. Dollar, 1997, “Aid, policies, and growth,” (World Bank Policy Research Working
Paper 1777).
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effective if it is used for productive expenditures. The neoclassical theory advocates that
poor countries should have a high return to capital and a fast growth rate in transition to
steady state; however, there are several factors that could interfere with this result. With a
subsistence consumption constraint and imperfect international capital markets, poor
countries will tend to grow slowly despite a high marginal return to investment. In this
context, foreign aid can accelerate growth rates in the transition to a steady state.
Furthermore, various institutional and policy distortions can lower the return to capital
and reduce transitional growth rates. Burnside and Dollar posit that in such a model the
impact of aid will be greater in a low distortion environment. In general, developing
countries’ growth rates will depend on initial income, institutional and policy distortions,
aid, and aid interacted with policy.
To investigate this model empirically, Burnside and Dollar (1997) use a new database on
foreign aid developed by the World Bank, where aid flows are defined as the grant
component of concessional loans plus full grants.41 They utilise recent empirical growth
literature to develop a model with a range of institutional and policy distortions, and
estimate the equation derived from the model in a panel with fifty six (56) countries and
six four-year time periods from 1970-73 until 1990-93. Aside from institutional/political
variables, the policies that have considerable weight in their equation are the budget
41
C. Chang, E. Fernandez-Arias, and L. Serven, 1997, “Measuring Aid Flows: A New Approach,” (World
Bank, mimeo, Online: ideas.repec.org).
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surplus, inflation, and the trade openness dummy developed by Sachs and Warner. 42 The
authors form an index of these three policies and interact it with foreign aid. Burnside and
Dollar conclude that foreign aid does have a positive effect on economic growth when the
necessary institutions and policy frameworks exist. Foreign aid facilitates economic
growth in an economic environment with good fiscal, monetary, and trade policies.
Lensink and White (1999) argue that Burnside and Dollar (1997) model suffer from
omitted variables. They validate their position by pointing out that in the Burnside and
Dollar growth regressions, the coefficients of the initial GDP variables are all negative,
but insignificant. According to the neoclassical growth theory, these coefficients are
significantly negative.
In Burnside and Dollar (1997) we observe that there is no
allowance for lagged aid to affect growth, but it seems plausible that the impact of some
aid projects would take years to develop.
Durbarry et al. (1998)43 seek to assess the impact of foreign aid on growth for a large
sample of developing countries, within augmentations of two prominent endogenous
growth models: the ‘Fisher-Easterly model’ and the ‘Barro model’. The Fisher-Easterly
model stresses the role of stable macroeconomic policies for sustained growth. The
42
Sachs, Jeffrey and Andrew Warner, “Economic Reform and the Process of Global Integration,”
Brookings Papers on Economic Activity, 1995:1, pp. 1-118.
43
R. Durbarry, N. Gemmel, & D. Greenway, 1998 “New Evidence on the impact of foreign aid on
economic growth,” (Credit Research Paper 98/8, Online:
http://www.nottingham.ac.uk/economics/credit/research/papers/cp.00.17.pdf).
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authors employ both cross-section and panel data techniques using data from sixty eight
(68) developing countries for the period 1970-93. They use annual data to construct four
periods (averages over six years) and two hundred and thirty eight (238) observations. In
addition, they use a Papanek-inspired decomposition of investment but allow for possible
non-linear effects of aid on growth by including a squared aid term. Durbarry et al argue
that because of the limited absorptive capacity of developing countries, the possibility of
non-linearity in the aid-growth relationship should be recognized from the outset. Their
results are in keeping with Burnside and Dollar’s findings that foreign aid has a positive
impact on growth, conditional on a stable macroeconomic policy environment. While
low amounts of aid do not appear to generate faster growth, very high aid/ GDP ratios are
also associated with slow growth. Their results identify an optimum aid volume around
40-45 percent aid GDP ratio.
Henrik Hansen and Finn Tarp (2000)44 consider three generations of empirical crosscountry work on aid effectiveness. Their survey covers 131 first and second-generation
regressions, available in the literature, and compares them with third generation work in a
common analytical framework.
They describe the analytical underpinnings of each
generation and provide an encyclopaedic survey of work in each. They find a consistent
pattern of results that aid increases aggregate savings and investment; and there is a
44
H. Hansen and F. Tarp, 2000, “Aid Effectiveness Disputed,” (Online:
http://www.econ.ku.dk/derg/papers/Aid_Effectiveness_Disputed.pdf).
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positive relationship between aid and growth in reduce form models. They posit that the
positive aid-growth link is a robust result from all three generations of work. Hansen and
Tarp (2000) contend that there is no micro-macro paradox45 to resolve, not even in
countries hampered by an unfavourable policy environment. These authors offer some
useful insights into the aid effectiveness policy debate, by stating that while the extreme
view that aid can only work in an environment of sound policy appears wrong, this is not
to say that economic policies have no impact on the marginal productivity of aid.
Lloyd et al (2001)46 study the impact of aid on growth in Ghana via its effect on
government spending using time series analysis. Using data from 1970 to 1997 they find
that exports, aid, and public investment all are positively related to long run growth. The
authors incorporate policy through interactive dummies for the period 1983 (adjustment
and post-adjustment). The possibility that policy reform following structural adjustment,
initiated in 1983, created a more favourable environment for growth is incorporated
through the use of a qualitative variable (taking the value of 1 for 1983 and subsequent
years). In the pre-1983 period, export and public investment have a negative impact on
short-run growth, while aid has no significant impact. Results for the post-1983 period
suggest that policy reform enhances the effectiveness of exports, public investment and
aid, all of which have a significant positive impact on short-run growth. The results of
45
There is a widespread perception that contradiction exists between the results of microeconomic and
macroeconomic studies on aid effectiveness.
46
T. Lloyd, O. Morrissey, and R. Osei, 2001, “Aid, Exports and Growth in Ghana,” (Credit Research
Paper, No. 01/01, Online: www.nottingham.ac.uk/economics/credit/research/papers/cp.99.3.pdf).
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this study seem to reinforce the view that policy can play an important role in enhancing
the effects of aid.
Xayavong (2002)47 re-examine the effectiveness of aid focusing on the interactive effect
of aid and policy conditionality on sustainable economic growth.
Using data from the
Lao People’s Democratic Republic’s economy for the period 1978-2001, he finds that
stable, moderate aid inflows boost economic growth even when aid is fungible.
The
author also reveals that failure to complete the policy conditionality owing to inadequate
policy design and problems of policy mismanagement caused by lack of state and
institutional capability in recipient country trigger unstable aid flows.
An innovative cross-country study by Jean-François Ruhashyankiko48 explores the link
between aid dependence, i.e. the proportion of aid to GDP (which averaged 11.5 percent
for IDA countries and 1.4 percent for non-IDA countries), and the growth prospects for
developing countries using annual data from 1984-2002. He contends that trends in aid
dependence introduce some heterogeneity across aid recipient countries that result in
differential impact of aid on growth in different countries. Two of his findings are
relevant to the present discussion. One, there is a positive aggregate impact of aid on
growth; and two, past trends of aid dependence are strong predictors of aid effectiveness.
47
V. Xayavong, 2002, “A Macroeconomic Analysis of Foreign Aid in Economic Growth and Development
in Least Developed Countries: A Case Study of Lao People’s Democratic Republic (1978-2001)” (Online:
http://www.dev-zone.org/kcdocs/devnet366_thesis.pdf).
48
Jean-François Ruhashyankiko, 2005, “Why Do Some Countries Manage to Extract Growth from Foreign
Aid?” IMF Working Paper WP/05/53.
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In this regard he presents four categories of aid recipient. Category 1, which includes
Botswana, Barbados, and Grenada, are countries where aid dependence falls over time.
These countries manage to extract growth from foreign aid and are strong performers
over time with 1.2 percent higher real GDP growth per annum. Category 2, which
includes Guyana, St. Lucia, and Haiti, are countries where aid dependence neither rises
nor falls over time, these countries do not manage to extract growth from foreign aid and
are neither better nor worse performers over time. Category 3, which includes Cameroon,
Vietnam, and Algeria, are countries that aid dependence rises over time, these country are
neither less able to extract growth from aid than the average aid-recipient country.
However, these countries are significantly worse performers over time with about 1.4
percent lower real GDP growth per annum. In his robustness check, 29 countries were
eventually screened out because of the endogeneity of aid, i.e. growth significantly
affects aid. These countries were placed in Category 4, which includes Peru, Bahamas,
and Guatemala.
Ruhashyankiko proves empirically that aid mediated through
sufficiently credible government can boost growth, but this growth cannot be sustainable
over time, unless the country becomes aid-independent. He, however, does not offer an
aid dependence threshold, claiming rather that unobservable country-specific effort,
create different threshold of aid dependence across countries.
Finally, three perspectives emerge from this analytical review. One, the analysis that aid
has a positive growth impact appears stronger even though several caveats surround such
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findings.
Two, several questions surround the choice of policy variables and the
definition of what is really “good policies”. The policy variables utilised in the studies
reviewed are narrow when compared to the overall set of policies recommended in the
structural adjustment programme.49
Three, there is much disagreement over the
appropriate econometric methodology and model specification.
49
The regressions used a policy index, which was calculated from inflation, budget surplus, Sachs-Warner
trade openness index and institutional quality. The four measures included in the regressions leave out
some of the main components of the structural adjustment programme, such as liberalisation of financial
and foreign exchange market, privatisation and tax reforms
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SECTION 6 EMPIRICAL ANALYSIS
The purpose of this section is to answer the question: what has been the growth impact of
foreign aid flows to Guyana? To do this, we will construct an empirical model and test it
using data for the period 1978-2002. This period was selected both because of the
completeness of the data set for all variables, and the emergence of the economy from a
deep trough brought about by years of inward looking economic policies and further
economic contraction brought about by structural adjustment measures which began in
the late 1980s as a means of achieving high and sustained economic growth.
6.1
Modelling the Aid-Growth Regression
The earliest growth model of the aid-growth regression focused on the aggregate output
and resource mobilisation. The analytical framework applied to investigate the aidgrowth nexus was the Harrod-Domar model, in which production technology and the
capital-labour ratio are assumed to be fixed and capital accumulation is essential for
growth. This model is premised on the view that savings provide the funds which are
borrowed for investment purposes. The economy's rate of growth depends on the level of
saving, the savings ratio, and the productivity of investment in the economy (capitaloutput ratio). If there is a shortage of domestic saving for investment, then growth can be
constrained.
Foreign capital, such as aid, can be introduced to compensate for the
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shortage of domestic savings. The model also assumes that there is an unlimited supply
of unemployed labour, not unlike the situation in Guyana. 50 Since labour is always
available, this keeps the capital – labour ratio constant; therefore, each additional unit of
capital would raise output by the same amount. Output, then, is a constant function of
capital stock. Expressed algebraically:
Yt = f (Kt)
…………………………………………………..Equation1
Where:
Yt is aggregate output at time t
and Kt is capital stock at time t
Although heavily criticised,51 this production function is typical of developing countries,
which are known for surplus of labour and shortage of capital. Differentiating equation 1
with respect to time (t) and dividing by Y, gives the growth rate of output as follows:
∆Y =
Y
1
∆K/∆Y
.
1
Y
…………………………………….Equation 2
Where:
∆Y/Y is the growth rate of output
∆K/∆Y is the incremental capital – output ratio (ICOR)
50
W. A. Lewis, 1954, “Development with an Unlimited Supply of Labour,”: Online:
(www.eco.utexas.edu/facstaff/Cleaver/368lewistable.pdf).
51
W. Easterly, 1997, “The Ghost of the Financing Gap: How the Harrod-Domar Growth Model Haunts
Development Economics,” (World Bank Policy Research Working Paper 1807).
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and I/Y is the ratio of investment to output
The Harrod-Domar result indicates that increasing investment will increase economic
growth. By definition, investment (I) is given as I = S + A, where
S is domestic saving
and A is foreign savings, i.e. capital inflows.
In the early 1960s, developing countries’ capital inflows were most likely to take the
form of foreign aid, and so conventional wisdom was that more foreign aid would lead to
higher economic growth. This model was extended by Chenery-Strout to include the
financing constraint in their two-gap model.
The apparent impact of aid on growth is
generally seen as an increment to the stock of physical capital, and can be captured in the
planned investment identity, as follows:
I = Sd + A + OF ……………………………………………….Equation 3
Where:
Sd - domestic saving
A - the inflow of aid
and OF - other sources of capital inflows
Assuming that the incremental capital-output ratio (ICOR) is held constant, the rate of
output growth in the two-gap model would then depend on the accumulation of physical
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capital, which depends on aid inflows, domestic savings, and other sources of capital
inflows. Combining equations 2 and 3 we arrive at the empirical form of the two-gap
model:
∆Y= β0 + β1 A + β2 Sd + β3 OF + ε ………………………………..Equation 4
Y
Y
Y
Y
Where:
∆Y/Y - rate of output growth
A/Y - aid flows as a percentage of GDP
Sd/Y - domestic savings as a percentage of GDP
OF/Y- and sources of capital inflow as a percentage of GDP
ε - error term.
To improve the estimation of the aid-growth coefficient, researchers have added a
number of new explanatory variables into their regression models in order to arrive at a
more consistent estimator of the aid-growth coefficient. Recent studies examining the
aid-growth nexus have incorporated new variables to capture policy and institutional
quality in the model. Equation 4 can assume the following form:
∆Y = β0 + β1 A + β2 Sd + β3 OF + β4 Z + e ……………………….Equation 5
Y
Y
Y
Y
In this equation, Z is a vector for control variables including the growth rate of various
factor inputs and policy variables, such as inflation, budget deficit, and degree of trade
openness, affecting growth.
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6.2
Model Specification and Data Description
The empirical model proposed will express economic growth as a function of external
and internal resources. Economic growth is chosen as the dependent variable because it
is widely regarded as the measure of the economic performance of the country. The
consensus from the existing literature is to use the growth rate of real per capita GDP as
the indicator of economic growth. In this paper, we will include two components of
external capital flows: foreign aid and foreign direct investment. The measure of foreign
aid is net official development assistance (ODA) as a percentage of gross domestic
product (GDP), and foreign direct investment is captured by net foreign direct investment
as a percentage of GDP. Savings is measured as gross domestic savings as a percentage
of GDP. Inflation is captured by the annual inflation rate as measured by changes in the
consumer price index, and the annual growth rate of exports measures export.
The
economic behaviour can be represented by the general specification below:
Yt = α + α1St + α2At + α3FDIt + α4 It + α5 Gxt ……………….….Equation 6
Where:
Y = economic growth
S = domestic savings as a percentage of GDP
A = ODA inflows as a percentage GDP
FDI = gross foreign direct investment as a percentage of GDP
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I = inflation
Gx = annual growth rate of exports
t = time
The growth equation contains aid, the variable of interest in this study. The inclusion of
aid in the growth equation has a long empirical tradition (Griffin and Enos, 1970;
Papanek, 1973; and Stoneman, 1975). In economic theory, the issue of the growth effect
of foreign aid is highly debated.
Some researchers (Papanek, 1973; Gupta, 1975;
Dowling & Hiemenz, 1983; Moseley et al, 1992; Durbarry et al, 1998; Hansen & Tarp,
1999) believe that aid has a positive impact on growth, while others (Griffin and Enos,
1970; and Bowen, 1998) argue that aid does not catalyse growth but retards it by
substituting for, rather than supplementing, domestic savings. We hypothesise that aid
will positively affect growth, this assumption is premised on the findings of recent time
series and cross country studies using advanced econometric methodologies.
We
presume that the injection of foreign capital can catalyse economic growth by allowing
the government to undertake large capital investment project that are essential in the
development of physical infrastructure and national linkages.
The inclusion of domestic savings as a variable in the model has several theoretical
antecedents (Papanek, 1973; Moseley, 1992; and Bowen, 1998). The general consensus
among researchers is that the coefficient of the saving (S) variable is expected to carry a
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positive sign (Dowling & Hiemenz, 1983; Moseley et al, 1992; Durbarry et al, 1998).
Increases in domestic savings can provide the necessary capital to develop the country’s
infrastructure and raise output.
Empirical works on the role of foreign direct investment (FDI) posit that it is positively
correlated with growth in host countries. FDI is an important source of capital, which
complements domestic private investment, and boosts economic growth in host countries.
We have added a policy variable in the form of inflation, which is expected to be
negatively correlated with growth. (Hadjimichael et al, 1995; Burnside & Dollar, 1997;
Durbarry et al, 1998). Durbarry et al (1998) echoing Fisher (1993) posit that inflation is
the foremost single indicator of macroeconomic policies.
They state that inflation rate
reveals the overall ability of the government to manage the economy. The growth rate of
export is also added to the model (see Mosley et al 1987 and Reichel 1995). We expect
this variable to be positively correlated with growth.
6.3 Data Source
The empirical analysis was conducted with a sample of annual data covering the period
1978 to 2002. Data on growth, aid, savings, growth rate of export, and foreign direct
investment came from the World Bank’s World Development Indicator 2005 CD-ROM,
and data on inflation came from IMF online database.
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6.4
Methodology
To examine the relationship between aid and growth, we adopt the recent times series
technique referred to as the autoregressive distributed lag (ARDL) approach to
cointegration analysis developed by Pesaran and Shin (1999) and Pesaran, Shin, and
Smith (1999). According to Lloyd et al (2001) the ARDL procedure is useful when
conducting cointegration analysis with small samples, since it is helpful in avoiding the
finite sample bias and is more efficient than the vector autoregressive (VAR) method. It
should be noted that single equation ARDL estimator delivers super-consistent estimates
of the long-run parameters and asymptotically valid t-ratios, even in the presence of
endogenous explanatory variable. The main advantage of this approach is that it can be
applied irrespective of whether the variables are I(0) or I(1). Another advantage of the
ARDL approach is that it takes sufficient number of lags to capture the data generating
process in a general-to-specific modelling framework.
In addition, the dynamic error
correction model (ECM) can be derived from the ARDL model through a simple linear
transformation.
The ECM integrates the short-run dynamics with the long-run
equilibrium without losing long-run information. It is also argued that using the ARDL
approach avoids problems resulting from non-stationary time series data. For example,
the ARDL model has proven to be robust against residual autocorrelation (Laurenceson
and Chai, 2003).
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However, since an assumption of the ARDL procedure is that the variables are either I(0)
or I(1), it is still necessary to conduct unit root tests in order to ensure that some variables
are not integrated to a higher order. The ARDL model of the aid-growth relationship can
be expressed in the following form:
p
q
q
q
q
q
Gt = α + ∑ βi Gt-i + ∑ ψ j St-j + ∑ π j At-j + ∑ γ j FDIt-j + ∑ λ j It-j + ∑ κ j Gx t-j + εt
i=1
j=0
j=0
j=0
j=0
j=0
…………………Equation 7
with p lags of the dependent variable, and the current value and q lags of the explanatory
variables. The appropriate lag length for the variables would be determined empirically
via the Schwarz information criterion.
Because of the relatively short time period
covered by the data, we begin with a model having two lags of the dependent variable
and two lags of each independent variable.
The error correction form of the ARDL model for equation 7 is given by:
2
2
2
2
2
2
ΔGt = α + ∑ βj Δ Gt-j + ∑ ψ j Δ St-j + ∑ π j Δ At-j + ∑ γ j Δ FDIt-j + ∑ λ j Δ It-j + ∑ κ j Gx t-j
j=1
j=1
j=1
j=1
j=1
j=1
+ φ1 Gt-1 + φ2 St-1 + φ3 At-1 + φ4 FDIt-1 + φ5 It-1 + φ6 Gx t-1 + εt
……………………..Equation 8
The null hypothesis for no cointegration ( Ho : φ1 = φ2 = φ3 = φ4= φ5 = φ6 = 0) is tested
against the alternative by way of the F–test. The F-statistic for the joint test of the
coefficients φ1, φ2, φ3, φ4, φ5 and φ6 are computed to test for cointegration among
variables. Next, the computed F-statistic is compared with the critical value bounds of
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the F-statistic. If the computed F-statistic were higher than the upper bound of the critical
value of the F-statistic, we do not accept the null hypothesis no cointegration. If the
variables are found to be cointegrated, the second step in the analysis is to estimate the
coefficients of the long run relationship of the growth equation and the associated error
correction models, and make inferences about them.
6.5
Result
Exhibit 1 gives the Augmented Dickey-Fuller (ADF) test results for the unit root test on
the variables included in the aid-growth model. As the results indicate, the variables are
either I(0) or I(1) thus implying that we can safely apply the ARDL methodology to our
model.
Exhibit 1 Results of ADF Unit Root Test on Series
Variables
Levels
First Difference
Inference
Growth rate of Per
capita GDP
Aid
-2.666
(-2.991)
-2.407
(-2.991)
-2.439
(-2.991)
-3.073
(-2.991)
-2.143
(-2.991)
-4.333
(-2.991)
-6.143
(-2.997)
--4.848
(-2.997)
-5.421
(-2.997)
-----
I (1)
-6.246
(-2.997)
-----
1 (1)
Savings
FDI
Inflation
Growth Rate of
Export
I (1)
I(1)
I (0)
I (0)
Numbers in parenthesis are 5% critical values based on the McKinnon (1996)
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Results displayed in exhibit 2 show that the computed F-statistic for the joint test of the
coefficients φ1, φ2, φ3, φ4, φ5, and φ6 is 3.88. The relevant critical value bounds, for the
present application, at the 95 percent level are 2.45 and 3.61. Since the computed FStatistic is above the upper bound of the critical value band, we cannot accept the null
hypothesis of no cointegration between the variables in the model.
Exhibit 2 Results of Cointegration Test
Computed FStatistic F
Lower Bound (95
percent)
Upper Bound (95
percent)
Inference
3.88
2.45
3.61
Do not accept null
hypothesis
Critical value bounds for the F-statistic at 95% confidence level from Pesaran, Shin, and Smith.(2001)
Having established the existence of a cointegration relationship among the variables
growth, aid, foreign direct investment, domestic savings, inflation, and growth rate of
exports, the ARDL method can be employed to estimate the dynamic structure of the
behavioural equation using the OLS method.
Exhibit 3 shows that the model selected by means of the Schwarz Information Criterion is
an ARDL (1,1,1,1,0,0) specification.
The R-squared value shows that the overall
goodness of fit of the model is satisfactory and the Durbin-Watson statistic is above 2.
The F-statistic measuring the joint significance of the all regressors in the model is
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statistically significant at the 1 per cent level. The diagnostic test results show that the
model passes the test for serial correlation, functional form, and heteroskedasticity.
Exhibit 3
Estimation of the Dynamic structure of ARDL Model (1,1,1,1,0,0)
Dependent Variable: G
Variable
C
G(-1)
A
A(-1)
S
S(-1)
FDI
FDI(-1)
I
Gx
R-squared
Coefficient
-5.673822
0.004781
0.108413
-0.234434
0.007775
0.349736
0.301147
0.203229
-0.051533
0.165188
0.888039
Std.
t-Statistic
Error
2.249691
-2.522045
0.155428
0.030760
0.061376
1.766384
0.092974
-2.521490
0.086450
0.089934
0.090364
3.870279
0.077269
3.897398
0.068465
2.968382
0.025560
-2.016159
0.033797
4.887711
Mean dependent var
Prob.
0.0244
0.9759
0.0991
0.0244
0.9296
0.0017
0.0016
0.0102
0.0634
0.0002
0.712500
Adjusted R-squared
0.816064
S.D. dependent var
5.240338
S.E. of regression
2.247466
Akaike info criterion
4.751820
Sum squared resid
70.71543
Schwarz criterion
5.242676
F-statistic
Prob(F-statistic)
12.33814
0.000031
Log likelihood
-47.02184
Durbin-Watson stat
2.491055
A: Serial Correlation F = 1.76 (0.21)
B: Specification Error F = 1.85 (0.29)
C: Heteroskedasticity Obs *R-Sq 19.94; (0.336)
D: Normality 2 = 0.8566 (0.6516)
A: Lagrange Multiplier test for residual serial correlation
B: Ramsey’s Reset test using the square of fitted values
C: White Heteroskedasticity Test
D: Jarque-Bera
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The stability test results, cumulative sum of recursive residuals and cumulative sum of
squares of recursive residuals (CUSUM and CUSUMSQ), of the ARDL model are shown
below (Figure 13 & 14). The CUSUM and the CUSUMSQ plotted against the critical
bounds at 5 percent significance level show that the model is stable over time.
Figure 13
Plot of Cumulative Sum of Recursive Residuals
15
Plot of C umulativ e Sum of R ec urs iv e R es iduals
10
5
0
-5
-10
-15
89
90
91
92
93
94
CUSUM
95
96
97
98
99
00
01
02
5% Signific anc e
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Figure1 4
Plot of Cumulative Sum of Squares of Recursive Residuals
1.5
Plo t o f C u mu la tiv e Su m o f Sq u a r e s o f R e c u r s iv e R e s id u a ls
1.0
0.5
0.0
- 0.5
89
90
91
92
93
94
95
96
C U SU M of Squar es
97
98
99
00
01
02
5% Signific anc e
Exhibit 4: Long Run Results
Variable
Coefficient
Std. Error
t-Statistic
C
-5.382778
2.214940
-2.430214**
A
0.140961
0.081028
1.739660
FDI
0.229916
0.086765
2.649871**
S
0.237151
0.101195
2.343514**
I
-0.067874
0.035427
-1.915899*
Gx
0.083279
0.036412
2.287168**
**significant at 5 percent level; * significant at 10 percent level
The coefficient of FDI is 0.230, which is positive and statistically significant at the 5
percent level. This means that in the long run, an increase of one percent in foreign direct
investment will result in a 0.23 percent increase in the growth rate of per capita GDP.
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This result corresponds with Dowling and Hiemenz (1983)52 who found a positive and
significant effect of FDI on growth when FDI is included in the aid growth regression.
This result has important implications for economies like Guyana that are plagued by the
scarcity of domestic productive resources and which can benefit from resource flows
through FDI. Along with physical capital, FDI brings new technology, managerial talent,
international market expertise, and increased access to international financial capital. This
is particularly evident in the mining sector of Guyana where significant FDI has boosted
exports and improved the balance of payments. The coefficient for domestic savings (S)
is 0.24, which is positive and significant. This means that in the long run, an increase of
one per cent in domestic savings will bring about a 0.24 percent increase in the growth
rate of per capita GDP. This result concurs with those of Dowling and Hiemenz (1983),
Mosley et al (1992), Durbarry et al. (1998). These studies found evidence of a positive
and statistically significant effect of domestic savings on growth.
The neoclassical
growth theory suggests that domestic savings play an important role in the process of
economic growth and development. Savings, to a large extent, determine the national
capacity to invest and produce, which in turn influence economic growth potential.
Government should, therefore, implement further measures to increase savings and
improve financial intermediation so as to promote a stable financial environment and
support sustainable economic growth by improving the efficiency of resource use. The
52
J. Dowling, J and V. Hiemenz, 1983, “Aid, Savings, and Growth in the Asian Region,” in M. Tsikata
“Aid Effectiveness: A Survey of Recent Empirical Literature,” (Online:
http://www.imf.org/external/pubs/ft/ppaa/ppaa9801.pdf).
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coefficient of the growth rate of exports (Gx) is 0.08, which is positive and statistically
significant at the 5 percent level. In the long run, an increase of one percent in the growth
rate of exports will result in an increase of 0.08 percent in the growth rate of per capita
GDP in Guyana. This result is similar to the finding of Mosley (1987), Reichel (1995),
Bowen (1998) and Lloyd (2001). These studies found that exports exert a positive effect
on growth. Exports generate foreign exchange, increase employment, improve trade
balance, and consequently national output. In this regard government policy must be
aimed at reducing barriers to international trade and investment production that are
associated with the export sector.
Guyana’s period of high growth (1991-97) was
associated with increases in exports in the agriculture and mining sector. The fact that
these results agree with economic theory and recent studies, lend credence to the
usefulness of the model.
The coefficient for the inflation variable is negative but insignificant. Durbarry et al
(1998) and Burnside and Dollar (1997) found the inflation variable to be negative and
significant. There is professional disagreement about the statistical significance of the
relationship between inflation and growth. Levine and Renelt (1992) conclude that the
relationship between inflation and growth is statistically insignificant at conventional
levels. However, while the coefficient on inflation in growth regressions is sometimes
statistically significant and sometimes not the coefficient is always negative. Levine and
Renelt (1992) refer to inflation as a fragile explanatory variable of economic growth.
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Despite not being significant at conventional levels (5 percent level of significance) in
our regression, the inflation variable is marginally significant (significant at a 10 percent
level of significance; see exhibit 4). We, therefore, concur with Levine and Renelt (1992)
that inflation is a fragile explanator for economic growth. Notwithstanding, inflation may
plausibly affect growth by both altering the level of investment as well as affecting the
efficiency of resource allocation. This result suggests that while macroeconomic stability
on its own is not sufficient to sustain growth and development, it is a necessary condition
for catalysing growth.
The coefficient of the aid variable is positive but statistically insignificant. Based on this,
we are unable to accept our hypothesis that aid has a statistically significant positive
impact on growth. The robustness of our results was tested using aid less debt
forgiveness. Again, we found no statistically significant long-run relationship between
aid and growth (Appendix: Table AII-17). This finding contradicts earlier findings of
Burnside and Dollar (1997), Hadjimichael et al (1995), Durbarry, et al (1998), Hansen
and Tarp (1999), and Lloyd et al (2001), where the positive growth impact of aid was
isolated. However, Moseley et al (1987) and Boone (1996) both found no statistically
significant positive relationship between aid and growth. Boone contends that aid does
not significantly increase investment and growth, but it does increase the size of
government consumption. Mosley et al concludes that the result of no statistically
significant relationship between aid and growth indicates the possible leakage of aid to
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non-productive expenditures in the public sector and the crowding out of private
investment in the private sector.
The insignificance of the aid variable in Guyana’s context may be partially explained by
certain factors that impacted on the economy, such as excessive emigration of skilled and
educated personnel, socio-political instability and governance issues, low capacities of
many national institutions, and to a lesser extent inflation, all of which may have
undermined the effectiveness of foreign aid. We have already alluded to the significant
outflows of skilled and educated workforce in Guyana and its deleterious effect on
national institutions and economic growth. There is a relatively large consensus that
socio-political instability such as riots, strikes, and demonstrations, all experienced by
Guyana, has a negative influence on aid effectiveness and growth. The quality of the
country’s governance may have also affected the productivity of aid resources, since the
bulk of aid was channelled through government institutions. Whenever aid, channelled
through government systems, does not contribute to sustained growth, inefficiency may
be widespread.
As we indicated earlier, our survey feedback reports beneficiary
complaints including projects having to be redone several times, long delays in
implementation, poor coordination between projects (project sequencing), substandard
work by contractors and short existence of project outcomes. The findings from our
preliminary analysis when compared to critical success factors for aid effectiveness show
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that there is a need for continuing reform in the management and coordination
mechanism of aid, so that it can contribute to long-run growth.
We have already pointed out that Guyana has had a history of government intervention in
economic activity, especially from the mid-1970s up until the reform measures
introduced through structural adjustment in 1988, which left a legacy of poor
infrastructure, weak private and financial sectors, and an enormous debt all of which can
affect aid’s contribution to sustained growth. Physical infrastructure is crucial in terms of
both investment climate and economic growth. For example, transportation and
communications infrastructure connect markets and people, both domestically and
internationally. Better infrastructure reduces production costs and enhances productivity,
thereby leading to growth. Governments can have some success in financing or inducing
factor accumulation over the medium term, however, it is far less successful at inducing
productivity growth when it takes a lead role in the economy. Even when a governmentdominated economy manages large quantities of investment, the quality of that
investment is often low resulting in socially suboptimal outcomes.
We mentioned earlier that Ruhashyankiko (2005) characterise Guyana as a Category 2
country, where aid dependence neither rises nor falls over time.
He explains that
Category 2 countries did not manage to extract growth from aid, since prolonged aid
dependence weakened institutional capacity and resulted in the inefficient use of aid
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resources.
Ruhashyankiko contends that protracted aid dependence can undermine
institutional quality by weakening accountability, encouraging rent seeking and
corruption, and alleviating pressures to reform inefficient policies and institutions. The
capacity-undermining effects, an unintended outcome, of prolonged aid dependence on
local capacity could in part be attributed to the donor dominated character of aid
relationships. Very often donors or their consultants identify and design projects that
cannot be implemented or sustained by local people alone. Thus locals are denied
genuine opportunities for learning, even learning from failure, and we all recognise the
fact that learning is central to the process of sustained growth and development. It not
unusual to see large donor missions making several trips here to implement and monitor
donor funded projects. To reduce the capacity-undermining effect of aid presence,
donors’ involvement should be directed more toward explanation, demonstration, and
facilitation and less on setting conditions and decision making.
Finally, government economic policies could have also accounted for aid not having an
impact on growth.
Burnside and Dollar (1997) stated that policies have a critical
influence on the effectiveness of aid, for the same reasons that they affect economic
growth; economic policies that engender balance of payments difficulties, high budget
deficits and external debt or high rates of inflation, all symptoms of the Guyana economy
during the period under review, are likely to foster a climate of economic uncertainty,
which dampens the private sector's response to the public investment represented by aid.
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High rates of inflation undermine private sector by reducing predictability while
discouraging investment. While macroeconomic stability on its own is not sufficient to
sustain growth and development, it is a necessary condition for catalysing growth.
The estimates of the error correction (ECM) representation which expresses the short run
dynamics are presented in exhibit 5. The coefficient of the first difference of the aid
variable is positive and statistical significant at the 5 per cent level, implying that
although there is no statistical significant long run impact of aid on growth in Guyana, a
change in the volume of aid flows is associated with a change in growth in the short run.
This result suggests that despite there is no significant long-run relationship between aid
and growth, there exists a significant short run effect.
This finding does highlight the
point that the flow of resources is not sufficient for inducing and sustaining growth.
While it is true that the construction of a school may stimulate economic activity in the
short run, in the long run, if quality teachers migrate, then the critical impetus that
education can provide to sustained economic growth will be absent.
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Exhibit 5 Results for Error Correction Model
Dependent Variable: DG
Variable
Coefficient
Std. Error
t-Statistic
C
DG(-1)
DA
DA(-1)
DFDI
DFDI(-1)
DS
DS(-1)
DI
DGx
ECM(-1)
R-squared
0.113865
0.013755
0.115332
-0.224977
0.248237
0.122471
0.050255
0.369688
-0.046696
0.152713
-1.335375
0.911962
0.452950
0.126386
0.049430
0.067232
0.071881
0.059112
0.083401
0.071200
0.033975
0.026503
0.289607
Mean dependent var
Adjusted R-squared
0.838598
S.D. dependent var
5.264791
S.E. of regression
2.115125
Akaike info criterion
4.642039
Sum squared resid
53.68504
Schwarz criterion
5.185101
F-statistic
12.43054
Prob(F-statistic)
0.000071
Log likelihood
Durbin-Watson stat
-42.38345
2.188608
0.251385
0.108832
2.333230
-3.346276
3.453432
2.071824
0.602572
5.192246
-1.374418
5.762068
-4.610991
Prob.
0.8058
0.9151
0.0378**
0.0058**
0.0048**
0.0605
0.5580
0.0002**
0.1944
0.0001**
0.0006**
0.043478
** Significant at the 5 percent level.
Both first differences of the FDI and export variables are positive and significant in the
short run, while the first difference of savings is insignificant. This indicates that both
FDI and exports have a short run impact on growth along with their long run impact. The
coefficient of the first difference of savings lagged one period was found to be positive
and significant. Further, our results indicate that the first difference of savings lagged
one period had the strongest short run impact. This further supports the strong empirical
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link established between savings and growth and accentuates the need for policy
measures aimed at increasing domestic savings rate.
The computed F- statistic is highly significant implying that the null hypothesis that all
regressors have zero coefficients for all cases cannot be accepted. Moreover, the DurbinWatson statistic does not indicate the presence of serial correlation. The R-squared
demonstrates that the variables in the model explain 91 percent of the growth variable in
the case of Guyana, which is an indication of a good fit. The analysis is extended to
include the lagged ECM term. The coefficient on the error term is negative and
significant, validating the existence of an equilibrium relationship among the variables
and suggests that ignoring the non-stationarity and cointegration of the variables would
have introduced misspecification in the underlying dynamic structure.
The size of the
coefficient provides a measure of the speed of adjustment back to long run equilibrium.
The speed of adjustment (the coefficient of the lagged ECM term) is -1.335, implying
that more than 100 percent of the error is being adjusted in one period. Tentatively, we
suggest damped cycles, with overshooting and undershooting of equilibrium following
shock.
In summary, our analysis suggests that during the period under review aid had a
significant positive impact on growth in the short-run; however, the effect is not
discernable in the long run. We attributed this result in Guyana to political and economic
shocks which affected the delivery channels of foreign aid, thus limiting its effectiveness.
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As expected, our results also confirm that domestic savings, foreign direct investment,
and export all contributed to long run growth and that it was important for Guyana to
create the environment and implement policies to increase savings, investment, and
exports.
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SECTION 7 CONCLUSION, SOME POLICY IMPLICATIONS AND NEW
RESEARCH EMPHASES
The major challenge of this work has been the investigation of the growth impact of
foreign aid in Guyana, in order to further the debate on the aid-growth relationship.
Studying the effects of foreign aid on economic growth provided the opportunity to
supply a balanced theoretical and empirical view of the effectiveness of foreign aid in
achieving long-term economic growth and development in Guyana. Identifying the actual
effects foreign aid or any other type of resource have on growth could generate insight
into which development policies can promote sustained economic growth. We draw the
following three conclusions from our study.
One, notwithstanding substantial amounts of aid, it appears that our expectation that aid
would boost economic growth has not been met. The insignificance of the coefficient of
the aid variable implies that there was no long-run relationship between aid and growth.
We conclude that it does not necessarily follow that a greater injection of foreign
resources will be translated into growth. Theoretically, we expected aid, a component of
foreign savings, to boost investment and growth in Guyana, a country, which suffers from
capital resource scarcity. Socio-political instability, emigration of skilled and educated
personnel, institutional bottlenecks, and low capacity in the aid coordination and
management institutions were some of the reasons we isolated as having the potential to
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undermine the effectiveness of foreign aid. In addressing these problems, we suggest the
following initial measures, which can be useful in maximising the development benefits
of foreign aid. It is imperative that government foster a political climate that engenders
confidence among all local stakeholder groups, facilitating the development of a
relationship of trust, and a positive climate for cooperation. Government can achieve this
objective through: adhering to democratic principles, making public administration more
participatory and transparent, and providing opportunities for the poor to improve their
lots. The Government of Guyana should endeavour to strengthen its self-development
capacity, continue to implement structural reforms necessary for sustained growth, and
emphasise personnel training to gradually improve institutional capacity. Government
should also seek to provide incentives to retain highly qualified and skilled personnel to
aid in the development drive. In addition, migrants can be encouraged to be agents of
development by contributing to the country’s growth thrust, through remittances,
investment and expenditure, and entrepreneurial activities to achieve sustained growth.
Two, it appears that protracted aid dependence may have affected aid’s impact on growth
by weakening local institutional quality. The capacity undermining challenges derived
from prolong aid dependence and their effects on local capacity are inimical to growth.
Consequently, donors and recipient need to work together to overcome these obstacles to
sustained growth. Fundamental reform of donors approach can be useful in solving this
problem. This requires a transformation of the conventional aid system, from its donor
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driven character to one that allows local institutions to choose and design projects on
their own, on the basis of their capacity to implement. Donors’ involvement should be
directed more toward explanation, demonstration, and facilitation and less on setting
conditions and decision making. The main task of local policy makers is to strengthen
public sector institutional quality through training, adopting a zero tolerance for
corruption and the abuse of executive power for rent-seeking, and hasten the governance
reform agenda; and to ensure that aid is effectively used to add to productive capacity and
thereby improve growth. Success in the former is contingent on the political will of
government, while success in the latter depends on establishing the virtuous cycle
between investment, exports, and savings. In this process investment (boosted by aid
flows) supports exports by providing the bases for technological change, productivity
growth, and increased competitiveness, while exports support investment because they
earn foreign exchange required for the import of goods and technology needed for capital
accumulation and growth. As incomes and profits are raised through investment, they
increasingly provide additional resources for capital accumulation. With rising savings
and exports, the savings and foreign exchange gaps are closed thereby eventually
eliminating aid dependence.
Three, the results also indicate that foreign aid may play a role in short-term economic
growth, as evidenced by the significance of the short-run coefficient of the aid variable;
however, foreign aid does not guarantee success. Here, we suggest innovation and
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adaptation by both donors and recipient to sustain the growth impact of aid.
A
substantial body of evidence has shown that if development is to be achieved, resource
transfers must be supplemented by a stable macroeconomic environment and constructive
aid delivery channels. In this regard, we would urge both donors and recipient to use best
efforts to do all that is necessary to increase and improve aid delivery and effectiveness.
The following recommendations represent preliminary steps in that direction: donors
should assist government in developing five to eight year rolling plans and medium term
investment strategies to chart their development course, thereby increasing the coherence
of the national growth thrust and development efforts; donors should also assist the
Government of Guyana in creating the framework of policies, analytical capacity,
systems, procedures and skills necessary for the government to take greater management
responsibilities for development work; government should strengthen the aid
coordination and management mechanism by setting up a task force to plan, implement,
and monitor resource mobilisation strategy; government should create and manage a
pipeline of development proposals, based on wide stakeholders’ consultation, through the
various stages of formulation, examination, negotiation and approval; government should
improve the liaison and reporting among the many stakeholders involved in the
development partnership, to ensure consensus, collaboration and smooth implementation
of programmes and projects to enhance transparency and encourage open debate; and
government should provide conducive investment climate for public and domestic and
foreign private investment, including political and macroeconomic stability, a sound
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regulatory framework, efficient institutions and an adequate physical and social
infrastructure.
Finally, we recommend that further research work should focus on investigating the
impact of foreign aid on growth in Guyana using disaggregated aid data. Aid can be
disaggregated into project aid and programme aid. New research should pay particular
attention to the relationship between domestic savings and total investment in the
economy. Researchers should also focus on isolating the determinants of investment in
Guyana and the way in which aid affects them.
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APPENDIX I ESTIMATION OUTPUT
Table AII-1: Summary Statistics
Aid as a
share of
GDP (A)
Domestic
Savings as
a share of
GDP (S)
Annual
Inflation
rate (I)
23.09200
Annual
growth
rate of
GDP per
capita (G)
0.576000
Foreign
Direct
Investment
as share of
GDP (FDI
5.682800
Annual
Growth
rate of
export
(GX)
3.200000
Mean
14.56000
16.44800
Median
11.50000
16.90000
15.00000
1.300000
0.970000
-1.000000
Maximum
42.60000
33.20000
101.5000
8.100000
39.81000
110.0000
Minimum
5.300000
2.700000
2.700000
-13.20000
0.000000
-26.00000
Std. Dev.
10.66681
6.895779
25.60887
5.175204
9.005675
23.90432
25
25
25
25
25
25
Observations
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Table AII-2: Correlation Matrix
Variables
G
A
A(-1)
FDI
FDI(-1)
S
S(-1)
GX
I
G
1.000
0.437
0.481
0.561
0.509
0.386
0.425
0.418
-0.114
A
0.437
1.000
0.599
0.259
0.199
0.047
0.062
0.488
0.414
A(-1)
0.481
0.599
1.000
0.600
0.279
0.001
-0.006
0.610
0.195
FDI
0.561
0.259
0.600
1.000
0.412
-0.013
0.024
0.064
-0.235
FDI(-1)
0.509
0.199
0.279
0.412
1.000
0.113
-0.028
-0.069
-0.347
S
0.386
0.047
0.001
-0.013
0.113
1.000
0.524
0.123
-0.002
S(-1)
0.425
0.062
-0.006
0.024
-0.028
0.524
1.000
-0.080
-0.035
GX
0.418
0.488
0.610
0.064
-0.069
0.123
-0.080
1.000
0.533
-0.114
0.414
0.195
-0.235
-0.347
-0.002
-0.035
0.533
1.000
I
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Table AII-3: Testing for Cointegration
Dependent Variable: DG
Variable
Coefficient
C
DG(-1)
DG(-2)
DA(-1)
DA(-2)
DFDI(-1)
DFDI(-2)
DS(-1)
DS(-2)
DI(-1)
DI(-2)
D(GX(-1))
D(GX(-2))
G(-1)
A(-1)
FDI(-1)
S(-1)
I(-1)
GX(-1)
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
-12.85980
0.298821
0.425045
-0.073053
0.129410
-0.063644
0.280174
0.154951
0.246961
0.070808
0.258246
0.276718
-0.089418
-1.588143
0.107768
1.222970
0.429715
-0.057074
-0.175222
0.974160
0.819117
2.263934
15.37620
-27.27621
2.931798
Std. Error
t-Statistic
Prob.
7.213719
0.557316
0.226883
0.193913
0.132939
0.516972
0.250050
0.350553
0.228260
0.093333
0.093943
0.208554
0.090268
0.891254
0.179444
0.392958
0.361440
0.069322
0.285189
-1.782687
0.536179
1.873412
-0.376732
0.973457
-0.123108
1.120474
0.442017
1.081929
0.758658
2.748970
1.326843
-0.990589
-1.781920
0.600568
3.112217
1.188896
-0.823318
-0.614406
0.1727
0.6290
0.1577
0.7314
0.4021
0.9098
0.3441
0.6884
0.3585
0.5032
0.0708
0.2765
0.3949
0.1728
0.5905
0.0528
0.3200
0.4707
0.5824
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
-0.127273
5.323102
4.206928
5.149192
6.283168
0.077610
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Table AII-4: Testing the null hypothesis for no cointegration
Wald-Coefficient Test:
Null Hypothesis: φ1= 0
φ2 = 0
φ3 = 0
Φ4= 0
Φ5= 0
Φ6= 0
F-statistic
Chi-square
3.878700
23.27220
Probability
Probability
0.146628
0.000710
Ho : φ1 = φ2 = φ3 = φ4= φ5 = φ6 = 0
The F-statistics is compared with critical value bounds for the F-statistic at 95%
confidence level from Pesaran etal 2001. The upper bound according Pesaran etal 2001
tables at 95 % confidence level is 3.61. Since the computed F-statistics 3.88 > 3.61, we
cannot accept the null hypothesis of no cointegration.
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Unit Root Tests
Augmented Dickey-Fuller Unit Root Test on per capita GDP growth (G)
Table AII-5: Test for Unit Root on per capita GDP growth in Level
ADF Test Statistic
-2.665520
1% Critical Value*
-3.7343
5% Critical Value
-2.9907
10% Critical Value
-2.6348
Dependent Variable: D(G)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
G(-1)
-0.482934
0.181178
-2.665520
0.0141
C
0.369944
0.942032
0.392708
0.6983
R-squared
0.244116
Mean dependent var
0.050000
Adjusted R-squared
0.209758
S.D. dependent var
5.149166
S.E. of regression
4.577381
Akaike info criterion
5.959786
Sum squared resid
460.9532
Schwarz criterion
6.057957
F-statistic
7.104996
Prob(F-statistic)
0.014128
Log likelihood
Durbin-Watson stat
-69.51744
2.064303
Since -2.6655 > -2.9907 we cannot accept null hypothesis of no unit root at 95%
confidence interval.
112
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Table AII-6: Test for Unit Root in First Difference
ADF Test Statistic
-6.142892
1% Critical Value*
-3.7497
5% Critical Value
-2.9969
10% Critical Value
-2.6381
Dependent Variable: D(G,2)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(G(-1))
-1.303014
0.212117
-6.142892
0.0000
C
0.118573
1.073994
0.110404
0.9131
R-squared
0.642463
Mean dependent var
-0.204348
Adjusted R-squared
0.625437
S.D. dependent var
8.405868
S.E. of regression
5.144521
Akaike info criterion
6.196683
Sum squared resid
555.7880
Schwarz criterion
6.295421
F-statistic
37.73513
Prob(F-statistic)
0.000004
Log likelihood
Durbin-Watson stat
-69.26185
1.977150
Since -6.1429 < -2.9969 we accept null hypothesis of no unit root at 95% confidence
interval.
113
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Augmented Dickey-Fuller Unit Root Test on Aid as a share of GDP (A)
Table AII-7: Test for Unit Root on Aid as a share of GDP in Level
ADF Test Statistic
-2.406625
1% Critical Value*
-3.7343
5% Critical Value
-2.9907
10% Critical Value
-2.6348
Dependent Variable: D(A)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
A(-1)
-0.406680
0.168983
-2.406625
0.0249
C
6.161304
3.075464
2.003374
0.0576
R-squared
0.208401
Mean dependent var
0.145833
Adjusted R-squared
0.172419
S.D. dependent var
9.649464
S.E. of regression
8.778260
Akaike info criterion
7.262089
Sum squared resid
1695.273
Schwarz criterion
7.360260
F-statistic
5.791843
Prob(F-statistic)
0.024938
Log likelihood
Durbin-Watson stat
-85.14506
1.794240
Since -2.4066 > -2.9907 we cannot accept null hypothesis of no unit root at 95%
confidence interval.
114
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Table AII-8: Test for Unit Root on Aid as a share of GDP in First Difference
ADF Test Statistic
-4.848153
1% Critical Value*
-3.7497
5% Critical Value
-2.9969
10% Critical Value
-2.6381
Dependent Variable: D(A,2)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(A(-1))
-1.061855
0.219023
-4.848153
0.0001
C
0.130748
2.102775
0.062179
0.9510
R-squared
0.528139
Mean dependent var
-0.247826
Adjusted R-squared
0.505669
S.D. dependent var
14.33336
S.E. of regression
10.07760
Akaike info criterion
7.541448
Sum squared resid
2132.718
Schwarz criterion
7.640187
F-statistic
23.50459
Prob(F-statistic)
0.000086
Log likelihood
Durbin-Watson stat
-84.72666
2.029162
Since -4.8482 < -2.9969 we accept null hypothesis of no unit root at 95% confidence
interval.
115
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Augmented Dickey-Fuller Unit Root Test on FDI as a share of GDP (FDI)
Table AII-9: Test for Unit Root on Foreign Direct Investment as a share of GDP in
Level
ADF Test Statistic
-3.073285
1% Critical Value*
-3.7343
5% Critical Value
-2.9907
10% Critical Value
-2.6348
Dependent Variable: D(FDI)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
FDI(-1)
-0.591998
0.192627
-3.073285
0.0056
C
3.606894
2.049711
1.759709
0.0924
R-squared
0.300368
Mean dependent var
0.251250
Adjusted R-squared
0.268566
S.D. dependent var
9.936604
S.E. of regression
8.498172
Akaike info criterion
7.197235
Sum squared resid
1588.817
Schwarz criterion
7.295406
F-statistic
9.445081
Prob(F-statistic)
0.005561
Log likelihood
Durbin-Watson stat
-84.36681
2.208744
Since -3.0732 < -2.9907 we accept null hypothesis of no unit root at 95% confidence
interval
116
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Augmented Dickey-Fuller Unit Root test on growth rate of export
Table AII-10: Test for Unit Root on the growth rate of exports in Level
ADF Test Statistic
-4.333332
1% Critical Value*
-3.7343
5% Critical Value
-2.9907
10% Critical Value
-2.6348
Dependent Variable: D(GX)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
GX(-1)
-0.919885
0.212281
-4.333332
0.0003
C
2.694622
5.121400
0.526149
0.6040
R-squared
0.460490
Mean dependent var
-0.333333
Adjusted R-squared
0.435967
S.D. dependent var
33.09494
S.E. of regression
24.85501
Akaike info criterion
9.343651
Sum squared resid
13590.97
Schwarz criterion
9.441822
F-statistic
18.77777
Prob(F-statistic)
0.000267
Log likelihood
Durbin-Watson stat
-110.1238
1.954756
Since -4.3333 < -2.9907 we accept null hypothesis of no unit root at 95% confidence
interval
117
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Augmented Dickey-Fuller Unit Root test on Savings
Table AII-11: Test for Unit Root on Domestic savings as a share of GDP in Levels
ADF Test Statistic
-2.438609
1% Critical Value*
-3.7343
5% Critical Value
-2.9907
10% Critical Value
-2.6348
Dependent Variable: D(S)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
S(-1)
-0.458265
0.187921
-2.438609
0.0233
C
7.157706
3.399549
2.105487
0.0469
R-squared
0.212790
Mean dependent var
-0.558333
Adjusted R-squared
0.177008
S.D. dependent var
6.712993
S.E. of regression
6.089953
Akaike info criterion
6.530813
Sum squared resid
815.9256
Schwarz criterion
6.628984
F-statistic
5.946816
Prob(F-statistic)
0.023275
Log likelihood
Durbin-Watson stat
-76.36976
1.869334
Since -2.4386 > -2.9907 we cannot accept null hypothesis of no unit root at 95%
confidence interval.
118
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Table AII-12: Test for Unit Root on Domestic savings as a share of GDP in First
Difference
ADF Test Statistic
-5.420853
1% Critical Value*
-3.7497
5% Critical Value
-2.9969
10% Critical Value
-2.6381
Dependent Variable: D(S,2)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(S(-1))
-1.166784
0.215240
-5.420853
0.0000
C
-0.737032
1.448936
-0.508671
0.6163
R-squared
0.583215
Mean dependent var
0.008696
Adjusted R-squared
0.563368
S.D. dependent var
10.46861
S.E. of regression
6.917463
Akaike info criterion
6.788916
Sum squared resid
1004.877
Schwarz criterion
6.887655
F-statistic
29.38564
Prob(F-statistic)
0.000022
Log likelihood
Durbin-Watson stat
-76.07254
1.934940
Since -5.4209 < -2.9969 we accept null hypothesis of no unit root at 95% confidence
interval
119
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Augmented Dickey-Fuller Unit Root test on Inflation (I)
Table AII-13: Test for Unit Root on Inflation Rate in Levels
ADF Test Statistic
-2.143489
1% Critical Value*
-3.7343
5% Critical Value
-2.9907
10% Critical Value
-2.6348
Dependent Variable: D(I)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
I(-1)
-0.355063
0.165647
-2.143489
0.0434
C
8.027134
5.763248
1.392814
0.1776
R-squared
0.172763
Mean dependent var
-0.450000
Adjusted R-squared
0.135161
S.D. dependent var
22.08399
S.E. of regression
20.53739
Akaike info criterion
8.962026
Sum squared resid
9279.253
Schwarz criterion
9.060197
F-statistic
4.594545
Prob(F-statistic)
0.043384
Log likelihood
Durbin-Watson stat
-105.5443
2.177756
Since -2.1435 > -2.9907 we cannot accept null hypothesis of no unit root at 95%
confidence interval.
120
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Table AII-14: Test for Unit Root on Inflation Rate in First Difference
ADF Test Statistic
-6.245915
1% Critical Value*
-3.7497
5% Critical Value
-2.9969
10% Critical Value
-2.6381
Dependent Variable: D(I,2)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(I(-1))
-1.299838
0.208110
-6.245915
0.0000
C
-0.752956
4.596371
-0.163815
0.8714
R-squared
0.650067
Mean dependent var
-0.052174
Adjusted R-squared
0.633403
S.D. dependent var
36.39614
S.E. of regression
22.03685
Akaike info criterion
9.106251
Sum squared resid
10198.08
Schwarz criterion
9.204989
F-statistic
39.01146
Prob(F-statistic)
0.000003
Log likelihood
Durbin-Watson stat
-102.7219
1.849191
Since -6.2459 < -2.9969 we accept null hypothesis of no unit root at 95% confidence
interval
121
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Diagnostic Test
Table AII-15: Ramsey RESET Test: Specification Error
F-statistic
Log likelihood ratio
Dependent Variable: G
Variable
1.847212
41.42354
Probability
Probability
0.290711
0.000009
Coefficient
Std. Error
t-Statistic
Prob.
C
G(-1)
A
A(-1)
-2.276019
-0.349248
0.103705
-0.284246
6.403514
0.267562
0.112420
0.238093
-0.355433
-1.305298
0.922482
-1.193841
0.7402
0.2618
0.4085
0.2985
FDI
FDI(-1)
S
0.498921
0.241471
-0.062592
0.305805
0.434699
0.087577
1.631500
0.555490
-0.714707
0.1781
0.6082
0.5143
S(-1)
I
GX
0.442122
-0.112451
0.222696
0.371137
0.080297
0.160419
1.191265
-1.400434
1.388214
0.2994
0.2340
0.2374
FITTED^2
FITTED^3
FITTED^4
-2.362110
-0.217642
0.371128
1.214599
0.240866
0.228768
-1.944765
-0.903579
1.622291
0.1237
0.4173
0.1801
FITTED^5
FITTED^6
FITTED^7
0.006105
-0.020844
0.000770
0.022309
0.013751
0.001195
0.273628
-1.515862
0.644389
0.7979
0.2041
0.5544
FITTED^8
FITTED^9
FITTED^10
0.000451
-3.11E-05
-2.87E-06
0.000306
2.95E-05
1.97E-06
1.472977
-1.054671
-1.457292
0.2147
0.3511
0.2188
FITTED^11
2.41E-07
2.04E-07
1.180845
0.3031
R-squared
Adjusted R-squared
S.E. of regression
0.980071
0.885409
1.773924
Sum squared resid
Log likelihood
Durbin-Watson stat
12.58723
-26.31007
2.447860
Mean dependent var
S.D. dependent var
Akaike info criterion
0.712500
5.240338
3.859173
Schwarz criterion
F-statistic
Prob(F-statistic)
4.840884
10.35333
0.017693
122
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Table AII-16: Breusch-Godfrey Serial Correlation LM Test
F-statistic
1.763994
Probability
0.206974
Obs*R-squared
2.867506
Probability
0.090385
Dependent Variable: RESID
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.792840
2.270586
0.349179
0.7325
G(-1)
0.148045
0.187969
0.787601
0.4451
A
0.016893
0.061105
0.276457
0.7865
A(-1)
-0.024923
0.092461
-0.269548
0.7917
FDI
-0.029553
0.078464
-0.376647
0.7125
FDI(-1)
-0.030610
0.070541
-0.433933
0.6715
S
0.014895
0.084928
0.175384
0.8635
S(-1)
-0.045868
0.094530
-0.485226
0.6356
I
0.003250
0.025010
0.129931
0.8986
GX
0.003118
0.032994
0.094507
0.9261
RESID(-1)
-0.460595
0.346793
-1.328154
0.2070
R-squared
0.119479
Mean dependent var
6.20E-16
-0.557844
S.D. dependent var
1.753449
S.E. of regression
2.188543
Akaike info criterion
4.707912
Sum squared resid
62.26639
Schwarz criterion
5.247853
F-statistic
0.176399
Prob(F-statistic)
0.995268
Adjusted R-squared
Log likelihood
Durbin-Watson stat
-45.49494
2.276564
123
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Table AII-17: White Heteroskedasticity Test
F-statistic
1.364209
Probability
0.391891
Obs*R-squared
19.93988
Probability
0.336215
Dependent Variable: RESID^2
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
20.31485
16.45081
1.234885
0.2717
G(-1)
G(-1)^2
-0.380177
-0.047873
0.463095
0.036863
-0.820949
-1.298677
0.4490
0.2507
A
A^2
A(-1)
1.128494
-0.017939
-2.499087
1.045719
0.021676
1.709115
1.079156
-0.827596
-1.462211
0.3298
0.4456
0.2035
A(-1)^2
S
0.049704
-0.415883
0.036389
0.794460
1.365912
-0.523479
0.2302
0.6230
S^2
S(-1)
0.004716
-0.653154
0.022577
0.582690
0.208904
-1.120930
0.8428
0.3132
S(-1)^2
FDI
FDI^2
0.017622
2.107195
-0.046074
0.015742
1.430415
0.036902
1.119478
1.473136
-1.248555
0.3138
0.2007
0.2671
FDI(-1)
FDI(-1)^2
-0.337326
0.004917
1.239063
0.022524
-0.272243
0.218293
0.7963
0.8358
I
I^2
GX
-0.124946
0.000449
-0.410781
0.320765
0.003092
0.211171
-0.389524
0.145159
-1.945249
0.7129
0.8903
0.1093
GX^2
0.003635
0.001982
1.834399
0.1261
R-squared
0.830828
Mean dependent var
2.946476
Adjusted R-squared
S.E. of regression
0.221810
4.168879
S.D. dependent var
Akaike info criterion
4.725811
5.707889
Sum squared resid
Log likelihood
Durbin-Watson stat
86.89774
-49.49466
2.206906
Schwarz criterion
F-statistic
Prob(F-statistic)
6.640515
1.364209
0.391891
124
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Figure AII-1: Histogram Normality Test
10
Series: Residuals
Sample 1979 2002
Observations 24
8
6
4
2
0
-5
-4
-3
-2
-1
0
1
2
3
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
6.38E-16
0.132914
3.751848
-4.088201
1.753449
-0.400047
3.465264
Jarque-Bera
Probability
0.856620
0.651610
4
125
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Sensitivity Analysis
Table AII-18: Regression Results with Aid less debt forgiveness
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
Aid less Debt Forgiveness
-5.473454
0.137392
2.357369
0.100584
-2.321849
1.365947
0.0315
0.1879
FDI
S
GX
I
0.252867
0.242323
0.125939
-0.067634
0.086227
0.104015
0.040853
0.037432
2.932590
2.329687
3.082735
-1.806872
0.0085
0.0310
0.0061
0.0866
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.645932
0.552756
3.460983
227.5897
-63.08182
2.129714
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
0.576000
5.175204
5.526546
5.819076
6.932406
0.000773
126
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Table AII-19: Data Set
obs
Foreign
Direct
Investmen
t as share
of GDP
(FDI)
0.00
Annual
growth
rate of
GDP per
capita
(G)
-2.70
Annual
Growth
rate of
export
(GX)
Annual
Inflation
Rate (I)
Domestic
Savings as a
share of GDP
(S)
Aid less Debt
Forgiveness
as a share of
GDP (ALDR)
1978
Aid as
a
share
of
GDP
(A)
5.50
9.00
15.10
20.50
5.50
1979
6.50
0.11
-2.50
-10.00
17.90
21.60
6.50
1980
7.10
0.10
1.30
3.00
14.10
20.40
7.10
1981
11.50
0.31
1.30
-6.00
22.20
8.00
11.50
1982
8.10
0.92
-13.20
-26.00
20.60
7.70
8.10
1983
6.30
0.97
-6.40
-3.00
15.30
2.70
6.30
1984
5.30
1.03
-4.70
10.00
25.10
20.20
5.30
1985
6.00
0.04
2.90
6.00
15.00
22.00
6.00
1986
5.90
0.00
-0.30
-9.00
7.90
33.20
5.90
1987
7.80
0.00
1.50
-3.00
28.70
19.90
7.80
1988
6.60
0.00
-3.10
-10.00
39.90
16.80
6.60
1989
11.60
0.00
-4.40
-7.00
89.70
15.00
11.60
1990
42.60
0.00
-2.40
-9.00
63.60
14.00
41.50
1991
38.50
0.00
5.70
110.00
101.50
17.90
4.70
1992
24.50
39.81
7.50
19.00
28.20
16.90
24.50
1993
24.20
15.72
7.80
-1.00
12.00
21.70
17.10
1994
14.60
19.73
8.10
-3.00
12.40
14.20
13.30
1995
13.80
11.97
4.60
1.00
12.20
20.80
12.70
1996
20.10
8.36
7.50
9.00
7.10
23.90
19.10
1997
35.30
6.94
5.80
2.00
3.60
20.60
12.30
1998
13.00
6.13
-2.10
-5.00
4.60
16.90
1.40
1999
11.40
6.62
2.50
4.00
7.50
15.40
3.00
2000
15.10
9.42
-1.80
-2.00
6.10
8.00
11.90
2001
13.70
7.86
3.00
0.00
2.70
5.80
12.00
2002
9.00
6.03
-1.50
1.00
4.30
7.10
8.50
127
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Figure A1I-2: Time series graph of variables used in the econometric analysis
120
100
80
60
40
20
0
-20
-40
78
80
82
84
86
88
90
92
A
FD I
G
94
96
98
00
02
GX
I
S
Figure AII-3: Time Series Graph Growth and Aid
50
40
30
20
10
0
-10
-20
78
80
82
84
86
88
90
A
92
94
96
98
00
02
G
128
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BIBLIOGRAPHY
1. Alesina, A., & Dollar, D. (1998). “Who Gives Foreign Aid to Whom and Why?”
NBER Working Paper 6612. Cambrdige: National Bureau of Economic Research.
2. Babbie, E. (1999). The Practice of Social Research. New York: Wadsworth
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