Job density, productivity and the role
of transport
An overview of agglomeration benefits from transport investments and
implications for the transport portfolio
JUNE 2012
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please telephone Public Affairs Branch, Department of Transport, on (03) 9655 6000.
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Table of Contents
Executive Summary ................................................................................. 1
Introduction .............................................................................................. 2
Economic and fiscal context ......................................................................... 2
The twin challenges: infrastructure and productivity.................................. 4
Making the case for infrastructure investment ............................................... 5
City productivity: agglomeration and agglomeration economies ....... 5
Agglomeration economies and their sources.............................................. 7
Other explanations for the productivity of cities ......................................... 7
Firm selection ............................................................................................... 8
Sorting .......................................................................................................... 8
Types of agglomeration economies: urbanisation and localisation .......... 9
The empirical evidence for agglomeration economies ............................. 10
Transport’s role in facilitating productivity and agglomeration ........ 12
How transport improvements support agglomeration .................................. 13
Investment Appraisal – Cost-Benefit Analysis .................................... 14
Wider economic benefits and agglomeration economies ............................ 15
Attempts to Measure Agglomeration Economies ............................... 16
United Kingdom ........................................................................................... 17
CrossRail .................................................................................................... 18
New Zealand ................................................................................................. 19
Australia ....................................................................................................... 19
Infrastructure Australia................................................................................ 20
Application of WEBs in investment appraisal in Victoria.......................... 21
East-West Link Needs Assessment ............................................................ 21
WestLink..................................................................................................... 22
Melbourne Metro 1...................................................................................... 24
Methodologies and Measurement of Agglomeration Benefits........... 26
Criticisms of agglomeration assessments................................................. 26
Divergence in agglomeration elasticity estimates..................................... 27
Methodological issues in measurement..................................................... 28
Avoiding ‘Double counting’.......................................................................... 28
Controlling for bias...................................................................................... 28
Suitable data set ......................................................................................... 29
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Enhancing our knowledge..................................................................... 30
Further Study – Melbourne Metro – M2MPJ................................................ 30
Accessing better Victorian data sets ........................................................... 30
COAG Reform Council – Continuous Improvement Project ........................ 31
Ex Post evaluation ...................................................................................... 31
Conclusions............................................................................................ 32
Methodological improvements .................................................................... 32
Victorian Guidelines .................................................................................... 32
National Guidelines..................................................................................... 33
Next steps................................................................................................... 33
References.............................................................................................. 34
Appendix A – Crossrail Impact on Welfare and GDP.......................... 40
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Executive Summary
The costs and benefits of transport investment go well beyond the direct user
impacts and operator benefits traditionally considered in cost-benefit analysis. There
has been significant interest in recent years in the wider economic benefits of
transport driven by a desire to understand the link between transport provision and
economic performance.
This paper looks at wider economic benefits, and in particular, a type of wider
economic benefit known as agglomeration. Agglomeration economies exist
whenever firms become more productive through proximity to other firms.
This paper provides an overview of studies on agglomeration economies, as well as
a discussion of the relationship between agglomeration economies and transport
investment. Measuring agglomeration economies is critical to our understanding of
the role of transport in supporting these efficiencies and their impact on productivity
and economic growth.
A review of studies of agglomeration shows that doubling the job density of an area,
can result in improvements in productivity in the range of four to 13 per cent,
depending on the size, industry structure, and economic make-up of the location
studied. This is due to: the sharing of infrastructure and inputs; the sharing of ideas
(knowledge spill-overs) that occur due to close physical proximity and drive
innovation, and the ability to match skilled workers to jobs.
Transport investment can enable an increase in job density in two ways: by making
it attractive for firms to move into areas providing access to a large potential
workforce, and by increasing the number of jobs that are accessible to workers.
The methodology to quantify the relationship between employment clustering and
productivity and transport has grown in sophistication over the last decade. The UK
appraisal framework for incorporating wider economic benefits into the investment
appraisal process provided the first well thought out approach. This approach was
used to estimate the wider economic benefits for the CrossRail project in London.
The impact the project would have on productivity and central London growth
helped the project to secure government funding.
In the UK and New Zealand, estimates of agglomeration economies are of higher
quality than those published for Australia, as robust data at the firm level is not
available in Australia. However, the Department of Transport has been improving its
methodologies for assessing the agglomeration benefits of transport investments
and this report concludes that there is significant value in continuing this work.
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Introduction
In the last two decades there has been a significant advance in our knowledge of
the forces that drive the clustering of economic activity in particular locations – in
cities, industrial locations, education precincts and retail strips. While this spatial
dimension of economies has been recognised for many years, the theoretical
frameworks, tools and models to understand it are relatively recent.
The clustering of economic activity is referred to as ‘agglomeration’, and has both
positive and negative impacts. Positive impacts include the increased productivity of
firms in economic clusters as they benefit from deeper labour pools from which to
draw workers, wider markets allowing greater specialisation, and knowledge spillovers that lead to higher levels of ideas-generation and innovation. On the negative
side, agglomeration can raise costs for business, such as land costs, congestion,
and the price of labour.
Transportation has a central role in supporting the benefits of agglomeration and
mitigating its costs. It is therefore critical in supporting the productivity of firms that is
driven by agglomeration.
This paper has been developed to inform the Victorian transport portfolio’s
understanding of agglomeration benefits and costs, and to provide advice about
how we can improve our methodologies for assessing transport’s contribution to
agglomeration benefits (or agglomeration economies). The paper examines the
evidence for the existence of agglomeration economies and investigates various
methods and issues related to the measurement of transport’s contribution to
agglomeration economies in various overseas jurisdictions, as well as in Victoria.
Following a short section on the economic and fiscal context, the paper moves to a
discussion of agglomeration including the causes, disbenefits and evidence for
agglomeration economies. Background is then provided on the ways in which
transport supports agglomeration. Next, the paper discusses traditional cost-benefit
analysis, with emphasis on the costs and benefits accounted for in the traditional
evaluation process. This leads into a discussion of the assessment of wider
economic benefits (WEBs) of transport projects (which include agglomeration
benefits). Case studies are presented outlining how agglomeration economies have
been integrated in various appraisal processes in the United Kingdom, New Zealand
and Australia. Key issues on measurement and methodology are then discussed,
followed by opportunities for further work, conclusions and recommendations.
Economic and fiscal context
Victoria benefits from being a compact State with a settlement pattern based on a
strong, centrally-positioned capital city surrounded by an arc of regional cities, the
largest of which are within relatively short commuting distance from Melbourne.
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Forces shaping the clustering of economic activity in Victoria have been, and
continue to be, relatively strong. Melbourne contributes approximately 78 per cent
($235.1 billion) of Victoria’s Gross State Product of $301.4 billion in 2010 (VCEC
2011, ABS 2010). Within Melbourne a similar pattern emerges. Nearly 32 per cent
of Melbourne’s economic output is generated in the three inner municipalities –
Melbourne, Yarra and Port Philip (SGS Economics and Planning, 2011a). Links
between Melbourne and regional Victoria are critical, contributing to the economies
of both Melbourne and the State in general.
In 2011, the Governor of the Reserve Bank of Australia, Glenn Stevens, spoke of
the complex interactions of forces at work on the national economy. This includes
commodity and financial cycles, population and migration flows and changes in
industry composition – a strong resources sector, a growing business services
sector, and tough conditions for trade exposed manufacturing.
Changes in the national economy have influenced and will continue to influence
shifts in state and regional economies. The structure of the Victorian economy has
been changing over time with considerable land use and transport impacts (DOT
and DPCD, 2011). Key points to note are:
industries are changing – finance and professional services are now much more
important and the most significant contributor to Gross State Product, but
manufacturing remains critical to Victoria’s ongoing economic prosperity
inner Melbourne is a highly favoured location for key new industries for a range
of reasons including amenity, connectivity and accessibility
inner Melbourne’s capacity to expand over coming years is a key competitive
advantage over comparable cities in Australia and globally.
Over time, the continued growth of employment in inner Melbourne has
corresponded with changes in the industry contribution to Victorian Gross State
Product. Inner Melbourne is the preferred location for firms providing financial and
professional services.
The central part of Melbourne has a number of fundamental strengths. It has a welllaid out CBD, a mixed transport system and room to expand into centrally-located
urban renewal sites. Much of the usual capital city infrastructure (international sports
precincts, arts centres, major university campuses) are within two kilometres of
Melbourne’s CBD. The centrally-located Port of Melbourne brings significant
benefits but also some specific challenges to the city.
A key feature of Melbourne’s ongoing competitiveness and capacity for productivity
improvement is that the central city is an attractive place to live and work. It has
significant capacity to accommodate more employment, despite its recent increasing
share of jobs. Central Melbourne (defined as the CBD and parts of the inner most
suburbs and St. Kilda Roads) had 490,000 workers at the end of June 2011 and
tipped to go over the half-million mark in the third quarter of 2011. This compared to
around 270,000 in 1995 (Dunckley 2011).
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There are, however, some challenges relating to Victoria’s public finances, which
have been characterised by expenditure growth outstripping revenue growth for the
last decade. The Victorian Government’s fiscal strategy is to keep the budget in
surplus, carefully target spending and keep debt to sustainable levels (Department
of Treasury and Finance, 2011, p. 1).
The process for getting Victoria’s finances back on track includes increasing the
rigour and oversight of the development and assessment processes for asset
investment proposals, particularly high-value and high-risk investments. It also
involves lifting the percentage of annual infrastructure investment which is funded
from recurrent cash flows from the current 41 per cent to 94 per cent by 2014-15
(Department of Treasury and Finance, 2011, pp. 4, 5).
The twin challenges: infrastructure and productivity
From a competitiveness perspective, Victoria and Melbourne are doing relatively
well. A recent benchmarking information paper, provided as part of the Victorian
Competition and Efficiency Commission’s (VCEC’s) (2011) Inquiry into a Statebased Reform Agenda, ranks Victoria as the most competitive state in the country.
Victoria’s productivity, on the other hand, is relatively poor. Victoria’s labour
productivity growth rates have been slowing over the last 10 years. VCEC’s
productivity information paper shows Victoria’s labour productivity and multi-factor
productivity (MFP) declining over the last 10 years, with MFP negative in recent
years. This decline is spread across industries.
The Victorian Treasurer, the Hon. Kim Wells, MP, has pointed to our over-reliance
on ‘population growth to underpin economic growth’. He stated that ‘productivity
growth is the main driver of higher living standards and economic prosperity,’ but
noted that in Victoria in the past decade it had fallen from an average of 2.8 per cent
a year in the five years to 1999-2000 to an average of just 0.7 per cent a year in the
five years to 2009-10. Victoria’s productivity growth exceeded the national average
in the 1990s but ‘Victoria now finds itself below the national average productivity
growth rate’ (Department of Treasury and Finance 2011).
The World Economic Forum, in its most recent Global Competitiveness Report,
ranked Australia 34th for overall quality of infrastructure, noting that inadequate
infrastructure is one of the most problematic factors for doing business. The OECD’s
2010 report on Australia cites the resolution of infrastructure bottlenecks and
improvement in core energy and communication activities as essential for the
country to meet the challenges of globalisation and to take full advantage of the
emergence of China and India as major markets.
Victoria faces significant budgetary pressures, needing to manage and control
increasing debt levels while also seeking to renew and refresh infrastructure and
address service needs. The 2011-12 Budget Update indicates that with ongoing
international uncertainty, a weaker national economy and a high Australian dollar,
the Victorian Government intends to keep public debt low to maintain economic
confidence. The government’s fiscal and economic strategy (2011-12 Budget
4
Update, p.3) includes investing in quality infrastructure, with a greater focus on
funding this through recurrent cash flows rather than increasing debt levels.
Significant challenges are faced in maintaining and upgrading the state’s asset and
infrastructure base which will be essential in sustaining and improving Victorian
productivity levels. Rapid population growth, demographic ageing, and economic
and structural change will compound these pressures.
These two challenges of productivity growth and infrastructure investment are
interrelated, with transport infrastructure provision one key to boosting productivity
levels and economic growth. As the Unites States Treasury has noted, ‘research
has shown that well designed infrastructure investments can raise economic growth,
productivity and land values’.
Making the case for infrastructure investment
In the Victorian context – fiscal pressures, productivity enhancements as a goal, and
growing needs for infrastructure investments – transport projects will face increasing
scrutiny. The robustness of investment appraisal and business case preparation will
be increasingly important, both at the state level and in Victoria’s engagement with
the Commonwealth through Infrastructure Australia and the Department of
Infrastructure and Transport. Making the case for investment in new infrastructure,
especially large scale, high investment city shaping projects, will be more difficult.
The challenge in making the case for new infrastructure projects also relates to the
complexity in understanding the implications of these investments, particularly their
impact on productivity. Although it is widely acknowledged that infrastructure
investments can raise productivity and grow the economy, it is becoming
increasingly clear that standard cost-benefit analyses do not provide good evidence
of the productivity enhancing nature of various investment options. This reflects the
level of uncertainty and the absence of coherent guidelines around measuring
productivity gains, which makes the identification of high-value high-return
infrastructure projects more difficult.
In recent years there have been advances in our understanding and measurement
of what are known as ‘wider economic benefits’ of transport projects – that is
economic benefits that are not captured in traditional cost-benefit analyses. The
most important of these advances have been in the field of agglomeration
economies.
City productivity: agglomeration and agglomeration
economies
Economic activity concentrates in geographical space – a phenomenon known as
agglomeration. This occurs at a range of spatial levels. One type of agglomeration
occurs when a small number of shops or restaurants cluster in a neighbourhood.
Another occurs when firms in similar industries cluster together, as in Silicon Valley.
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At yet another level agglomeration can be found in the formation of cities across the
range of city size, from London at one scale to Bendigo at a different scale.
The Industry Atlas of Victoria (Department of Business and Innovation 2011) shows
7,185 businesses with turnover greater than $10 million in 2009. The Atlas provides
a sense of the levels of spatial agglomeration of large firms in Victoria. (The source
of the information is Counts of Australian Businesses, including entries and exits,
ABS catalogue 8165.0).
In Melbourne most such businesses are situated in four locations, the industrial hub
of the south-east around Dandenong, the western industrial region around Sunshine
and Werribee, the northern industrial area of Broadmeadows; and the knowledge
intensive services centre of the City of Melbourne where most professional,
scientific and technical services and finance and insurance services are based.
In regional Victoria the large businesses, with turnovers of $10 million and over, are
based in the major regional centres of Mildura, Wodonga, Shepparton, Ballarat,
Warrnambool, Geelong, Morwell and Traralgon. Most of these high-turnover
companies in regional Victoria are large-scale manufacturing plants.
As an economic phenomenon, agglomeration received very little attention until the
early 1990s, despite some of the core ideas going back to the work of Adam Smith
(1776) and later Alfred Marshall (1890).
But recently, agglomeration has become the subject of extensive study
internationally, including work undertaken by the OECD and the International
Transport Forum. This interest has mirrored the growing interest in cities and has
been driven by a desire to understand the reasons for economic agglomeration, its
impact on the economic performance of cities, the trade-offs involved, and what
governments can do to support agglomeration where this has a benefit for the state.
The first serious attempts to understand the forces underpinning agglomeration
came from Paul Krugman. He developed a simple model that explored the effects of
the centripetal forces that concentrate economic activity and the centrifugal forces
that disperse activity, generating a whole field of research known as the New
Economic Geography.
The centrifugal forces that disperse economic activity include high land prices, high
wage costs, congestion, pollution, crime and socio-economic polarisation. Urban
density has costs. On average big cities have more congestion, pollution and crime
than smaller cities (Glaeser 1998, Glaeser and Sacerdote 1999).
Kahn (2009) reviewed these costs of urban density in the United States and their
trends over time. In most metropolitan areas in the US, commute times rise with
distance to the city. Travel speeds tend to be slowest in big metropolitan areas, and
this congestion is one of the big costs of living in a metropolitan area. However,
pollution problems and crime rates have been falling in big US cities over the past
decade. The decline in pollution is linked to the exodus of manufacturing from big
cities as well as the rise of catalytic converters and lower levels of car emissions.
The reasons behind declining crime rates are less well understood.
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Agglomeration economies and their sources
In large cities the dispersal forces can be significant. Why would firms locate in
areas where wages and land are so expensive? The reason for firms clustering
together spatially is that they derive benefits from collocation that they wouldn’t
derive in other ways, and that exceed the centrifugal forces driving dispersal.
These benefits are referred to as economies and can be internal or external to the
firm. Agglomeration economies are those that are external to the firm and come
from the local density and diversity of firms, workers and residents. Agglomeration
economies exist whenever people become more productive through proximity to
others.
The three traditional sources for agglomeration economies (identified by Marshall,
1890) are sharing, matching and learning.
Sharing refers to two things: the sharing of infrastructure with high fixed costs
and large economies of scale (such as, airports, ports, road networks and rail
transit networks), and the sharing of specialised input suppliers.
Matching refers to the ability to access a large pool of skilled labour so that
firms may more effectively address their particular skill needs, and for
employees to have access to a greater range of job opportunities to find a good
match with their skills and development goals.
Learning relates to the development, adoption and transfer of new and
advanced technologies, improved business practices and knowledge spillovers.
Close physical proximity increases the flow of knowledge by increasing the
amount of face-to-face interaction. This interaction has a particular effect on
productivity when information is imperfect, rapidly-changing or not easily
codified. These conditions are present in many knowledge-based industries.
Transport costs (or the absence of them) are the key to understanding
agglomeration economies. Sharing, matching and learning can occur in dispersed
economic environments, but they incur greater cost. Density reduces physical space
between people and firms, and reduces transport costs for goods, people and ideas.
More recently other sources of agglomeration economies have been suggested,
most importantly home market effects where the concentration of demand
encourages agglomeration.
Other explanations for the productivity of cities
The fact that firms located in dense environments are more productive does not in
itself indicate that it is the density that causes the higher productivity. The causes
may lie elsewhere. Alternative explanations have been offered for the greater
productivity of firms in cities. The two main alternatives are firm selection and firm
sorting.
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Recent studies shown below indicate that earlier pioneering analyses based on
aggregate data (city size, regional GDP, manufacturing wages in an industry in a
city) have overstated agglomeration benefits compared to later research at the firm
or worker level. Today’s estimates are around half that of earlier results.
Firm selection
‘Firm selection’ refers to the possibility that, since larger markets attract more firms,
dense cities are tougher and more competitive places in which to operate and where
only the fittest survive. In such environments market selection will lead to less
productive firms exiting, with the result that the remaining firms have higher average
productivity.
If firms are on average more productive in larger markets because only the more
productive survive, then higher productivity is not caused by agglomeration
economies but is the result of a selection process.
Using 788,200 observations of New Zealand businesses, Maré and Graham
initially estimated an agglomeration elasticity of 17 per cent, but this could
overstate the true impact of agglomeration on productivity as a result of the
sorting of high-productivity firms into high-density areas. They concluded that a
lower estimate of 6.9 per cent be used in the New Zealand official economic
appraisal guidelines.
Following on from an earlier extensive study of French metropolitan firms
showing that productivity differences between areas are explained mostly by
agglomeration, in their later analysis, again using micro-data on French firms,
Combes, Pierre-Philippe, Duranton, Puga and Roux (2011) find that selection
bias does not appear to be important in estimating agglomeration economies.
Sorting
Workers and firms may also choose locations that reflect their own levels of
productivity, so that the measured and unmeasured productive abilities of the local
labour force vary. This is a process known as ‘sorting’. Highly productive firms may
choose high amenity areas like central cities because those locations are attractive
to the workers they are trying to attract. Workers expect and achieve higher mean
wages in areas specialised in skill-intensive industries.
Using micro-data on each of 2.6 million French workers, Combes, Duranton and
Gobillon (2007) find that sorting explains about half of the spatial disparities
across French regions.
Carlino (2011) cites an unpublished paper by Baum-Snow and Pavan in 2010
which estimates that agglomeration economies and sorting each account for
about one-half of the urban wage premium in the US.
Venables’ paper (2010) on productivity in cities illustrates how the high costs of
living in cities induce self-selection by workers, so that more expensive cities have
8
disproportionately many high-ability workers with ‘self-selection’ improving the
quality of matches in such cities.
Carlino (2011) also suggests that a city’s prosperity and growth depends crucially on
its ability to attract and retain highly skilled workers. He cites Jesse Shapiro who has
shown that the amenities that cities offer are especially attractive to high-skill
workers, who can stimulate employment and population growth. Skilled workers
may adjust more rapidly to negative economic shocks, and educated workers may
find it much easier to adapt their activities to changing economic incentives
presented by emerging technologies.
Behrens (2011) found that agglomeration economies, labour sorting and firm
selections make city sizes follow a smooth statistical distribution. The shape of the
distribution is consistent with the mathematical statistical Zipf’s Law, found in many
types of data in the social and physical sciences.
Types of agglomeration economies: urbanisation and localisation
While external economies exist when the scale of the urban environment adds to
productivity, Rosenthal and Strange (2004) have examined the dimensions of those
externalities. They distinguish ‘localisation economies’ from ‘urbanisation
economies’.
‘Localisation economies’ describe the efficiency gains arising from increased density
of activity within a particular industry operating in close proximity. These economies
are external to firms but internal to the industry. The main sources of benefits are
similar to those driving agglomeration economies generally:
proximity increases the ease of communication facilitating technological
spillovers between firms within the same industry
industrial agglomeration can drive the efficient provision of intermediate inputs to
firms in greater variety and at a lower cost due to the growth of subsidiary trades
firms can share larger markets for their inputs; in particular they can access and
share a larger local skilled labour pool.
‘Urbanisation economies’ describes the productive advantages that accrue to firms
through location in large population centres such as cities. These economies are
external to the firm and to the industry but internal to cities. Firms benefit from the
scale of markets, from the proximity of market areas for inputs and outputs and from
good infrastructure and public service provision.
Graham’s study (2007) using UK firm-level data for 27 industry groups found that
localisation economies tend to exist over relatively small spatial scales, with positive
localisation externalities identified for 13 industry groups within a 10 kilometre radius
of the firm. Localisation elasticities (that is the strength of the connection between
density and productivity) tend to be high for manufacturing industries while
urbanisation elasticities are higher for the services sector. Urbanisation elasticities
across all sectors tend to be higher than localisation elasticities.
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The distinction between localisation and urbanisation economies is important to the
measurement and understanding of productivity gains from government investment,
for example those intended to support a particular industry, such as a biotech
precinct. Potential productivity gains that come from the density of firms within
particular industries (which is more an issue of spatial organisation) may require a
very different response from government than productivity gains that come from
general density in an urban environment.
Projects outside the metropolitan area may also claim these agglomeration
economies.
The empirical evidence for agglomeration economies
The concentration of both industries and population in a particular location is clear to
everyday experience. The very existence of cities confirms this and is, in itself, a
striking fact. Indeed the foremost question of urban economists is why cities exist.
Agglomeration can be measured in a number of ways. Population size and
concentration of industrial plants in a particular location are examples but these are
inadequate for measuring the density of economic activity in a city.
The standard measure of agglomeration used in the UK is effective job density
(EJD). In Australia, SGS Economics and Planning has developed and used a
measure of EJD in its studies. Effective job density measures the numbers of jobs
accessible from a particular location within a specified travel time.
In order to measure agglomeration economies we need to be able to determine the
impact of agglomeration on productivity. A significant body of empirical work has
sought to identify agglomeration economies and to quantify their effects on
productivity. There are a number of theories supporting agglomeration economies
and empirical studies that have confirmed their existence. However estimates of the
size of this positive externality have tended to vary in magnitude.
In explaining the large difference in labour productivity across the US, Ciccone and
Hall (1996) examined the role of increasing returns to density. That is, the
phenomenon that firms can generate higher returns in dense environments. Using
data on gross output, they found that a doubling of employment density increases
average labour productivity by around six per cent. More than half the variance in
output per worker was explained by differences in density of economic activity.
Venables (2004) developed a theoretical model demonstrating the links between
transport provision and agglomeration. While accepting that the debate about the
magnitude of the relationship is far from closed, he saw the empirical evidence as
suggesting a positive city-size productivity relationship. He proved that linkages
between firms within the city results in an increase in the effective density of the
cluster and that, by relaxing constraints on access to the centre, overall city
employment increases.
Venables intended to demonstrate that the agglomeration forces that cause cities to
exist provide additional benefits that should be included in urban transport appraisal.
These effects can be large, typically yielding total gains several times larger than
10
that resulting from standard cost-benefit analysis (CBA). Venables was also
suggesting how to encompass these effects in transport investment appraisal.
Building on Venables’ work and other research linking productivity to transport
investment via effects on city size, Graham (2006) developed aggregate estimates
of density externalities to demonstrate the relationship, modelling a measure
incorporating both proximity and scale of economic activity. He developed an
effective density measure of agglomeration that captured both elements, providing a
flexible measure of urbanisation that can be constructed for small areas and
incorporating a transport dimension.
Graham calculated a weighted average urbanisation elasticity of 12.9 per cent for
the economy as a whole. His results showed that agglomeration economies are
present in many manufacturing industries and can be substantial in most service
industries. If transport changes the densities of labour available to firms, for instance
through a reduction in travel time or in the cost of travel, Graham concluded there
are likely to be positive gains from agglomeration and that having reliable estimates
of the density-productivity relationship allows quantification of these wider economic
benefits.
Many studies have since quantified the strength of the relationship between
economic productivity and concentration of activity. Generally, these studies have
shown a positive correlation between average productivity and local market size and
density, with the elasticity of labour and firm productivity with respect to size and
density typically in the three per cent to eight per cent range (Rosenthal and Strange
2004).
Graham (2005) found the majority of empirical estimates of agglomeration
elasticities to be between one per cent and 10 per cent. In a more extensive metaanalysis, Melo et al (2008) found the median estimate to be 4.1 per cent. Maré and
Graham (2010) presented a set of agglomeration elasticity estimates from New
Zealand micro data. This showed an aggregate agglomeration elasticity of 17 per
cent. Controlling for firm ‘sorting’ bias yielded an elasticity of 6.9 per cent.
These results are similar to Trubka’s (2009) estimates for Melbourne, which has a
productivity elasticity of 7.4 per cent, meaning that doubling the density in a centre
of Melbourne would result in an average wage (labour productivity) increase of 7.4
per cent across the existing occupations. SGS’s agglomeration elasticity estimate
for Melbourne is eight per cent, which is in the middle range of the productivity
elasticities with respect to EJD from overseas studies (five to 13 per cent) and is
similar to the seven per cent estimated by Trubka. This is discussed in further detail
in the paper (Melbourne Metro section).
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Transport’s role in facilitating productivity and
agglomeration
Transport’s role in facilitating agglomeration has varied over time. In the 19th
century, moving goods over land was expensive, access to transport hubs such as
Chicago and New York made firms much more productive. These cities grew up
around transport modes and many of the early industries in both places arose
because of goods that were being shipped through (Glaeser, 2008).
Today, agglomeration economies are much less about the cost of moving goods.
Over the twentieth century, the real cost of moving a ton a mile by rail has declined
by more than 90 per cent (Glaeser and Kohlhase, 2004). Agglomeration economies
these days are more closely associated with reducing travel time for people and
their ideas. The cost of a person’s time (in terms of, say, wages foregone) has
increased over time. Reducing the cost of a person’s time in getting around a city,
rather than the cost of transport itself, is the major contribution in the early 21st
century of transport to agglomeration economies. These agglomeration economies
are a significant factor in explaining how cities are increasingly oriented around
services.
Transport plays an important role in the production of goods and services and
impacts on all sectors of the economy. The efficiency with which people and freight
is transported makes an important contribution to productivity. Freight movements
and other business to business interaction is impeded by congestion on our road
system and the agglomeration of business activity in city centres will stall without
addressing crowding issues by adding capacity to our train and tram networks.
There are four main areas where transport investments can lead to improved
productivity:
making it easier for businesses-to-business interaction by enabling the clustering
of related economic activities (agglomeration)
supporting human capital development through improving access to higher
skilled jobs, and accessibility of education and training
improving Victorian business access to markets
keeping business transport costs down.
Transport infrastructure opens up markets and creates conditions that influence
economic structure and performance (Lakshmanan, 2007). However, transport
infrastructure and transport improvements are not sufficient to sustain economic and
productivity growth. Lakshmanan and Chaterjee (2005) conclude that sustained
improvements in transportation – when they go hand in hand with parallel
improvements in information and production technologies and institutional structures
– cause structural and developmental transformation in the economy.
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These are represented graphically in Figure 1 (Lakshmanan 2007), showing the
mechanisms and processes underlying the wider economic benefits of transport
infrastructure investments.
Figure 1: Transport Infrastructure and Economy Wide Benefits
Source: Lakshmanan (2007)
How transport improvements support agglomeration
There is a very particular set of circumstances under which agglomeration
economies may be enabled through transport investments. Not all transport projects
foster agglomeration economies. The Bureau of Transport Economics, (1999) states
that under certain circumstances, a concentrated land-use pattern can lead to more
interpersonal contacts, increased networking, productivity and community
interaction which can lead to some agglomeration economies that escape
measurement in a conventional CBA. This is qualified by the proviso that only some
transport projects foster agglomeration while other projects may have no impact on
agglomeration or may cause dispersion of economic activity.
13
In a wide-ranging review of the literature, Chatman and Noland (2011) note that
there are almost no direct studies in the published academic literature of the impact
of public transport investments on agglomeration. Although they agree that public
transport infrastructure investments or service improvements could lead to higher
density employment clusters and to larger, denser more diverse cities. The
hypothesis is that there would be large effects in big cities with significant transport
impediments and virtually none in cities with no road congestion and little demand
for public transport.
Infrastructure Australia emphasises that:
only certain initiatives addressing a specific set of economic fundamentals will
generate wider economic benefits
significant wider economic benefits will only be found in initiatives with strong
traditional benefits
wider economic benefits may well be negative for some initiatives.
Investment Appraisal – Cost-Benefit Analysis
The standard approach to investment evaluation is cost-benefit analysis (CBA). The
aim of this analysis is to determine which investment project or which option among
a range of possible options represents best ‘value for money’.
CBA involves estimation of benefits to users of the transport network and to
suppliers of transport services. Benefits accruing to transport users include travel
time savings, reduced vehicle operating costs and improved safety. Other benefits
include improvements in service frequency, reliability and comfort. Benefits to
transport operators are savings in operating costs and in some cases, in capital
expenses.
Cost-benefit analysis applies a welfare economics methodology in which
consumers’ willingness to pay forms the basis of assessing benefits. It is a
methodological approach which gives primacy to the incorporation (in the evaluation
process) of direct user benefits. There are various assumptions embedded in the
process and there are inherent difficulties in quantifying and valuing certain benefits
and costs as well as complexities in the use of demand forecasts and projections
into the future.
Another complication is the need to consider results within an overall project
assessment which addresses both quantifiable and non-quantifiable effects.
In the Victorian Department of Transport’s (2010) CBA guidelines, the typical
benefits of a transport related project to be incorporated and assessed in the
investment appraisal process encompass:
14
savings in travel time – this is derived by multiplying default values of time per
hour (as determined by Australian Transport Council 2006 guidelines) by the
number of travel hours saved by the project
reduced vehicle operating costs – derived by multiplying the default operating
cost per vehicle kilometre (based on Austroads 2008 guidelines) by the number
of vehicle kilometres saved by the project
reduced accident costs – quantified by estimating how many accidents or
crashes may be avoided following a project and estimating the likely unit costs of
an accident or crash had it occurred, using default values from Austroads (2008)
reduced environmental damage – estimation of local, regional and global
environmental costs through accounting for avoidance of air pollution,
greenhouse gas emissions, noise pollution and water contamination using
default values from Austroads (2008) guidelines.
Costs included in the transport appraisal process include capital costs and recurrent
costs.
Wider economic benefits and agglomeration economies
In recent years there has been significant interest in the assessment of a range of
costs and benefits of transport investment that go well beyond those traditionally
considered in cost-benefit analysis.
This interest has stemmed from the limitations of focusing on user benefits of
transport investments at the expense of broader impacts to the economy. These
broader impacts are referred to as wider economic benefits. Agglomeration
economies are a subset of these wider economic benefits.
Some of the most advanced work in this area has occurred in the UK, where
guidance on the assessment of wider economic benefits includes the following four
key elements (UK Department for Transport, 2009):
Move To More Productive Jobs (M2MPJ)
M2MPJ measures the additional output of the new jobs that would be enabled
in an economic cluster through a new transport initiative. The assumption is
that the new jobs will be more productive in a dense environment (for the
reasons outlined above) than they would be if they existed elsewhere and that
this improvement in productivity is a benefit to the broader economy not
captured in traditional CBA. It is the net gain in output that needs to be
captured here, not simply the total output from each new job enabled.
Agglomeration
Agglomeration (sometimes known as ‘pure agglomeration’ to distinguish it
from M2MPJ, which also measures an agglomeration benefit) measures the
growth in productivity of existing workers in a cluster as the density of
employment around them increases.
15
Output change in imperfectly competitive markets
Reductions in transport costs can allow firms to increase output. This increase
in output is counted in traditional CBA as a business user benefit. However the
calculation assumes markets are perfectly competitive – the welfare gain is
calculated on the basis of the marginal cost of the increased output.
When firms operate in imperfectly competitive markets they set prices above
their marginal costs to earn quasi-monopoly profits. There will be greater
benefits in imperfectly competitive markets in excess of the marginal cost of
increasing the output, because a firm can set prices above marginal costs.
The difference between price and marginal cost, in the aggregate, can be
significant.
Labour supply impacts
Transport costs are likely to affect the overall costs and benefits to an
individual from working. In deciding whether or not to work, an individual will
weigh travel costs against the wage rate of the job travelled to. A change in
transport costs is therefore likely to affect the incentives of individuals to work
and hence the overall level of labour supplied in the economy.
Of the wider economic benefits, there has been a wealth of studies and critiques on
agglomeration economies. Recently, there have been attempts towards quantifying
M2MPJ as one of the wider economic benefits for consideration in transport
appraisal. However, other wider economic benefits do not appear to have been as
prevalent within the literature due to the difficulty in measuring their effects.
Attempts to Measure Agglomeration Economies
From a transport appraisal perspective, there are key steps that need to be taken to
determine a transport investment’s impact on productivity and agglomeration. First,
a measure of agglomeration is necessary. Throughout this paper effective job
density has been highlighted as the most suitable measure for agglomeration
currently used.
Second, the calculation of specific elasticities, for both urbanisation and localisation
economies and for each economic sector, is an integral component in incorporating
agglomeration economies in transport appraisal. These elasticities are measures of
the strength of the relationship between economic density and productivity.
Thirdly, proponents need to determine if the benefits from the project can be
attributed to agglomeration economies and not other factors such as firm selection
or sorting. This is in line with understanding the role that transport plays in
supporting density.
16
The following case studies highlight how agglomeration economies have been
integrated in various appraisal processes in the UK, New Zealand and Australia.
United Kingdom
The UK appraisal framework (New Approach to Transport Appraisal, known as
NATA) aims to capture the benefits society derives from a project in a number of
specific areas: climate change; support of economic growth; promotion of equal
opportunity; the natural environment; and better safety, security and health.
In 2005, based on Graham’s work, a UK Department for Transport discussion paper
outlined an approach to estimating wider economic benefits not captured in existing
appraisal methods. The following year, the Department for Transport provided a
summary of the nature of the main wider economic benefits (those outlined in the
previous section), the reasons for them and methodology for estimating wider
economic benefit values.
Eddington’s study for the UK Department for Transport (2006) found the inclusion of
wider GDP impacts – positive and negative – was an important aspect of the overall
cost-benefit assessment. The results for schemes undertaken in urban networks
were particularly boosted because of the agglomeration and labour market benefits
with an average uplift of the benefit-cost ratio (BCR) of around 7 per cent for urban
projects. Agglomeration impacts were greatest for schemes in London, with
additional GDP benefits (from agglomeration) of 30 per cent over and above direct
time savings captured in traditional appraisal. Other cities such as Manchester,
Leeds and Edinburgh also showed the significance of agglomeration economies
with additional benefits in the region of 10 per cent above journey time savings.
More recent estimates are much lower.
An extensive two-year consultation to refresh NATA included how best to
incorporate assessment of wider impacts in the appraisal process. In June 2010,
some limited changes in appraisal were announced, but the Department for
Transport left relatively unchanged the Wider Economic Benefits Transport Analysis
Guidance (WebTag): The Wider Economics Sub-objective is still in the form of draft
guidance only for public consultation and for reference and application by project
proponents.
The UK guidance requires quantification of the constraint presented by transport on
the level of agglomeration and concentration of economic activity. The change in
overall economic performance of an area resulting from removal of the constraint is
then evaluated.
Agglomeration economies are assessed using evidence of the relationship
between changes in agglomeration (measured as effective density) and productivity
(Graham 2006). Effective density is an employment accessibility measure based on
official employment data and journey costs for work and commuting travel.
The welfare impact from output change in imperfectly competitive markets is
estimated as a fixed proportion of total user benefits on business and freight
journeys identified in traditional CBA. The up-rate is currently 10 per cent.
17
The additional value to the economy resulting from a change in the overall labour
supply due to transport improvements affecting the number of people attracted into
work encompasses:
estimation of total commuting costs and travel time savings for workers
commuting from a zone
assessment of how the change in benefit from working will impact on the overall
amount of labour supplied using ‘return to work’ elasticities
multiplying the change in labour participation by the wage of the marginal-less
productive worker. The net wider impact is the amount of taxation paid on the
additional output.
Move to More Productive Jobs (M2MPJ) involves modelling the impact of a
scheme on changes in employment location between areas with changes having the
capacity to affect the overall productivity of employment and with the effects
estimated using an index of productivity differentials for local authority districts.
While the assessment of M2MPJ is not a core requirement, the UK guidelines set
out an approach for estimating the move to more productive jobs, requiring the use
of a Land Use Transport Interaction model.
Labour supply impacts and imperfect competition impacts are to be assessed for all
projects with a scheme costing more than £20 million while agglomeration is only
necessary if the scheme is near an economic centre or large employment area. The
appraisal of the move to more/less productive jobs requires a land-use transport
interaction model so is not a core requirement.
CrossRail
One of the initial estimations of wider economic benefits using the UK guidance was
for the CrossRail project in London, an underground east-west rail link connecting
existing rail networks on each side of the city.
An original economic appraisal had concentrated only on direct user benefits –
savings in time and comfort for travellers – which were assumed to capture all of the
economic benefits.
The project was expected to deliver significant capacity and accessibility benefits to
the city, estimated at about £12.8 billion (net present value) to transport users. But
the overall project cost gave a benefit-cost ratio (BCR) which was not sufficient to
secure government funding.
Buchanan (2007) extended that analysis by developing an approach which valued
the impact of CrossRail on central London growth and productivity. A key aspect of
this was the quantification of potential employment growth through to 2076 and
calculation of how much of this potential employment growth would be curtailed if
limited transport capacity resulted in ‘crowding out’, with passengers unable or
refusing to travel on heavily overcrowded lines.
18
Buchanan estimated that wider economic benefits would add additional welfare
benefits of £22 billion and have a GDP impact of £44 billion. These were
(respectively) 1.7 and 9 times more than the conventional welfare and GDP
benefits.
Buchanan then looked at the very long term, encompassing the potential of
employment growth in the city within low, medium and high scenarios. In the ‘high
scenario’, wider economic benefits contributed an additional £61.9 billion to the GDP
and £29.0 billion in additional welfare benefits (see Appendix A for details).
New Zealand
In New Zealand there has also been recognition in the investment appraisal process
in recent years that transportation can have a significant impact on the density of
economic activity and the economies that can result from this density.
As with Victoria, the economic evaluation framework for transport activities in New
Zealand had been based on evaluating direct benefits to transport users and private
transport operators. Reorganisation of industry and households to take advantage of
changes in accessibility created by improved transport had been regarded as a
lagged effect of secondary importance that was difficult to quantify.
The New Zealand Transport Agency and Motu Infrastructure funded a study on
agglomeration elasticities. Maré and Graham (2010) provided the first set of
agglomeration estimates directly estimated from the Prototype Longitudinal
Business Database of Statistics New Zealand (1999 to 2007). Services sectors such
as finance and insurance and property/business services were found to have the
largest estimates for industry specific agglomeration elasticities. Agglomeration
elasticities were also found to vary across regions.
New Zealand investment appraisal guidance now states that transport investments
can render a larger scale of activity more accessible by reducing travel time or the
costs of travel, giving rise to positive agglomeration benefits. Conversely, where
transport systems are weak or inefficient, they may inhibit development and
realisation of agglomeration benefits.
The Economic Evaluation Manual (New Zealand Transport Agency 2010) specifies
the two types of agglomeration economies discussed earlier in this paper –
localisation economies and urbanisation economies.
The required degree of spatial concentration of economic activity for realising
agglomeration benefits is considered only likely to occur in major industrial and
urban centres and that only large and complex transport initiatives will provide
relevant conditions to justify analysis of agglomeration benefits.
Australia
In Australia there is currently no reference to agglomeration benefits or wider
economic benefits within the National Guidelines for Transport System Management
in Australia (Australian Transport Council 2006). The Victorian Department of
19
Transport’s (DOT) own Guidelines for Cost-Benefit Analysis provide no advice on
wider economic benefits and agglomeration economies.
The vast majority of projects put up by DOT through the Gateway Review process
do not recognise or assess broader economic benefits.
A review of the National Guidelines has recently been started. The review will
include harmonisation with Infrastructure Australia guidance (see below) and
guidance on the applicability and calculation of wider economic benefits (WEBs) and
agglomeration economies.
Agglomeration economies will be given particular attention in the review. The formal
terms of reference for the review state that since the National Guidelines were
initially published in 2004, the imperative for guidance on methodologies in transport
planning and project appraisal has been heightened with the creation of
Infrastructure Australia and advances in project appraisal methodologies such as
WEBs.
Infrastructure Australia
Infrastructure Australia advises the Australian Government on the nation’s current
and future investment priorities. The organisation’s Reform and Investment
Framework (2010), acknowledges its use of CBA as a key tool in the prioritisation
stage.
The position of Infrastructure Australia is that it will use national and state and
territory guidelines on economic appraisal as the primary framework within which to
assess the economic costs and benefits of all proposed transport initiatives. The
main area of departure (from the existing guidelines) is the specific reference that
‘where appropriate it may take into consideration what have been referred to as
“wider economic benefits” of initiatives such as agglomeration effects’.
The framework notes that wider economic benefits are not typically captured in
traditional cost-benefit analysis. It accepts the most significant source of wider
economic benefits is agglomeration economies and that wider economic benefits
also encompass imperfect competition in the labour market as well as changes in
welfare resulting from the deepening of the labour market and improved job
matching when directly attributable to a transport initiative. In other words,
Infrastructure Australia accepts the four-fold categories of wider economic benefits
used in the UK, outlined above.
Infrastructure Australia treats WEBs separately from traditional CBA and requires
that state jurisdictions consult with Infrastructure Australia before proceeding on any
analysis of WEBs for any particular project.
The general philosophy at Infrastructure Australia is that wider economic benefits –
when applied in a robust and convincing manner – can clearly add weight to the
case for the funding of a project.
It should be noted that Infrastructure Australia has been largely critical of the use of
WEBs within submissions by various jurisdictions to date, finding that the analyses
20
have not been up to standard in many cases and have failed to convince the
organisation’s analysts.
Application of WEBs in investment appraisal in Victoria
There is no clear consensus within and across the Victorian transport portfolio or
more broadly across government about the nature and type of projects to which
measurement of WEBs are relevant or how to estimate these benefits.
Victoria has quantified the wider economic benefits of some of its submissions to
Infrastructure Australia. Westlink and Melbourne Metro are among relevant projects
which assist in tracing the gradual development in sophistication of the
methodological approach in Victoria in wider economic benefits assessment.
East-West Link Needs Assessment
Investing in Transport - East-West Link Needs Assessment (Eddington 2008)
covered traditional cost-benefit analysis but also included assessment of the flow-on
effects of transport infrastructure development on the Melbourne and Victorian
economies (such as changes in GDP, GSP and employment). It also includes
calculation of wider economic benefits.
The net present value of traditional measured benefits (Table 1) was calculated at
$11.1 billion. Travel time savings was the most significant element representing the
difference between the modelled performance of the major transport projects
involved and a ‘base case’ representing the future without the projects. Incremental
fare revenues were added to other benefit sources.
Table 1: Cost-Benefit Assessment for East West Link
Source: Eddington (2008)
Costs and Benefits
$ billion
Present value of costs
•
Capital
13.0
•
Operating
2.0
15.0
Total Costs
Present value of benefits
•
Travel time savings
9.4
•
Vehicle operating cost savings
0.5
•
Reduced crash costs
0.3
•
Externalities
0.7
•
Public transport revenue
0.2
21
Costs and Benefits
•
$ billion
3.3
Wider economic benefits
Total Benefits
14.4
Benefit Cost Ratio (incorporating WEBs)
0.96
WEBs were assessed as totalling $3.3 billion, adding around 35 per cent to
conventional transport-user benefits. The most important of these benefits was
ascribed to agglomeration effects and to greater labour supply.
Ergas and Robson’s (2009) main critique for this project’s calculation of WEBs was
the direct application of summary impact multipliers from the UK. In particular, they
criticised the use of labour supply elasticities established for the UK, which would
have had questionable application in Australia.
WestLink
The Investing in Transport projects were subject to further development and
refinement following the Eddington study with some sections removed or
reprioritised to be included within other projects. Cost information was still largely
based on that prepared for the Eddington study.
The methodology for arriving at the wider economic benefits for WestLink
(Department of Transport 2009a), one of the projects that resulted from Investing in
Transport, was based on the UK framework and guidelines. Ernst and Young
provided the supporting economic analysis for the WestLink project, focused on the
provision of an alternative route to reduce pressure on the Westgate Bridge in the
medium term and the Monash-Westgate Freeway (part of the AusLink network) in
the longer term.
Standard cost-benefit analysis representing the first stage of the analysis was
undertaken and then combined with the wider economic benefits analysis and
additional benefits to produce a total economic outcome.
The analysis of wider economic benefits encompassed elements of agglomeration
economies, imperfect competition and economic welfare benefits arising from
improved labour supply. Of the four, the project quantified only the value of
agglomeration economies and economic welfare benefits arising from improved
labour supply. For imperfect competition, Ernst and Young adopted a conservative
assumption and valued it at zero.
The estimation of agglomeration economies followed directly the five step process
used within the UK methodology:
i.
Definition of spatial disaggregation regions
Ernst and Young (2009) examined transport, employment and value-added
data from a variety of sources including Australian Bureau of Statistics (gross
product by industry which was then converted to gross regional product);
Department of Transport (population data by Statistical Local Area (SLA),
22
employment by SLA and by industry); and traffic modellers (traffic model
outcomes for journey to work trips on an SLA basis across Melbourne).
ii.
Calculation of effective job density
Effective densities for each region were calculated for the base case (without
the project) and after the implementation of the project.
iii.
Calculation of Gross Regional Product per worker for the base case
Calculation of the gross regional product per worker took into consideration
the agglomeration elasticities for each industry. In this case, the agglomeration
elasticities for UK industries were used. The difference in effective density of
employment from one period to the next is also part of the calculation.
iv.
Calculation of the Gross Regional Product (GRP) per worker (after introduction
of the Project)
GRP per worker was calculated using a similar formula to step 3, but
considering GRP per worker after the introduction of the project and prior to
the introduction of the project. This also takes into consideration the change in
effective density before and after the project implementation.
v.
Calculation of the increase in total Gross Regional Product
This is the difference between GRP before and after the product multiplied by
the employment in each sector, region and year after the project’s completion.
The breakdown of WEBs and their corresponding share of total benefits are shown
in Table 2.
Table 2: WEBs for WestLink
Source: Department of Transport (2009a)
Wider Economic Benefit
Value ($m, 2009)
Share of Total benefits (%)
Agglomeration Economics (WB1)
529.5
9
Labour supply (WB4, GP1)
51.3
1
Productivity impacts (WB4, GP3)
105.9
2
Total
686.7
11
The sensitivity analysis for the WestLink project included variations on
overestimation of project benefits by 10 per cent and 30 per cent and
underestimation of project benefits by 10 per cent. In all scenarios, standard costbenefit analysis including wider economic benefit BCRs were still above 1 as shown
in Table 3.
Table 3: Selected Sensitivity Tests, WestLink
23
Source: Department of Transport (2009a)
Variation on Sensitivity Tests
Standard BCR
Standard BCR with
WEBs
Underestimation of Project benefits – -10%
1.46
1.67
Overestimation of Project benefits – 10%
1.20
1.37
Overestimation of Project benefits – 30%
0.93
1.06
Melbourne Metro 1
The Melbourne Metro project is the critical enabler of a metro-style rail system in
Melbourne and involves a rail tunnel from South Kensington to South Yarra. The
project will dramatically increase transport capacity to central Melbourne, improve
accessibility to Melbourne’s knowledge economy and facilitate inner urban renewal
in the Arden-Macaulay precinct, and assist with the expansion of central city
industries to St Kilda road and the inner north and west.
An estimation of the agglomeration benefits of Melbourne Metro 1 (when the project
was conceived in a number of stages, with MM1 being the cross-city stage) was
conducted by SGS Economics and Planning (2010), based on the UK guidelines.
The degree of business agglomeration is measured through Effective Job Density
(EJD) as defined above. This allows for the measure to ‘incorporate both proximity
and the scale of the economic activity and be calculated for very small areas’
(Graham, 2006).
SGS suggests that this enables a more ‘real life’ representation of the proximity (in
terms of travel time) component of agglomeration that other more basic measures
overlook. This method reflects real and perceived costs associated with travel in
various parts of the city. As a general rule commuters will favour the mode of
transport which minimises their travel costs including value of time and any direct
monetary cost.
Compared to the Westlink assessment, which directly used UK parameters in the
estimation of WEBs the Melbourne Metro 1 approach used a Melbourne based
database; clearly a methodological improvement. SGS has aggregated travel zone
effective job density (EJD) to an SLA level using a weighted average based on
population for origin and employment for destination. As an illustration, Figure 2
shows the EJD of Melbourne.
SGS calculated an average elasticity of eight per cent which is in the middle range
of the productivity elasticities with respect to EJD from overseas studies (five to 13
per cent) and is similar to the seven per cent estimated by Trubka (discussed in
detail below). The findings show that the strength and degree of the relationship
varies across industries, with a higher degree of relationship across knowledge
service sectors.
With the application of the SGS estimated labour productivity elasticities on the
MM1-induced changes in EJD, the impact on Melbourne Gross Value Added (GVA)
is indicated to be $128 million in 2031 and $384 million in 2046, for a total value of
24
the agglomeration-based GVA boost of $1.6 billion. This represents some 21 per
cent of the total benefits of the project. The analysis shows that agglomeration
impacts will be different across industries and locations, with knowledge based
industries and western areas garnering most of the benefits. A decrease in WEBs
by 50 per cent would still yield a NPV of $1.8 billion, equivalent to a BCR of 1.4.
The business case also presents a BCA for the full scheme, with WEBs valued at
$2.6 billion, 18 per cent of total benefits.
Figure 2 – Effective Job Density of Melbourne
Source: SGS Economics and Planning
25
Methodologies and Measurement of Agglomeration
Benefits
The measurement of agglomeration economies is an evolving issue. While we are
seeing an increasing body of evidence which builds the case for formal recognition
in the investment appraisal process, there remain methodological and measurement
issues that need to be looked at to ensure proper estimation of agglomeration
impacts.
Criticisms of agglomeration assessments
While there has been an increasing body of literature devoted to wider economic
benefits, opinion is still divided on their significance and the role they should play in
the appraisal process. Much of the debate focuses on the estimation process and
the nature and type of projects for which the measurement of WEBs, including
agglomeration economies, is relevant.
Some leading authorities query the claims made for agglomeration economies.
Abelson (2009) has argued against inclusion of supposed agglomeration benefits as
a general component of benefits in transport studies. He considers it doubtful as to
whether such benefits exist over and above the benefits counted in a (properly
conducted) standard economic evaluation. He argues that new transport
infrastructure can often result in the dispersion of activity rather than its greater
concentration. However, Abelson concedes that there will be specific cases where
transport can be shown to increase urban densities and where it can be shown that
there are benefits in addition to those counted in the standard evaluation model.
Ergas and Robson (2009) were critical of the specific evaluation of WEBs and
agglomeration economies arising from Victoria’s East-West Rail Link Project. Their
concern was not that agglomeration economies associated with transport
investment are negligible, rather that they centred on the simple application of UK
multipliers and elasticities. They also argued strongly for the need to undertake
detailed location-specific studies.
UK expert Roger Vickerman (2011) has suggested that CBA remains the most
effective method of decision-making, particularly for smaller investment projects, in
potentially capturing all benefits as user benefits. However, he has conceded that
significant WEBs may be identified for what he termed ‘mega-scale projects’ that
cannot be captured by conventional CBA methodology.
Vickerman concluded that the claims made for agglomeration economies are still
unresolved and that there should be care taken not to overstate perceived WEBs.
26
Divergence in agglomeration elasticity estimates
The divergence in elasticity estimates, and the reduction in these estimates over
time as methodologies have become more refined, have also been discussed in the
literature. Table 4 shows the agglomeration elasticities of some selected studies.
The wide range of agglomeration productivity elasticity estimates is greatly
influenced by the estimation techniques employed, and, presumably, by the
economic make-up of the location being studied. Estimates in Australia and New
Zealand, are, however, relatively constant.
Table 4 – Elasticities in other studies
Source: SGS Economics and Planning (2010), Graham et al (2009)
Author
Elasticity (%)
Location
SGS October 2010
8
Australia
Maré and Graham (2009)
7
New Zealand
Trubka (2009)
7
Australia
Graham, Gibbons and Martin
(2009)
4
United Kingdom
Graham (2007b)
13
United Kingdom
Ciccone (2000)
6
USA
Ciccone and Hall (1996)
5
European Union
Combes et al (2010) note that while significant progress has been made towards the
estimation of agglomeration economies over the last decade, the existence of a
consensus is not a guarantee of reliability. They stressed the importance of
understanding how different types of workers and firms benefit from cities.
Based on the further work of Graham et al (2009), the UK guidance now quotes an
overall agglomeration elasticity of four per cent averaged across the four broadbased sectors of the economy – with a doubling of the city density increasing
productivity by four per cent – and for specific sectors encompasses elasticities of
two per cent for manufacturing and consumer services, three per cent for
construction and eight per cent for business services.
Trubka (2009) published the first estimates for Australia of the relationship between
productivity and density of economic activity. He found Melbourne to be the best
example of employment density predicting productivity, explaining 80 per cent of the
variance in the productivity index. Trubka derived a productivity elasticity for
Melbourne of 7.4 per cent meaning that doubling the density in the centre of
Melbourne would increase the productivity of firms in the city by 7.4 per cent.
27
While results for Melbourne were significant, they were inconsistent across capital
cities and Trubka suggests the need for further research to address:
the difference in SLA size across capital cities, possibly diluting density
measurements – small geographic units cannot control for cross-boundary
agglomeration spillovers and reduce the ability of the productivity index to
control for employment composition effects
aggregates of like industries to have their productivity index measured
separately
the exclusion of construction-oriented industries which Trubka considers pay
artificially high wages.
Trubka’s concern about how certain industries accrue more agglomeration benefits
has been reiterated by Rawnsley and Szafraneic (2010), who note that the services
sectors tend to gain more from agglomeration benefits compared with the
manufacturing and wholesale trade sectors.
These issues and further developments in the methodology need to be considered
in any future work on specific agglomeration elasticities for Victoria or Melbourne.
Methodological issues in measurement
Avoiding ‘Double counting’
In calculating agglomeration benefits or economies, some economists have drawn
attention to the need to avoid ‘double-counting’. As Vickerman (2007) notes,
traditional transport appraisal assumes that a well-specified cost-benefit analysis will
capture the entire economic impact of a transport infrastructure investment including
the economy-wide productivity gains.
Criticism of double-counting was essentially aimed at earlier crude studies which
were not well designed and articulated, and relied heavily on the use of uplift rates
applied to travel time savings in order to estimate wider economic benefits.
Care in later studies has lessened the allegations of double-counting to exaggerate
the benefits of transport projects.
In any case there is a clear conceptual difference between savings in travel time,
vehicle operating costs, fares, and deaths and injuries avoided – the focus of
conventional CBA – and the broader economy-wide productivity gains stemming
from a transport project. The former are gains accrued by individuals and transport
operators, while the latter accrue to the economy as a whole.
Controlling for bias
There is also a need to ensure that the productivity increases can be attributed to
agglomeration benefits and are not influenced by other factors such as sorting.
Subsequent studies have implemented methodological improvements in this area
which improves the reliability of the agglomeration estimates.
28
Maré and Graham (2010) specifically examined alternative ways of controlling for
firm heterogeneity and ‘sorting’ given they may bias agglomeration elasticities
arising from higher productivity firms choosing denser locations (rather than
becoming more productive by locating in denser areas). This is a significant issue to
be assessed in calculating wider economic benefits and agglomeration economies
anticipated in large investment projects such as Melbourne Metro.
Suitable data set
The issue of a suitable data set for estimation of wider economy benefits in the
Australian context is another complexity. UK estimates of agglomeration economies
(for example by Graham) are of higher quality than those published for Australia as
UK researchers have access to better data. Lifting the quality of Australian studies
to UK standards requires accurate and robust data of the locational and profitability
behaviour of firms.
UK researchers study the behaviour of individual firms, for example, examining how
firms become more profitable by co-locating with their competitors, customers and
suppliers. Under UK legislation, each registered company is required to provide
accounting and other information about their information to Companies House, an
executive agency of the Department of Trade and Industry (Graham, 2007).
These are made available in a commercial software package called Financial
Analysis Made Easy (FAME). The FAME data has extensive financial information for
each firm and are available over a number of years. This allows analysts to track the
relation between location and profitability of firms over time.
In the absence of access to data on the profitability and location of individual firms,
Australian researchers have had to be less direct, adjusting their methodology to fit
available data, and in one case needing to construct synthetic data. They have not
so far studied the behaviour of firms directly. SGS used regressions on synthetic
data at the SLA level to yield comparable results at the aggregate level with Trubka
for Australia, but a little higher than for the European Union, the USA and New
Zealand.
The critical importance of the data issue was demonstrated by Maré and Graham
(2010). Their ability to present a comprehensive micro economic analysis of the
impact of agglomeration on firm multi-factor productivity was attributed to the
availability of a rich longitudinal unit record data set with close to economy wide
coverage of New Zealand.
At the core of the NZ data set is the Longitudinal Business Frame which provides
longitudinal information on all businesses at enterprise and plant level. In
conjunction with a range of information from an administrative series, and at a tax
administration level, the strength of agglomeration effects can be assessed for a
comprehensive range of New Zealand industries.
29
Enhancing our knowledge
Further Study – Melbourne Metro – M2MPJ
As this paper was prepared, SKM was commissioned by the Victorian Government
to appraise the impact of Melbourne Metro on the Move to More Productive Jobs
(M2MPJ) component of WEBs.
SKM is providing the method and rationale for the assessment, SGS the data and
demographic context while Ernst and Young will cover engagement and funding.
Significant tasks in the proposal include:
development of the theoretical framework
the data collection process
assessment of other potential factors and constraints adversely impacting on
future employment location in Melbourne
the replication of analysis done for the CrossRail project relating to crowding and
demand growth on transport
development of a crowding constraint model to estimate the extent to which
demand would be ‘crowded out’ in the future without Melbourne Metro
the quantification and valuation of additional CBD jobs
in the context of the M2MPJ outcome, re-estimation of overall agglomeration
benefits given the impact of employment redistribution on effective density.
The results of this study were not available at the time this paper was finalised, but it
should provide another step forward in our understanding of the measurability of
WEBs in a Melbourne context.
The consultants note that the UK Department for Transport has downgraded its
initial support for M2MPJ in transport appraisal. The UK Department for Transport
now will only include this benefit if it is calculated from an approved Land use
transport interaction model – and it has not yet approved any such model.
Accessing better Victorian data sets
The major limitation of the current published data sets used to assess the
productivity gains of density is that aggregation hides key behaviour patterns of
individual firms and workers. This follows from the requirement of data custodians to
respect the privacy of individuals and the commercial confidentiality of firms.
A marked improvement in statistical knowledge can be achieved by the data
custodians themselves running equations on unit records of firms and households.
The Department of Transport may be able to track the behaviour of 9,000 firms in
Australia over the six years 2004-05 to 2009-10 through the use of the ABS
30
Business Longitudinal Database. Public access to this database (Australian Bureau
of Statistics 2009) provides access to only a fraction of this data; however the full
database includes the business address which may be geocoded to enable detailed
spatial analysis. The ABS business database has direct access to Australian
Taxation Office (ATO) quarterly Business Activity Statement returns for profitability
and also links with Customs and Excise information. The department could
commission ABS to undertake research to our specifications or do it in house using
their data with the necessary confidentiality safeguards.
The Victorian WorkCover Authority is another potential source of information to
enable agglomeration estimates for Melbourne and Victoria. The Victorian
Government has commissioned the ABS to provide inter-censal estimates of
employment in Victoria between 2006 and 2011 and thereafter by Local
Government Area by industry sub-division of employer. The ABS will use
administrative data from the returns by employers to the Victorian WorkCover
Authority as they insure against workers compensation claims. This new database
of timely information about the location and number of jobs in Victoria and the
industry of the employer will provide a foundation for further research into the
economics of agglomeration.
COAG Reform Council – Continuous Improvement Project
At its December 2011 meeting, the COAG Reform Council (CRC) endorsed the
funding of a consultancy study of the current state of empirical research on
productivity, urban form and agglomeration benefits.
Commencing in early 2012, the study will examine the costs and benefits in
productivity terms of different urban forms and settlement patterns and, in particular
information on data gaps that are hindering inquiry into productivity in Australian
cities. The report will look at the current state of empirical research into
agglomeration economies. The CRC advises that the report should be finalised by
the end of May 2012, with the opportunity for states to comment on a draft.
Ex Post evaluation
Economic benefits of agglomeration claimed in budget or financing bids can be
verified at the completion of the project. Systematic ex post evaluation of every
project can improve our understanding of both economics and its measurement.
A study of all UK major road improvements between 1998 and 2003 (Gibbons et al.,
2010) found that the schemes evaluated were too small to generate sufficiently
large economic effects in addition to traditional travel time savings.
However, it was acknowledged that large-scale strategic transport improvements
(including rail schemes) can be expected to generate very large changes in
accessibility and agglomeration with wider geographical scope, so there remains a
case for incorporating agglomeration-related productivity effects into the ex-ante
appraisal of these schemes.
31
On-going routine ex post evaluation of transport projects was recommended as the
best way to estimate the causal linkages between transport and firm outcomes.
Conclusions
The issue of wider economic benefits and agglomeration economies has been the
subject of significant development, discussion and debate within the Department of
Transport and across government. Much has been learned from developments in
the UK framework and methodological approach for incorporating WEBs into the
investment appraisal process.
The purpose of this paper has been to discuss these developments and make
proposals about the relevance of wider economic benefits and their use in the
preparation of business cases.
Methodological improvements
Proper assessment and measurement of wider economic benefits of major transport
projects may well lead to better public investment decisions in the context of overall
government policy and strategy.
Significant progress is being made in the assessment and incorporation of
agglomeration benefits. This is particularly so in Victoria reflected in the business
cases for major projects considered by Infrastructure Australia following the
Investing in Transport Report including Regional Rail Link, Westlink and Melbourne
Metro.
The recent work of SGS Economics & Planning for the proposed Melbourne Metro
project demonstrated the addition of about $2.6 billion (in present value terms) of
agglomeration benefits, representing some 17.7 per cent of total benefits of $14.65
billion (in present value terms). This demonstrates how the measurement of wider
economic benefits can be an important component of business case prepared for
certain major infrastructure projects.
However, there may be a need to further strengthen the methodology for estimating
agglomeration economy parameter values specific to Melbourne. Identification and
application of a more relevant and robust data set and methodology, as was the
case in the UK, would further strengthen the case for the inclusion of wider
economic benefits as part of the cost-benefit analysis process.
Victorian Guidelines
The most appropriate approach for incorporating wider economic benefits in the
investment appraisal process lies in incremental expansion of the Department’s
CBA guidelines in line with the Infrastructure Australia assessment process. This
approach is recommended for the following reasons:
32
although knowledge and methods in estimation of agglomeration benefits and
wider economic benefits are improving, there is still considerable scope for
development and a range of only partially-answered questions
this approach follows the methodology on wider economic benefits assessment
adopted by UK and New Zealand
not all projects will accrue agglomeration or wider economic benefits, limiting the
application.
As Vickerman, Abelson and others have emphasised, the need to measure and
value agglomeration benefits will potentially only apply to the larger complex megascale projects.
National Guidelines
Any changes to Victorian guidelines could form the basis of informing the review of
the National Guidelines for Integrated Passenger Transport and Land-use Planning.
It may also encourage a consistent approach nationally given the need for
agreement among jurisdictions on the issue of the relevance of, and the
methodological approach to the measurement of wider economic benefits.
However, there must be acknowledgement that wider economic benefits are place
specific and, as such, elasticities that are relevant for the UK or New Zealand could
not entirely be applicable to Australia in general and Melbourne in particular.
Trubka’s paper, in particular, highlights this concern, and states that there may not
even be a relevant elasticity / parameter estimate for the whole of Australia owing to
the difference in impacts of agglomeration economies to each city.
Next steps
The transport portfolio will continue to advance its understanding on agglomeration
economies and measuring agglomeration benefits in transport appraisal.
The methodology and approach will be further improved through detailed
investigation of the potential to generate higher quality data (such as those from
the Australian Bureau of Statistics and the Australian Taxation Office) and
information sources to underpin robust quantification of wider economic benefits
and agglomeration economies in business case preparation and investment
appraisal.
To further test the validity of methods for assessing agglomeration economies
the portfolio should undertake ex-post evaluations of those transport projects for
which wider economic benefits were claimed.
33
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Appendix A – Crossrail Impact on Welfare and GDP
Source: Buchanan (2007)
40
Crossrail’s Wider Economic Benefits
Source: CrossRail (2011)
Component
(£bn; PV 1Q 2002 prices)
TfL (London
values)
DfT (UK wide
values)
Wider Economic Benefits
-
GDP (includes Welfare below)
42
6 to 15
-
Welfare (including Increased Tax)
7 to 18
6 to 9
Central Estimate
3.97
3.09
Sensitivity Estimate (including M2MPJ)
5.87
3.53
Central Estimate
5.23
4.07
Sensitivity Estimate (including M2MPJ)
7.74
4.66
BCR (including Welfare WEBs)
BCR (including Welfare WEBs), without ‘sunk’ costs
41