WIDER ECONOMIC BENEFITS OF TRANSPORT

SCHEMES IN REMOTE RURAL AREAS

Paper presented at the Conference on Wider Economic Impacts (WEI) of Transport

Infrastructure Investments.

Molde University College, Molde, Norway

10th September 2013

James J Laird

J.J.Laird@its.leeds.ac.uk

Peter Mackie

P.J.Mackie@its.leeds.ac.uk

Dan Johnson

D.H.Johnson@its.leeds.ac.uk

Institute for Transport Studies

University of Leeds

Leeds LS2 9JT

Great Britain

+44 (0)113 343 5325

ABSTRACT

The wider benefits of transport interventions on the economy in terms of changes in

output and employment are of perennial interest to policymakers. Their inclusion

however in transport appraisal methods and cost benefit analysis methods in

particular has only received attention in the last 10 to 15 years. Primarily this is

because they are only relevant in a cost benefit analysis if the secondary markets

are distorted – and market distortions have only recently shown to be relevant in

developed economies (e.g. agglomeration economies). Despite a strong interest

over the last 10 to 15 years the methods for inclusion of wider economic benefits in a

cost benefit analysis remain in their infancy, and their extension to remote rural

areas has received very little discussion. The aim of this paper is to review wider

economic benefits, their evidence and the methods used to incorporate them into

cost benefit analysis in general and then specifically focus on the extension of the

methods to remote rural areas. The distinguishing aspect of such areas is a lack of

alternatives and choices – travel choices are limited and choices of employment and

choices of supplier are also limited. The empirical relevance of wider economic

benefits in remote rural areas is illustrated using case studies from Scotland. We

find as with urban environments focusing the cost benefit analysis on only the

primary transport market can significantly underestimate the welfare benefits of

transport schemes. Again as with more urban environments, the degree of

underestimation varies on a case by case basis. It is highest for schemes where the

impacts on business and employment are large and where all of the users of the

route are from a remote rural area. It is lowest for routes that pass through remote

rural areas, but whose main market is inter-urban traffic. Whilst significant, the

degree of underestimation found is unlikely to be sufficient to turn a ‘poor’ scheme

into a ‘good’ scheme, but is sufficient to affect project prioritisation within a national

or regional investment programme.

1 INTRODUCTION

Investment that improves transport quality and lowers its use costs almost always

has impacts outside of the primary transport market, often stimulating economic

growth. Demands for goods, services, land, capital and labour alter and prices

accordingly adjust as the transport benefits feed into the wider economy.

Occasionally a transport investment can open up an area for

development/regeneration and this might be one of the key objectives of the

investment. Typically these economic impacts also have a spatial dimension.

Additionally they almost always hold a strong interest for policymakers and have

been found to influence transport investment decision making at some level (Nilsson,

1991; Odeck, 1996; Nellthorp and Mackie, 2000; Preston and Wall, 2008; Eliasson

and Lundberg, 2012). How they are measured and treated within the appraisal

process is clearly very relevant to transport policy.

Interestingly transport cost benefit analysis (CBA), the methodological focus of this

paper, by assuming conditions of partial equilibrium does not consider such wider

economic impacts. This is because if markets are not distorted then measuring

benefits in the primary transport market gives a full measure of the welfare impacts

of a transport investment. It is only if markets are distorted is there a need to

consider how wider economic impacts should be treated in a CBA (Dodgson, 1973,

Jara-Diaz, 1986; Mohring, 1993; Boardman et al., 2011 p121. Rouwendal, 2012).

However, the highly influential report by SACTRA (1999) identified that prices can

depart from marginal social costs in mature economies – due to the presence of

agglomeration externalities, spatial monopolies and product differentiation. Other

market distortions or imperfections that lead to prices departing from marginal social

costs identified in the literature include labour taxes, immobility in the housing or

labour markets or distorting labour market regulations leading to involuntary

unemployment and search costs in the labour market. To date the focus of the

research effort on the incorporation of wider economic benefits into a CBA has been

on urban or populated areas, however, arguably some of these market distortions

also occur in remote rural economies (Kilkenny, 2010) – though the authors are not

aware of any effort to estimate the contribution of remote rural wider economic

impacts to a transport CBA. Land markets can also be distorted though the

evidence on the degree of distortion and the impact on a transport CBA is limited to

non-existent. We do not therefore consider further distortions in the land market in

this paper.

The primary contribution of this paper is to identify the importance of wider economic

benefits for transport schemes in remote rural areas and the need for further

research in this area. Its secondary contribution is to review the theoretical and

empirical evidence base on the presence of market imperfections that lead to the

need to consider wider economic benefits for transport appraisals in general, and

how they should be incorporated into the said appraisal. To do so we also briefly

review the economic channels by which transport affects an economy and the

methods used to model these wider economic impacts. This is because ultimately

the successful incorporation of wider economic benefits into a CBA rests on the

economic modelling that precedes the CBA – rubbish in gives rubbish out.

The paper is organised as follows. Following this introductory section the second

section presents how transport impacts on the economy and briefly reviews different

methods for modelling it. Section 3 identifies five distortions in the economy that

have been shown to influence a transport CBA: agglomeration economies, imperfect

goods market, labour taxes, involuntary unemployment and thin labour

markets/search costs. Five remote rural case studies are introduced in Section 4. In

section 5 the evidence for each of the aforementioned market distortions is

considered and if relevant the additionality that that distortion brings to the CBA is

estimated for each of the case studies. The sixth and final section presents some

conclusions.

2 TRANSPORT’S IMPACT ON THE ECONOMY

Fundamentally, transport improvements enhance economic competitiveness by

reducing the cost of doing business at particular locations. This occurs due to the

various linking mechanisms or channels between improvements in accessibility, due

to better transport quality, and changes in the rest of the economy outside the

transport sector. In discussing the channels we split the discussion into output

effects and reorganisation effects and then discuss the spatial location aspects of

both together. We are not here discussing how these competitiveness effects are

dealt with in cost benefit analysis; that follows in section 3. We then briefly review

the modelling of the economic impacts of transport infrastructure investment. This is

a complex issue that crosses several disciplines and is at the cutting edge of

regional science. Unsurprisingly there is therefore a large but disparate body of

literature covering the various methodological approaches and applications.

2.1 The channels

Output Effects

Of primary interest to policymakers is that lower transport costs can stimulate

increases in output. Consider first an agricultural economy. Improved feeder roads

both lower the cost of bringing fertiliser to the villages and lower the distribution cost

of getting the product to market; there is both a supply side and a demand side effect

on output. This can be a very marked effect in developing countries because where

transport infrastructure is poor, transport costs can be a high proportion of delivered

prices. In the case of city economies, the effect is likely to be less marked but should

nevertheless be there. When the transport system improves, labour is enabled to

access employment at lower generalised cost of travel so assuming wages held

constant, wages net of transport costs rise and more people are willing to enter the

labour market. Similarly, improved transport means that the cost incurred by the

customer in accessing goods and services falls. Output is enabled to rise.

Agglomeration externalities, the productivity benefit of being located close to others,

also enable output to rise – if the accessibility

An important caveat to the above is that in the favoured locations, land is assumed

to be available. In the simplest versions of the model, the land market is assumed to

be competitive so that the cost changes in the transport sector, possibly amplified by

economies of scale, are fully passed through into the product market. In the real

world this may not be the case; accessibility improvements may pass partially into

increased land rents which then mute the final output effects. Different results occur

depending on the relative competitiveness of the urban land, labour and product

markets.

Reorganisation Effects

In a world of all round perfect competition with constant returns to scale, there is no

reason why transport improvements should lead to any commercial reorganisation.

The proposition is that there are some sectors which are subject to economies of

scale but which cannot be fully exploited because of transport costs. This leads to a

form of imperfect competition or possibly spatial monopoly in which market areas are

served from different locations. With improvements reducing transport costs, the

balance between production costs and distribution costs is shifted in favour of fewer

larger lower cost production locations. Mohring and Williamson (1969) use the

example of steel production but the argument applies also to physical distribution

and logistics, cement, oil distribution, beer and other transport intensive products.

An interesting question is whether a similar effect might occur in office employment

or other sectors characteristic of city centre locations. If transport quality was really

very poor, the limiting factor might be the ability to assemble the necessary volume

of qualified labour in one place; firms might operate with branch offices partly to be

attractive in the labour market and partly to serve the customers. A much improved

transport system might then be expected to encourage centralisation so as to exploit

economies of scale in office functions. For high value added activities, the likely

location would be in the city centre so as to maximise accessibility to workers,

visitors and customers. Notoriously however, in car dominated societies the natural

advantage of the city centre can break down in favour of satellite locations,

classically at points around the city ring road(s).

The important point about reorganisation effects is that in the pure case, economic

output remains fixed but output is produced at lower cost. At the aggregate level

there will be economic benefits but within that aggregate there will be gainers and

losers from the economic adjustments.

Location Effects

There is a spatial dimension to both the reorganisation and output effects. Looking at

it from the perspective of a region, there are three categories to consider :

Relocation of activity within the region. This is likely to be the largest category.

Changes in relative accessibility shifts the location of production within the

region.

Relocation of activity between regions. Obviously this only applies for

activities where there is competition between regions.

Relocation of activity between countries.

These categories are useful for considering the different perspectives of regional and

national government. For the first and third categories the perspective is essentially

the same: the first is a redistribution within the area while the third is an

unambiguous effect on national output. However the second will be viewed

differently by the two tiers of government and is one reason why the regional tier can

be more enthusiastic than the national tier about infrastructure investment.

Also it is necessary to consider the two-way road effect. A rural highway improves

the accessibility from the region to its market, but also improves accessibility from

the economic core of the country to the region. The remote region is opened up to

competitive forces and some substitution of activities to the core may occur (e.g.

business services). For regeneration to occur or economic growth to occur in the

remote region, then without strong supporting planning policies, change may not

take place at the intended location. The way in which transport improvements are

linked up to planning and development policies is often important.

2.2 Modelling methods

The modelling of how transport schemes affect the wider economy is fundamental to

the successful appraisal of wider economy impacts and we therefore briefly review

these methods. In part we do this as the different methods offer different strengths

regarding the incorporation of wider economic impacts into an appraisal, but also

because the different methods can give rise to very different results.

Micro surveys of firms: These surveys elicit location factors or impacts of specific

factors on firms’ behaviour. Such approaches are useful when there are limited

resources with which to conduct research. They can however lead to biased

responses, and do not capture either agglomeration impacts or re-distributive

impacts well. They are often used in conjunction with output and employment

multipliers derived from input-output (I-O) tables. They give estimates of local

changes in output and employment, but typically by using I-O multipliers assume

productivity to be constant.

Regional production function models. These macro based models use estimated

relationships between classical factors of production (labour, capital and land) to

predict changes in economic output. Enhancements to the models include indicators

of infrastructure and accessibility as explanatory variables in the production function

of a region (Wegener, 2011). These models are hard to estimate, requiring detailed

time series and cross-sectionally disaggregated data. Challenges that also need to

be overcome in their estimation include the familiar causality issue in relation to the

infrastructure and the variability of production elasticities.

Wage equation models: These models estimate an economic relationship between

wages and accessibility (either multi-modal or by a particular mode) via proximity to

economic mass. Some of these models distinguish between place based and

people based effects (SERC, 2009). Place based effects reflect a once off increase

in the productivity of the place due to the increased accessibility, whilst people based

effects relate to the increased productivity of the location due to changes in the

workforce composition (due to e.g. migration). In application the models can be

applied in isolation or in conjunction with a model that re-distributes employment.

They give estimates of changes in productivity and output, but ancillary models are

needed to predict changes in employment.

Partial equilibrium model. Effectively this model takes the GDP impact to be equal

to business and freight user benefits from the transport model. For this to be the

case the perfect competition to exist everywhere outside of the transport market –

i.e. the supply curves are effectively assumed to be perfectly elastic. The method

only gives an estimate of changes in output and says nothing about changes in

employment. Additionally it does not give any information about distributional

changes.

Land Use Transport Interaction (LUTI) models. Land use transport interaction

models are linked transport and land use models. Households and firms interact with

each other in various goods and services, labour and property markets. These

models explicitly model the re-distributional effects of transport investment.

Additionally some of them, through the use of multiregional input-output tables, also

model structural change in the regional economies in terms of substitution between

industrial sectors. Transport influences the decisions of households and firms

through accessibility changes on key land using activities, transport systems and

through the linkage to other markets. Land use is affected by other factors as well as

transport, e.g. demographics and development. There are a handful of examples of

LUTI models within a random utility framework being used to evaluate the benefits of

simultaneous changes in land use (e.g. intensification of land uses near rail stations)

and transport policy (see e.g. Geurs et al., 2010). Typically LUTI models are only

used to model re-distribution of economic activity, though they can be enhanced to

model net economic growth and agglomeration effects. They give estimates of both

changes in employment, but through the use of I-O tables assume productivity is

constant.

Spatial Computable General Equilibrium (SCGE) Models. These models are

input-output based models that also include economies of scale and imperfect

competition. They are comparative static equilibrium models of trade and location

between regions. A key strength of the models are that they are based in

microeconomic theory and link households’ utility maximising behaviour and firms’

production functions to model wider impacts of transport investments, through

comparing outcomes of different equilibrium states (see Brocker and Mercenier,

2011 for overview). These models can give estimates of economic gain as well as

additionality in a CBA. They therefore seem to offer the most functionality from the

perspective of the transport analyst. Their weakness is their complexity which can

make it necessary to restrict the analysis to comparative statics and to impose

certain closures (e.g. to limit migration) in order for the model to find an equilibrium.

There are only a handful of applications of this approach worldwide, such as the

RAEM model (Tavasszy et al, 2011), the CGEurope Model (Brocker and Mercenier,

2011) and the Australian TRESIS-SGEM (Hensher et al, 2012).

Consistency between methods: Unfortunately the different methods appear to give

very different results and further research is needed to identify the reasons for this.

For example the wage equation applications to a high speed rail scheme in the UK

give rise to estimates of economic impact 3 times those of partial equilibrium

methods (Laird and Mackie, 2010); whilst an SCGE application and a regional

production function application to the TEN-T network gave rise to differences of up to

a factor of 10 with the production function method tending to give the higher

estimates of regional economic growth (Bröcker et al., 2004 pp168-175).

3 ADDITIONALITY OF WIDER ECONOMIC IMPACTS

As mentioned in the introduction wider economic impacts only have relevance in a

transport CBA if markets are distorted – that is price does not equal marginal social

costs in the economy. We now present five such distortions and the evidence that

these distortions are material to the robustness of transport CBA. These distortions

are: agglomeration economies, imperfect goods market, labour taxes, involuntary

unemployment and thin labour markets/search costs.

3.1 Agglomeration externalities

Agglomeration economies have been the main focus of attention in the literature on

the wider economic impact of transport interventions (van Exel et al., 2002; Laird,

Nellthorp and Mackie, 2005; DfT, 2005a; Eddington, 2006; Venables, 2007, Graham,

2007). They arise as a consequence of the positive consumption externalities that

occur when economic agents in transport using sectors of the economy are brought

closer together by a transport improvement. By bringing these agents closer

together labour productivity is raised above and beyond what would be expected

from the transport efficiency saving alone. The numerous micro-economic linkages

between economic agents, brought closer together, generate the externalities which,

collectively and at a localised level, give rise to aggregate increasing returns or

agglomeration economies. Venables (2007) in is highly influential paper shows that

the productivity and output impact caused by the agglomeration externality is

additional to transport user benefits.

There exists a substantial literature on the variation in worker productivity with

agglomeration size (see for example Rosenthal and Strange, 2004; Melo et al.,

2013). The agglomeration effects of transport schemes can be quite significant.

Bröcker et al. (2004) using a SCGE model CGEurope found that completion of all of

the TEN-T priority infrastructure projects may generate between 20 and 30% more

economic benefit than would be measured in a normal transport cost-benefit

analysis. The additionality measured in CGEurope arises through productivity

effects and imperfect competition in the goods and services market (as discussed

below), though it is not possible to disaggregate the results between the two effects.

Elhorst and Oosterhaven (2008) find increases in labour productivity are between

12% and 21% of transport user benefits depending on the maglev2 train variant

appraised.

Using a partial equilibrium approach DfT (2005a p8) found that Crossrail, a large rail

capacity enhancement in Central London, generates an additional 24% of economic

benefits due to agglomeration alone on top of transport user benefits. As Crossrail

re-distributes employment to the most productive part of the UK the value of its

indirect effects are the largest one would expect to find in the UK. Typically

agglomeration effects will have a much lower added value than Crossrail. For

example the Eddington Study found the sum of agglomeration and imperfect

competition effects average 22% of user benefits for urban schemes, 7.4% for

surface access projects to international gateways and 9.1% for inter-urban corridors

(Eddington, 2006 Figure 1.5 p.129).

3.2 Imperfect competition

Venables and Gasiorek (1999) first identified the relevance of imperfect competition

in the goods and services markets as being a source of distortion in the economy

relevant for transport CBAs. Imperfect competition occurs as firms may hold market

power if they engage in product differentiation or become large relative to their

market. The latter is particularly true in geographically isolated areas, where as a

consequence of geography firms act as local monopolists or oligopolists. If imperfect

competition exists then a transport induced expansion of output will give rise to an

additional welfare impact stemming from this market – as under imperfect

competition output is not at its socially optimum level.

Central to the argument of the empirical relevance of imperfect competition is

evidence on price marginal cost mark ups. There is ample evidence at an

international level that perfect competition does not prevail. For example for 10 EU

countries Badinger (2007) estimates markup factors of price above marginal costs of

approximately 1.3 for manufacturing and construction and 1.37 for services for the

late 1990s. Christopoulou and Vermeulen (2008) also find evidence that rejects the

perfect competition hypothesis with average price-cost factors of 1.37 in 8 Euro area

countries and 1.31 in the US. They also find that the price-cost margins are not

uniform with significant variation by industry and country lying behind the observed

averages.

In terms of empirical relevance to a transport CBA Venables and Gasiorek (1999)

using synthetic data identifies that imperfect competition could be very relevant to

transport cost benefit analysis. They estimate that in a two region one sector

economy with imperfect competition the additional welfare impact from an expansion

in output is between 30 and 40% of the change in consumer surplus derived by

business and freight users. This result relates to a partial equilibrium analysis, in

that changes induced in other sectors of the economy (the general equilibrium

effects) are of no net social value. Davies (1999) and Newbery (1998) who

undertook reviews of the Venables and Gasiorek research challenge this finding and

consider the 30-40% figure to be an upper limit. For the UK SACTRA (1999) took

the view that indirect effects due to imperfect competition would on average increase

benefits by about 12%1. There appear to be very few studies of imperfect

competition impacts in isolation from other impacts in the literature – other studies

1This calculation rests on the assumption that the monopolist does not price differentiate. If a

monopolist is able to discriminate between consumers they will expand output towards the sociallyoptimum level and convert some of the surplus under the demand curve to producer surplus. In thisscenario there will be a lower, and at the limit zero, additional welfare impact in the product market.With a price differentiating monopolist average price-cost margins will not be a good indicator ofmarket power. To date this issue has not been explored in the literature, and this paper does notreturn to it, but it is noted that such an argument undermines the general case for including changesin output in imperfectly competitive markets in a transport cost benefit analysis.

typically report imperfect competition impacts in combination with other types of

impact (e.g. Bröcker et al., 2004; Eddington, 2006).

3.3 Labour tax

Venables (2007) in his highly influential paper identified the relevance of labour taxes

to transport cost benefit analysis. Labour taxes create a distortion in the labour

market that mean workers do not receive a wage equal to their marginal product of

labour, and employment levels lie below those that would occur in an undistorted

labour market. Venables (2007) showed that if a transport scheme displaces

economic activity to a more productive location, where wages are higher ceteris

paribus, then transport user benefits do not capture the full welfare gain of the

intervention. Similar arguments can be made for additionality to transport user

benefits if a transport scheme can be shown to expand employment at a national

level – through for example lowering the cost of commuting thereby making entering

the labour market more attractive to those on the margin of entering the labour

market. In a case study of the London rail proposal Crossrail DfT(2005a) found that

these additional surpluses due to labour tax distortions were 15% larger than the

agglomeration benefits – so they can be quite substantial.

3.4 Involuntary unemployment effects

It has long been recognised in cost benefit analysis literature that expanding

employment in areas with involuntary unemployment has a welfare value

(Boardman, 2011 pp105-108; Haveman and Farrow, 2011). Modern cost benefit

analysis guides (e.g. EC, 2008 p53) explicitly recognise this through the use of

shadow wages. It is therefore surprising that in a survey of transport appraisal

practice in the EU Odgaard, Kelly and Laird (2005) found that, aside from Germany2,

no national transport appraisal cost benefit analysis guidelines explicitly account for

such welfare benefits despite pockets of high and persistent unemployment

2Since the Odgaard, Kelly and Laird survey Ireland has adjusted its CBA guidelines to shadow price

labour due to the presence of high levels of unemployment.

remaining at a local, and sometimes regional levels. If involuntary unemployment

exists then transport user benefits will not capture the full social value of expanding

employment – that is there is additionality. Involuntary unemployment can be

caused by an immobile workforce, skill mis-matches or some form of labour market

regulation e.g. minimum wages.

Elhorst and Oosterhaven (2008) using a Spatial Computable General Equilibrium

model for the Netherlands challenge the view that involuntary unemployment is not

relevant to a BCA in developed economies with mature transport networks. They

appraise four variants of a maglev3 high speed train line and find that involuntary

unemployment effects in remote regions can have a substantial impact on scheme

benefits. Depending on the route of the maglev line under consideration, they found

that indirect effects due to involuntary unemployment may change benefits as

measured in a conventional transport cost benefit analysis by between -1% and

+38%, and can also dominate agglomeration benefits. Effectively re-distributing

employment in the remote region (from the economic core of the country) generates

substantial efficiency benefits, whilst variants that re-enforce the economic core and

re-distribute employment away from the periphery generate substantial disbenefits.

These disbenefits cancel out the benefits due to increased agglomeration and

productivity in the economic core. Their results are, however, case dependent. In

this instance they arise as a consequence of a labour market failure relevant to the

Netherlands – that of national minimum wages by industry. This is extremely

important. In the Netherlands there is a legal mechanism which means an excess

supply of labour will prevail in certain regions when the market clearing wage is

below the minimum industry wage.

3.5 Search costs and thin labour market effects

Pilegaard and Fosgerau (2008) were the first (and only authors to date) to identify

the relevance of search costs as a market distortion in the appraisal of transport

infrastructure. They implemented a job search model into a SCGE model populated

with Danish economic data. The model was then used to evaluate a transport

quality improvement that increases labour supply at a national level. They report

significant additional benefits of around 30% of commuter user benefits arising from

3Magnetic levitation train

the labour market (for an economy with no labour tax) as a consequence of search

imperfections.

In job search models (see Rogerson, Shimer and Wright, 2005 for a survey)

unemployed workers have difficulties in finding information on job vacancies, and

even if there are many jobs within the workers’ neighbourhood only a small

percentage of them become vacant at any one time. From the perspective of the

employee, labour markets are therefore thin - even if there are many firms. This

then gives firms market power over workers (Bhaskar, Manning and To, 2003;

Manning, 2003a). With this market power firms will only employ labour up until the

point that marginal cost of labour equals its marginal revenue product– which is

below the level of employment that would occur under perfect competition. An

expansion of employment therefore creates a surplus additional to user benefits.

4 THE CASE STUDIES

The influence of wider economic benefits in remote rural areas on the transport cost

benefit analysis is illustrated through five case studies (see Figure 1)

<Insert Figure 1 around here>

Case Study 1: Berneray Causeway and Sound of Harris Ferry, Outer Hebrides,

Scotland

The Berneray causeway (in the Outer Hebrides) opened in April 1999 at a capital

cost of £6.6 million. The Outer Hebrides are in the far north west of Scotland. The

causeway is just less than 1km in length and is free to use (i.e. there is no toll). The

causeway replaced the Berneray ferry (between Berneray and North Uist) and

shortened the Sound of Harris ferry crossing between Harris and North Uist. The

two islands linked by the causeway have a total population of 1,500 people. The

causeway delivered time savings, fare savings and improvements in the

convenience of travel to Berneray. Using business surveys Halcrow (1996 Section

3.1) estimate that businesses on Berneray would experience up to a 20% increase in

turnover and permanent employment would increase by 38.5 full-time equivalent

(FTE) jobs. This employment and output was expected to be displaced from

elsewhere in the UK. Using ex post data user benefits in the opening year were

estimated to be £272,000 (1996 resource prices and 2000 values) (Laird, 2008).

Case Study 2: A82 Tarbet to Fort William, Highlands, Scotland

The A82 trunk road between Glasgow and Fort William is the principal road link

between the West Highlands and the west of Scotland. The 108 kilometre section of

the route between Tarbet and Fort William is single carriageway and passes through

some of Scotland’s most spectacular scenery. Aside from Fort William, with a

population of 10,000, the area served by the road is sparsely populated. The

estimated cost of the route upgrade is £99.3 million (2006 prices). The direct

benefits of the project are driven principally by time savings, though accident savings

are also important. User and safety benefits over a 60 year project life were

estimated to be £93.8 million (discounted) (2002 prices and values) giving a benefit

cost ratio of 1.09 (Scott Wilson, 2006). Wider economy impacts were estimated

using micro surveys of businesses. Regional output was estimated to increase by

£152 million over 30 years (i.e. £5.0 million per annum) with £113 million additional

at the Scotland level. About 208 permanent FTE jobs would be created in the region

of which 70 are additional at the national level (Tribal, 2005 Tables 2 ,4 and 6).

Case Study 3: A96 Nairn, Elgin and Keith bypasses, North East Scotland

The A96 trunk road is an important route that not only links the cities of Aberdeen

and Inverness but it also links remote communities to these cities and via the main

trunk road network to Central Scotland (Glasgow and Edinburgh). The economies of

these remote communities are classically, for remote regions, based on agriculture,

fishing, the manufacture of food and drink products and tourism. The A96 therefore

serves both interurban and remote rural markets. The proposed bypasses are

located either in an urban area (Elgin) or in small towns accessible to an urban area

(Nairn and Keith). As such the proposals do not directly serve remote communities,

however, as significant journey time delays occur in these areas remote communities

benefit from the proposals. In the opening year time savings from completion of the

bypasses have been estimated to provide benefits of £21.5 million (2002 prices)

(Scott Wilson, 2008a). The main indirect effects on employment and output are

associated with developing land the opened for development by the proposals. This

is estimated to generate 8,345 full time equivalent (FTE) jobs all of which would be

located in the bypassed towns. A GVA impact of £134.5 million per annum for the

region (excluding construction impacts) has also been estimated (2007 prices) (Scott

Wilson, 2008a), though no attempt has been made to quantify displacement effects

in the rest of Scotland.

Case Study 4: A9 Perth to Inverness upgrade to dual carriageway,

Highlands,Scotland

The A9 between Perth and Inverness is the main route linking the central and north

Highlands with Central Scotland (including access to ports for export, Edinburgh,

Glasgow and onwards to England). The majority of the 180km route is single

carriageway, which due to limited overtaking opportunities, leads to journey time and

safety issues. The area it passes through is sparsely populated with only three

significant settlements (Pitlochry, Kingussie and Aviemore) none of which has a

population greater than 3,000. In a similar manner to the A96, the A9 serves a

mixture of traffic travelling to/from remote areas as well as interurban traffic. Scott

Wilson (2008b) identify that upgrading the road along its length to dual carriageway

would give 60 year discounted user benefits of almost £1.2 billion (2002 prices and

values). Using business surveys in the short term it was estimated that employment

in the central and north Highlands would increase by 725 jobs and in the longer term

may increase by up to 4,500 jobs with a third of the jobs being in remote areas (Scott

Wilson, 2007). A 30 year discounted regional GVA impact of £956 million was also

estimated, though no attempt has been made to quantify displacement effects in the

rest of Scotland.

Case Study 5: Removal of tolls from Skye Bridge, Highland, Scotland

In 1995 the Skye Bridge was opened. The bridge connects the Isle of Skye to the

Scottish Mainland. It is one of the earliest contemporary uses of private finance to

fund transport infrastructure in the UK. The Isle of Skye has a population of 9,200

and has a strong dependence on tourism and agriculture and fishing. The bridge is

the dominant transport link between the island and mainland Scotland. The tolling of

the bridge was always controversial and on 21 December 2004 the Scottish

Executive ‘bought’ the bridge and the tolls were removed. The removal of the tolls

led to a 50% increase in the traffic using the bridge. DHC (2007) estimated user

benefits of £5.9 million for a single year (2006 in 2006 prices) as a consequence of

the toll removal (includes the removal of the toll and delays at the toll booth). They

were not able to clearly identify any employment impacts of the toll removal due to

problems in defining the counterfactual. Using output and employment multipliers

from the increased income associated with the saved toll revenue McQuaid and

Greig (2007), in an ex ante study, anticipated that a potential 256 FTE jobs could be

created from the toll removal – of which almost 80% would arise from an increase in

tourism – with an associated gain in regional GDP of £4.7 million per annum. No

displacement effects to the rest of Scotland were estimated.

5 ESTIMATING WIDER ECONOMIC BENEFITS IN REMOTE RURAL AREAS

5.1 Partial equilibrium

In Section 2.2 we briefly outlined the different methods available to model transport’s

impact on the wider economy. Basically only SCGE models are holistic enough to

both model wider economy impacts and output measures of changes in welfare. If

one of the other wider economy methods is used a partial equilibrium approach can

be adopted. With such an approach one treats each market in isolation and

calculates the surpluses in that market that are additional to transport user benefits.

This is exemplified by the UK’s Department of Transport’s approach (DfT, 2005a;

2012). The criticism with using partial equilibrium methods is twofold. Firstly, the

general equilibrium effects have to be assumed to be zero. Secondly examining

each market individually may result in double counting between the ‘additional’

surpluses. Clearly this is a strong criticism, particularly when we consider that for the

remote rural cases being examined multiple market failures in both the labour and

the product market can exist.

To date only Venables and Gasiorek’s (1999) have developed results for both partial

and general equilibrium cases. Newbery (1998) considered the general equilibrium

effects to be small, but the Venables and Gasiorek work is based off sysnthetic data

and does not consider multiple failures in several different markets. Its results

cannot therefore be generalised. On the other hand a partial equilibrium analysis is

much easier to implement than a general equilibrium analysis – which for the

transport context faces a number of unique challenges regarding linking transport

demand models and SCGE models and modelling the impacts of transport costs on

production (Tavasszy, Thissen, and Oosterhaven, 2011).

As a first test regarding whether wider economic benefits are of a scale to warrant

further research a partial equilibrium approach has some merits. It may not give a

precise result but it will identify whether wider economic benefits are relevant and

whether further research on the issue is warranted. We have therefore used a

partial equilibrium approach to these case studies. In doing so we take the transport

user benefits from each of the case study appraisals and add to them a surplus

associated with each market failure or distortion: agglomeration, imperfect

competition, involuntary unemployment, thin labour markets, labour supply.

In the context of the five case studies we know consider the evidence for whether

each of the market imperfections/distortions is relevant and if so how it should be

included in a partial equilibrium analysis so as to capture the additionality to transport

user benefits.

5.2 Agglomeration effects

Agglomeration externalities are generic, but the evidence to date is that they have

little effect on remote rural economies. In part this is due to the predominant

industries that are located in such areas (e.g. fishing and agriculture), but also

because populations are dispersed and urbanisation and localisation economies fall

away quite quickly with distance (Graham, 2009), even though there is some

evidence of industry clustering in remote regions (Graham, 2004). Analysis

conducted by the UK DfT (2012) also shows that agglomeration economies are only

empirically relevant to a transport CBA near major population centres. Empirically

Bråthen (2001) found no evidence of external economies affecting the growth of four

firms located near to recently constructed fixed link island crossings in remote areas

in Norway. Agglomeration economies do not therefore appear relevant to our case

studies. Surpluses additional to transport user benefits associated with these effects

have not therefore been estimated.

5.3 Involuntary unemployment effects

The UK, as a whole, has a flexible labour market, though pockets of involuntary

unemployment exist where skill mis-matches and residential immobility occur.

Evidence however indicates such pockets are mainly located in urban areas. Rural

unemployed workers migrate ensuring the rural economy remains at or close to full

employment. Monk and Hodge (1995) for example found that those losing jobs in

rural areas have a higher propensity to migrate away from an area completely rather

than remain in an area and search for a job. Furthermore the unemployment rate in

the Highlands and Islands of Scotland is significantly lower than the Scotland and

British average (HIE, 2011). This indicates that in remote rural areas of Scotland the

labour market is at or close to full employment, and involuntary unemployment

effects are not relevant to our case studies. Surpluses additional to transport user

benefits associated with these effects have not therefore been estimated.

In times of economic decline remote rural areas can experience falling population

levels and a tight labour market simultaneously. This is certainly the case in

Scotland. Whilst out-migration by the labour force from remote rural areas is rightly

a cause of policy concern it does not constitute a market failure. In other countries

where rural labour markets are regulated differently and exhibit different

characteristics market failures may occur (as in the Dutch example cited earlier).

5.4 Imperfect competition

From the perspective of remote rural areas the expectation is that their remote

nature would lead to higher price marginal cost margins than in other parts of the

economy. Unfortunately available evidence is almost exclusively focused on

industry classifications and does not distinguish by area type (beyond nation states)

though Richards, Acharya and Kagan (2008) found that 38% of the economic

surplus of non-metropolitan banks was due to spatial market power. This is also the

case for the Scottish context, where if any regional disaggregation occurs it is at the

UK level, where Scotland is treated as a region in the UK (e.g. Harris, 1998). There

is therefore a clear evidence gap. To gain an understanding as to whether price

marginal cost margins differ between remote rural and more accessible areas, as

theory would suggest they should, we turn to evidence on rural-urban price

comparisons and an industry specific case study. Together these demonstrate that

market isolation allows high price marginal cost margins to occur in remote rural

parts of Scotland.

Surveys of prices in Scotland have consistently found that prices are higher in rural

areas. For example Sneddon Economics (2003 p.1) found that petrol prices were on

average 9.7% higher than in urban areas whilst food was 11.0% higher, while more

recently Hirsh et al. (2003) found that food prices in remote rural parts of Scotland

were between 10 and 50% higher compared to those in an English rural town . Not

all of this price difference can be attributed to differences in market power as the cost

of transporting goods to the locality and differences in economies of scale in

production (if goods are produced on-site) and economies in retailing account for

some of the difference. Identifying the component of the price differential attributable

to market power and the component attributable to differences in operating costs

requires access to firm specific data. In the absence of such an analysis our best

understanding of the market conditions in Scotland’s remote rural areas is from

industry specific studies. In this respect the UK Office of Fair Trading (OFT) has

conducted three investigations into the supply of petrol (OFT, 1998; 2000; 2013).

The OFT has the power to examine companies’ financial transactions to identify if

excessive margins are made, a power that other researchers do not have. They find

that the petrol industry is competitive across the UK as a whole because of the

proximity of consumers to many different suppliers. This competitive argument

breaks down in remote areas where they concluded that a lack of competition in

some localities gave rise to higher prices (OFT, 1998 p.73) and in some instances

excessive pricing due to market power (OFT, 2000). They found that margins across

the Highlands and Islands are on average 64% higher than across the UK. The

higher on average margins in the region disguise wide variations in local margins:

from margins that are comparable to the rest of the UK (in the urban and more

accessible rural areas) to margins three times that (in the very remote parts of the

region). Taking the petrol supply sector as a barometer for price-cost margins in

other sectors leads us to consider that price cost margins in the remote rural parts of

Scotland can quite easily be double those in urban environments.

Following Davies (1999) the economic value of expanding output in imperfectly

competitive markets is the product of increased output, the elasticity of demand for

goods and the price-cost margin. With an average price cost margin for the UK of

0.2 (DfT, 2005a), an elasticity of demand of 0.5 and margins in remote rural areas

being more than double those elsewhere, this indicates that the additional welfare

benefit of expanding output in remote rural areas is about 20% of the expansion in

output. In only one case study, the A82 Tarbet to Fort William, has the increase in

output (net of displacement) been calculated. For the other studies only the regional

gain has been calculated – most of which will be displaced from elsewhere in

Scotland. For the other four case studies we therefore use user benefits of business

and freight traffic as an estimate of the expansion in output in this calculation.

5.5 Labour supply effects

As with the rest of the UK, workers in the five case study areas pay an income tax on

earnings – a labour tax. This distortion means that increases in employment at a

national level will create an additional welfare benefit to transport user benefits.

Whilst this market distortion is relevant to remote rural areas only one of the five

case studies generates additional employment at the national level – the A82 Tarbet

to Fort William project. These new jobs create a surplus additional to user benefits,

in a partial equilibrium setting, equivalent to the income tax revenue derived by

government. This has been calculated using existing tax rates and local wage data.

5.6 Search costs and thin labour market effects

Thin labour markets are particularly relevant in remote areas as sparse populations

give rise to a limited choice between employers for workers (Findeis and Jenson,

1998; Vera-Toscano, Phimister and Weersnik, 2004). Firms therefore have market

power over workers in thin labour markets. Remote rural labour markets in the UK

and Scotland exhibit properties consistent with being thin. There are few jobs and

where they do exist vacancies are often not advertised. Successful job search is

often attributed to contacts and networks (Monk and Hodge, 1995; Lindsay, Greig

and McQuaid, 2005). Furthermore workers do not have ready access to job centres.

It is therefore hard to find work in remote rural areas in Scotland.

Empirical evidence on the presence of thin labour markets can be found in the

degree of compensation that occurs for commuting costs. Theories on job search

predict that workers will only receive partial compensation for commuting costs and

evidence of such partial compensation has been found at the aggregate level

(Manning, 2003b; van Ommeren and Rietveld, 2005; Rouwendal and van Ommeren,

2007). Empirically Laird (2008 Chapter 8) finds evidence of thin labour markets by

examining whether workers in remote rural areas receive compensation for their

commute. Laird also found evidence that in Scotland in addition to workers in

remote labour markets those with low skills and women may also face thin labour

markets.

Remote rural labour markets are not the only segment of the labour market that is

thin. The labour market literature identifies that women, those with low skills and

ethnic minorities lack mobility and face geographically constrained job search areas

(Madden, 1981, 1985; Zax, 1991; Ihlanfeldt, 1992; McQuaid, Greig and Adams,

2001). From a cost benefit analysis perspective this is important as in the main

transport schemes re-distribute employment between regions. If some of the

employment that has been re-distributed comes from a thin labour market then the

net ‘additional’ impact of the increased employment in a remote rural area will be

much smaller than if all the employment had been re-distributed from a fully

competitive regional labour market.

The additional surplus associated with creating employment in thin remote Scottish

labour markets has been estimated in two stages. Firstly the number of jobs created

to which an additional surplus should be attached was estimated. To do this

employment estimates from the economic impact studies were split into employment

that occurred in remote rural areas and employment that occurred elsewhere (e.g.

the cities/towns of Inverness, Elgin, etc.). There is no additional welfare benefit to

transport user benefits to creating employment in urban or urban accessible areas.

The remote rural employment was then further split into those jobs that were

additional at the national level and those that were displaced. Only the A82 Tarbet

to Fort William study identified employment additional at the national level. An

additional surplus to transport user benefits is generated by all employment that is

additional at the national level. For displaced employment an additional surplus to

transport user benefits is only generated for skilled male displaced employment.

This is because women and low skilled workers face thin labour markets throughout

Scotland. Local proportions on skill and gender levels of the workforce were used to

then identify of the displaced jobs the proportion that would be filled by skilled male

workers.

In the second stage the welfare benefit per job per year is estimated and applied to

each new job to which an additional welfare surplus should be attached. The

additional surplus is given by the gap between the marginal product of labour and

the wage received by the worker. There is no specific evidence on this gap for rural

areas of Scotland, however, Manning (2003a) argues that on balance and for the UK

as whole the evidence indicates the wage is 17% below the marginal product of

labour (i.e. the marginal product of labour is 20% higher than the wage). Local

wages and this proportion are then used to identify the welfare benefit for each job

created for which a surplus should be applied.

5.7 Case study findings

Table 1 presents the results of the partial equilibrium calculations of the additional

surpluses associated with wider economy impacts for the five case studies. Here it

can be seen that the additional welfare benefit due to imperfect competition ranges

from 5.5% (£15k) of the ‘narrow’ Present Value of Benefits (PVB) for the Berneray

Causeway/Sound of Harris Ferry to 12.8% (£12.0M) for the A82. It can be seen that

the estimates for the A82 is higher than the estimates for the other schemes. This is

driven in part by the fact that the A82 is expected to expand national output rather

than just displace output from other regions. Possibly the different methods

associated with modelling the increase in output is also a factor – as for the A82 the

estimates have been based on the economic impact report that used business

surveys, whilst for the other 4 case studies it has been based on the business and

freight time savings.

With respect to thin labour markets there is quite a range in benefits – from nothing

(the A96 bypass schemes) to £19.2M (19% of the ‘narrow’ PVB) for the A82 Tarbet

to Fort William route. The range arises as a result of how much of the employment

created by the schemes occurs in remote rural areas and how much of that

employment has been displaced from elsewhere. For the A96 and A9, both of which

are important inter-urban routes, a lot of the employment that is created is in urban

areas or small towns close to urban areas – two thirds in the case of the A9 and all

of the jobs in the case of the A96. In contrast it is estimated that the A82 would

increase net employment across the UK by benefiting an important export orientated

sector located in the north west of Scotland – fish farming and salmon farming in

particular. This gives rise to the large additional employment welfare benefits

associated with this proposed route upgrade. The additional employment at the

national level created by the A82 also creates a large additional surplus due to the

distorting effects of labour taxes.

The presence of market distortions in remote rural areas means that transport

schemes that affect employment and output can give rise to welfare benefits that

cannot be fully captured by looking at the transport market in isolation. For the case

studies examined here these ‘additional’ benefits range from between 6.6% to 37.5%

of the direct benefits occurring in the primary transport market. Clearly at the upper

end of this range these benefits are substantial. Saying that, the PVB does not

change in order of magnitude. The policy implication of this finding is that including

these wider economic benefits will not transform the transport CBA from being poor

to being good but it will be sufficient to affect prioritisation/ranking of schemes. This

is because firstly the levels of additionality vary from case to case, and secondly

because at the upper end of the range the increment in the benefit cost ratio will be

sufficient to, for example in the UK, shift the scheme between different value for

money categories4.

This variation in the importance of these wider economic benefits between transport

projects is interesting. It firstly shows that no rule of thumb can be adopted

regarding the relationship between the benefits in the primary transport market and

the additional welfare benefits that occur in the secondary markets due to the

presence of market distortions in those markets. The relationship between the two is

case dependent and varies with the type of route under consideration and the

markets and locality served by the route. Only a small change in benefits occurs for

routes through remote rural areas where the majority of the traffic is inter-urban. The

additional welfare value of the wider economic benefits is much larger when the

majority of the traffic using the route is directly related to remote areas and where the

scheme generates employment and output that is additional at the national level.

6 CONCLUSION

Whether surpluses observed in the primary transport market give a full description of

the welfare changes generated by transport schemes including wider economic

benefits is an active topic. There is a theoretical argument that the isolation of

remote rural areas can lead to market failures in both the product market and the

labour market. This is because a lack of choices means that local monopolies can

prevail, whilst workers can find difficulty finding employment due to immobility

problems leading to involuntary unemployment or because labour markets are thin.

Using five case studies this paper has demonstrated that imperfect competition,

labour taxes and thin labour markets are two relevant market distortions in a remote

rural Scottish context. The literature also suggests that other market failures,

4 In the UK a scheme has a low value for money (VfM) if the BCR is between 1.0 and1.5, medium if the BCR is between 1.5 and 2.0, high if the BCR is between 2.0 and 4.0and very high if the BCR is greater than 4.0 (DfT, 2005b)

associated with and agglomeration and involuntary unemployment, can be relevant

in other regional contexts. Each of the case studies has a significant local economic

impact. This impact in combination with the identified market imperfections is

empirically relevant to cost benefit analysis – increasing benefits by up to 37.5% in

one case study. The degree to which a focus on only the primary transport market

understates the true welfare impact of the proposals varies with the type of transport

route under consideration and the markets and locality served by the route. A key

issue is how much of the anticipated regional economic impact is displaced from

elsewhere and how much is additional at the national level. To a certain extent this

makes the analysis dependent on the quality of the economic modelling that inputs

to the cost benefit analysis.

From a policy perspective these empirical findings are relevant in two ways. Firstly it

shows that focusing efforts on measuring the surpluses occurring in the primary

transport market will capture the majority of a remote rural transport scheme’s

benefits. Secondly the variation between schemes in the way wider economic

benefits affect a cost benefit analysis means that their exclusion may alter scheme

ranking/prioritisation in an investment programme and/or lead to a bias in the

decision-making.

This paper has brought together disparate strands of research to make a case that

wider economic benefits are relevant to transport schemes in remote rural areas.

There remains the need for further research. Firstly this paper has not considered

market failures in the land market, and the analysis presented here needs to be

developed in that direction. Secondly, a partial equilibrium method has been used to

illustrate the scale of the benefits that a focus on the primary transport market

excludes. An important next step in demonstrating the relevance of wider economic

benefits in remote areas is to use a general equilibrium analysis - as multiple

markets and market failures are under consideration. Finally, there is a need to

develop the evidence with which to estimate the relevant surpluses in the product

and labour markets. Such evidence will of course be case dependent and will most

likely vary between countries and also within countries. Finally, any attempt to

include wider economic benefits in a cost benefit analysis needs reliable estimates of

these impacts. To date the different methods available lead to very different

estimates – and this undermines the quality of the CBA. Improvements in regional

economic modelling are therefore also needed.

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ACKNOWLEDGEMENTS

We are grateful to Transport Scotland, Highlands and Islands Regional Transport

Partnership (HITRANS) and Highlands and Islands Enterprise (HIE) for use of their

data.

Figure 1: Case study locations

Table 1: Scottish case studies – welfare benefit measures

BernerayCauseway

and Sound ofHarris ferry

A82 Tarbet toFort William

routeupgrade

A96 Nairn,Keith and

Elginbypasses

A9 Perth toInverness

dualcarriageway

upgrade

Skye Bridgetoll removal

Units ofaccount

Price base 1996 resourceprices and

2000 values

2002 marketprices and

values

2002 marketprices and

values

2002 marketprices and

values

2006 marketprices and

values

Single year/evaluation period Opening yearonly

60 years Opening yearonly

60 years Single year(2006)

Units £thousands £millions £millions £millions £millions

Impacts inprimarytransportmarket

(A) User benefits 272.00 80.92 21.50 1,176.60 5.95

(B) Safety benefits ---(1)

12.86 ---(1)

---(1)

---(1)

(C) Carbon costs ---(1)

---(1)

---(1)

-3.29 ---(1)

(D) ‘Narrow' measure of PresentValue of Benefits (=A+B+C)

272.00 93.78 21.50 1,173.31 5.95

Indirecteffects onoutput andemployment

(E) Agglomeration 0.00 0.00 0.00 0.00 0.00

(F) Imperfect competition 15.00 12.02 1.57 67.93 0.55

(G) Labour supply 0.00 3.95 0.00 0.00 0.00

(H) Involuntary unemployment 0.00 0.00 0.00 0.00 0.00

(I) Thin labour markets 23.00 19.21 0.00 9.46 0.21

(J) ‘Wider' measure of PresentValue of Benefits(=D+E+F+G+H+I+J)

310.00 128.95 23.07 1,250.70 6.71

Proportion of BCA benefitsarising from market distortionsthat affect output andemployment (=J/D-1)

14.0% 37.5% 7.3% 6.6% 12.8%

Notes: (1) Not estimated in original study