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The wider economic impacts of transport investments The wider economic impacts of transport investments SUMMARY WIDER ECONOMIC IMPACTS OF TRANSPORT INVESTMENTS The development of transport infrastructure engenders economic growth. Several studies have demonstrated that investments in transport capital reduce the costs of transport and production, and thus contribute to economic growth and productivity. In addition to these long run impacts during the operation phase, there are more immediate economic impacts during the construction phase. The economic impacts of new and improved transport capacity are complex and often indirect. Transport infrastructure investments will not improve the economic vitality of a region unless it has sufficient economic capacity and the labour, land-use, housing and economic development policies, for example, supporting the positive economic development. Investments in capacity are often necessary but they may not create conditions sufficient for economic growth. Transport infrastructure investments require public financing. Feasibility assessment is needed to ensure reasonable and acceptable allocation of allowances. Relevant economic, environmental and social impacts should be considered. There is an increasing awareness within the transport sector, that decisions concerning transport system development are associated with scale effects and externalities that produce more than just travel costs savings. The planners and decision-makers need to know more about the wider economic impacts regarding individual infrastructure projects and also more generally concerning transport policies. AVAILABLE TOOLS FOR ECONOMIC IMPACT ASSESSMENT Transport sector has a long tradition of using the principles of practical cost benefit analysis (CBA) in transport project appraisal that analyses the primary impacts of transport project proposals. The standard transport project assessment is necessary but not sufficient for the estimation of the wider economic impacts. There are several analytical techniques for the estimation of the economic development impacts, varying from simple case studies and surveys to complex economic simulation modelling. However, there is no single analytical tool that is equally useful to all of the information needs in the planning and decision making. The purpose and level of desired sophistication of the analysis varies. Computable General Equilibrium models (CGE) can be considered powerful tools to be used in the assessment of economic impacts of infrastructure investments. In this project, RegFinDyn and RegSweDyn CGE-models have been defined to be used in the assessment of rail investments in Finland and in Sweden. The use of these models is, however, rather expensive and requires specific skills and knowledge. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 2 The wider economic impacts of transport investments This project has aimed to tackle the contradicting needs for a complex CGEmodelling and the desired easiness and flexibility of the analysis: A spreadsheet tool with a streamlined interface that uses the results of a large number of previously made CGE-model simulations. NEW PLANNING TOOLS WEBRAILSWE AND WEBRAILFIN The development of the tool led to twin tools that were named WebRailSwe and WebRailFin. The tools are made for a quantitative approximation of the wider economic impacts of large rail investments in the national areas of Sweden or Finland. The wider economic impacts calculated by this tool are supplementary to the results of a standard project assessment (CBA). The tools use generalised results of RegSweDyn and RegFinDyn CGEmodelling. The Swedish tool covers 8 areas (Nuts 2) and is based on generalised results of 128 scenario simulations. The Finnish tool covers 4 areas (Nuts 2 except Åland) and is based on a total of 200 scenario simulations. Both tools contain four main parts: 1) Basic calculation where the user enters the input parameters and receives the main results of the calculation, 2) Base scenario 2013–2040, that defines the reference alternative for the investment under investigation, 3) calculation of the investment shock and 4) calculation of the productivity shock. The four economic indicators calculated by the tools are real GDP, real household consumption, employment and population. The basic case of using the tools is to calculate the wider economic impacts of a particular rail investment. The tools can also be used to compare the economic impacts of similar investment in various national areas. In addition, the projections of the regional Base scenarios may be useful as such. The tools can calculate only at Nuts 2 level, but the relative results may be used to approximate economic impacts at Nuts 3 level, too. CONCLUSIONS It has been proved that it is possible to have a tool that is relatively simple to use but gives results that are based on comprehensive CGE-modelling. This can be considered a promising start for a wider use of advanced modelling of economic impacts in the transport sector. However, the results of this project, WebRailSwe and WebRailFin, are only applicable to rather large rail investments, and the results are calculated and presented on a spatial resolution that is rather coarse. Further work is needed to define similar tools for road investments and other forms of transport improvements, and to define the spatial resolution of the tools. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 3 The wider economic impacts of transport investments FOREWORD The Bothnian Green Logistic Corridor (BGLC) is an international project working to develop the infrastructure on the Corridor and its connections. The Bothnian Corridor transport network connects northern Europe and its rich natural resources to the most densely populated areas in Europe. The Bothnian Corridor is a strategically significant artery for securing efficient raw material transport and sustainable economic growth in Northern Europe. The project brings together public authorities and private stakeholders to cooperate for future transnational transport policies and actions. Work Package 5 of the BGLC-project aims to increase the knowledge and understanding of the economic impacts of infrastructure development on industrial development and new potential, on their value chains, and on regional economy. This project ‘Wider economic impacts of transport investments’ is Activity 5.3 of the Work Package 5. The objectives for the project in hand were to elaborate the concepts and mechanisms of the wider economic impacts of transport investments and, to develop a tool to assess those impacts. This report of the economic impacts of transport investment is the first deliverables of this project. The other deliverables are two assessment tools developed in the Microsoft Excel environment to calculate the economic development impacts of large rail infrastructure investments in Sweden (WebRailSwe2014.xlsx) and in Finland (WebRailFin2014.xlsx). The tools are presented and demonstrated in this report. The methodological challenge with the tools has been the idea to combine complex computable general equilibrium (CGE) modelling with a need to have a flexible and “simple” tool. This project proves that such tool is possible to make. However, further work is needed to define similar tools for road investments and other forms of transport improvements. The spatial resolution should then be defined to Nuts 3, too. The Steering Group of this study included the following representatives Jukka Lindfors, Council of Tampere Region Pentti Hämäläinen, Council of Tampere Region Hannu Siitonen, Uusimaa Regional Council Erkki Vähätörmä, Uusimaa Regional Council The visiting representatives of the Uusimaa Regional Council in the Steering Group meetings during the project have been Ilona Mansikka, Markku Hyypiä and Olli-Pekka Hatanpää. This study was conducted by a following consultant team: Heikki Metsäranta, Strafica ltd, project manager Professor Hannu Törmä, University of Helsinki, Ruralia Institute, RegFinDyn and RegSweDyn modelling Jouko Kinnunen, Statistics and Research Åland, development of the WebRailFin and WebRailSwe tools Seppo Laakso, Urban Research TA ltd, the theoretical framework of economic development impacts (Chapter 3) Urszula Zimoch the University of Helsinki Ruralia Institute, the economic modelling tools (Chapter 4). Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 4 The wider economic impacts of transport investments CONTENT 1 INTRODUCTION ............................................................................................................................................................................... 6 2 THE ECONOMIC IMPACTS OF TRANSPORT INVESTMENTS – AN OVERVIEW ............................................................ 7 2.1 2.2 2.3 2.4 2.5 3 THE ECONOMIC DEVELOPMENT IMPACTS OF TRANSPORT INVESTMENTS........................................................... 11 3.1 3.2 3.3 3.4 4 ECONOMIC IMPACTS IN TRANSPORT DECISION MAKING.................................................................................................................................. 7 THE DIRECT ECONOMIC IMPACTS OF TRANSPORT INVESTMENTS.................................................................................................................. 7 TYPES AND MECHANISMS OF ECONOMIC DEVELOPMENT IMPACTS ............................................................................................................... 8 ARE WIDER ECONOMIC IMPACTS ADDITIONAL TO DIRECT TRANSPORT BENEFITS? ................................................................................... 9 THE SPATIAL SCOPE ........................................................................................................................................................................................... 10 IMPACTS ON ECONOMIC GROWTH AND EMPLOYMENT ................................................................................................................................. 11 IMPACTS ON AGGLOMERATION, COMPETITION AND LABOUR SUPPLY ........................................................................................................ 12 IMPACTS ON LAND USE AND PROPERTY VALUES............................................................................................................................................ 13 POTENTIAL FOR WIDER DEVELOPMENT OF LAND USE ................................................................................................................................. 14 TOOLS FOR ECONOMIC DEVELOPMENT IMPACT ASSESSMENT .................................................................................. 16 4.1 TRANSPORT PROJECT ASSESSMENT (COST BENEFIT ANALYSIS CBA) ....................................................................................................... 16 4.2 SURVEYS, INTERVIEWS AND MARKET STUDIES .............................................................................................................................................. 17 4.2.1 Interviews and surveys .....................................................................................................................................................................17 4.2.2 Market studies ......................................................................................................................................................................................18 4.3 COMPARATIVE ANALYSIS – CASE STUDIES ..................................................................................................................................................... 18 4.4 LAND-USE–TRANSPORT INTERACTION SIMULATION MODELS .................................................................................................................... 19 4.5 ECONOMIC MULTIPLIER – INPUT –OUTPUT (IO) MODELS .......................................................................................................................... 19 4.6 AN OVERVIEW OF COMPUTABLE GENERAL EQUILIBRIUM (CGE) MODELS ............................................................................................... 20 4.7 THE REGFINDYN MODEL .................................................................................................................................................................................. 22 4.8 INTEGRATED CGE – TRANSPORT MODELS ..................................................................................................................................................... 24 4.9 CONCLUSIONS ..................................................................................................................................................................................................... 24 5 A PLANNINGTOOL FOR ECONOMIC IMPACT ASSESSMENT ........................................................................................... 26 5.1 INTRODUCTION TO THE METHODOLOGY......................................................................................................................................................... 26 5.2 REQUIRED BACKGROUND INFORMATION AND PREPARATORY WORK ........................................................................................................ 27 5.2.1 The basic calculation .........................................................................................................................................................................27 5.2.2 Additional options ..............................................................................................................................................................................29 5.3 THE RESULTS ...................................................................................................................................................................................................... 29 5.4 THE CGE-MODELLING TO CREATE THE RESULT DATA BANKS FOR THE PLANNING TOOLS .................................................................... 30 5.4.1 Data sources and dimensions .........................................................................................................................................................30 5.4.2 Population dynamics .........................................................................................................................................................................32 6 DEMONSTRATION OF THE TOOL ........................................................................................................................................... 33 6.1 EXPLORING THE WIDER ECONOMIC IMPACTS OF A MAJOR RAIL INVESTMENT.......................................................................................... 33 6.1.1 Norrbotniabanan ................................................................................................................................................................................33 6.1.2 Seinäjoki–Oulu .....................................................................................................................................................................................36 6.2 EXPLORING THE REGIONAL DIFFERENCES OF WIDER ECONOMIC IMPACTS ............................................................................................... 40 6.2.1 Comparing similar investments in different national areas of Sweden ........................................................................40 6.2.2 Comparing similar investments in different national areas of Finland ........................................................................41 6.3 EXPLORING THE BASE SCENARIO FOR REGIONAL PROJECTIONS ................................................................................................................. 43 6.3.1 Sweden ....................................................................................................................................................................................................43 6.3.2 Finland ....................................................................................................................................................................................................44 7 FINAL CONCLUSIONS AND RECOMMENDATIONS ............................................................................................................. 46 8 REFERENCES .................................................................................................................................................................................. 48 Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 5 The wider economic impacts of transport investments 1 INTRODUCTION This study focuses on the economic development impacts of infrastructure investments in the context of Bothnian Green Logistic Corridor. The main focus is on the development of rail transport. The development of both efficient and environmentally friendly transport solutions is important for the following reasons: More capacity is needed to respond to the expected increase of freight transports during the next decades The competitiveness of the central and northern regions of Scandinavia requires efficient transport connections to the European and global markets, which in turn need the availability of the natural resources and products of the Northern regions The economic growth must be environmentally sustainable, too. The role of public authorities in this context is to ensure sufficient operating environment for the private firms to engage in profitable business. Transport infrastructure is an integral part of the economic process. The local and national authorities and governments have the power to decide, how to develop (or not to develop) the transport infrastructure in the Bothnian Corridor. The decisions they make will have impacts on the economy. Therefore it is important, that the decision-making is provided with sufficient and reliable information about the economic impacts. The two main tasks of this study have been (1) a literature review of the wider economic impacts of transport investments and (2) development of an evaluation tool to quantify those impacts. The previously set context for the study has been the development of the railway infrastructure within the Bothnian corridor. The literature review was carried out on the wider economic impacts of transport investments (Chapters 2 and 3), and the methodologies to assess those impacts (Chapter 4). Both qualitative and quantitative approaches were concerned, as well as existing tools and models. The review builds an understanding of the wide range of wider economic impacts that can follow transport improvements, and the potential methods for quantifying these. Finally, the review compares the computable general equilibrium (CGE) models with other methods in the estimation of the wider economic impacts. An assessment tool was developed in the Microsoft Excel environment to calculate and present the wider economic impacts of rail infrastructure investments within the spatial scope of Finland and Sweden (Chapter 5). The core of the evaluation tool has been built by using RegFinDyn and RegSweDyn CGE-models to compute several investment and impact scenarios of two actual investment projects, Seinäjoki–Oulu in Finland and Norrbotniabanan in Sweden. These two projects were used also in the demonstration of the tool (Chapter 6). Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 6 The wider economic impacts of transport investments THE ECONOMIC IMPACTS OF TRANSPORT INVESTMENTS – AN OVERVIEW 2 2.1 Economic impacts in transport decision making Transport connects people, businesses and resources. The demand for transport is derived demand reflecting the economic activities of firms, households and individuals. Changes in the transport system, in turn, have impacts on the economic development, that can be defined by society’s strategic economic goals and objectives (Littman 2010) concerning e.g. income, employment, competitiveness, business activity, property values, affordability, tax revenues, equity. These objectives have local, regional and national dimensions. Investment decisions are key decisions in every long term development strategy. The main underlying reason to use economic resources now is to gain economic benefits in the future. Decisions concerning transport infrastructure are made by public agencies and governments, and are expected to support the public good. Therefore, project appraisal is used to investigate and reason the consequences of the decisions to assist the decisionmakers to reach informed and rational choices. Generally speaking, transport investments generate two categories of benefits (Berechman 2009): Direct, primary benefits within the transport system and secondary, externality benefits in the other sectors of society and the economy. The primary impacts of transport investments concern accessibility, traffic safety and transport related costs both internal and external. Environmental and other restrictions and impacts are taken into account and may in some cases be of great importance and interest. However, the main motivation for transport investments comes down to economic goals and objectives. Transport authorities in most countries have a long tradition of using the principles of practical cost benefit analysis (CBA) in transport project appraisal. The theoretical framework for such an analysis is broad, and therefore there are International (e.g. World Bank), European (EU) and nationally harmonised guidelines for transport project assessment. The CBA provides the decision-making with tools to analyse the primary impacts of transport project proposals. There is an increasing awareness within the transport sector, that decisions concerning transport system development are associated with scale effects and externalities that produce more than just travel costs savings. There can be wider economic effects following the investment money spent on the region and the transport cost reductions. These benefits may include, for example, employment generation, increased productivity and availability of labour, changes in land and property values. The concern in this respect is that without due recognition of the broader impacts in the transport decision-making framework, the decisions may lead to undesired allocation of investment funds. Since transport investments affect economic growth and welfare, it is of importance in the decision-making to get a wide view of the economic impacts. Direct, indirect and induced effects together provide the total economic impact of transport investments. 2.2 The direct economic impacts of transport investments The direct economic impacts of a transport investment include investment and maintenance costs, operating costs of transport operators and the time costs for business travel and freight. Further, the costs of traffic accidents and pollution include potentially relevant cost items. The principal economic impact of a transport improvement is the time savings to freight drivers and business travellers. The value placed on travel time savings is the opportunity cost of the lost time that is often measured as gross hourly labour cost (as is in Finland and in Sweden). Time savings in business travel have direct implications on the productivity of the employees. It should be noted, however, that there are possibilities to use the Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 7 The wider economic impacts of transport investments travel time productively. This phenomenon may be tackled by using different values of time for different modes of transport and different trip purposes. For freight movements there can be additional gains from reducing the time goods are held up in transport. In particular for higher-value goods, time savings could mean economic efficiency gains. Improved reliability of transport, on the other hand, may lead to tighter scheduling and thus improved productivity. (Kernohan and Rognlien 2011.) From the transport operator point of view, there are usually direct economic impacts concerning fuel or electricity consumption, vehicle rotation (vehicle hours or vehicle days) and working time of drivers and other personnel. These impacts affect the productivity and quality of service of transport operators. In addition, traffic accidents have four kinds of economic impacts: costs of medical treatment, loss of production and consumption, material costs and administrative costs. 2.3 Types and mechanisms of economic development impacts The economic impacts of transport investments are commonly divided into short- and long-run economic development effects. The effects in the short-run or in the long-run are associated with investment multiplier effects and regional economic growth effects, respectively (Berechman 2009): Short-run multiplier effects: The value of economic activity following the money spent on construction and purchases during the investment period. The multiplier effects of large investments are generally quite high in terms of changes of personal income, jobs and gross regional product. Thus, these impacts are of interest especially among local decision-making. Long-run effects on regional economic development: The changes in the economic development following the primary transport effects (time and cost changes). The development effects are structural changes in the impacted markets that materialise in a long period of time. The value of economic development impacts is quite low compared with the short run multiplier impacts. It is also a challenge to separate the impact of a particular transport investment from all other land-use, economic, demographic and other transport system developments taking place in the region during the following decades. Economic development impact types can generally be categorized as follows: Impacts relating to overall area economy; economic output, gross regional product, value added, personal income, employment Impacts relating to specific economic development such as productivity, capital investment, property appreciation and fiscal impacts including both public revenues and expenditure The development impacts may occur as a direct consequence of the investment. The most interesting impacts, however, are the indirect, induced and dynamic development impacts: Direct mechanism: The most significant impact is the reduction of transport costs. Businesses of the region are offered improved accessibility to markets and resources (labour, materials and equipment) and, the benefits of reduced costs of transport and thus enhanced productivity. Direct impacts of construction on wealth and job creation. Indirect mechanism: “Secondary” entities such as local businesses supplying inputs to directly affected businesses. Induced mechanism: Increased income leads to increased spending and thus to increased demand. Dynamic mechanism: Long-term changes in economic development; business location patterns, work force, labour costs, prices, land-use changes, that in turn affect the wealth in the region. Figure 1 below summarises the causalities of the economic impacts of a transport investment. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 8 The wider economic impacts of transport investments Figure 1. 2.4 Types and mechanisms of economic development impacts (figure based on an original by Sinha & Labi 2007) Are wider economic impacts additional to direct transport benefits? Many of the development impacts of an infrastructure investment are in fact capitalised direct impacts. Therefore, it is a widely applied rule that the wider economic impacts of an investment project are not to be added to the direct (transport economic) benefits. The estimates of the wider economic impacts will, however, be of great interest in the decision-making process. There may also be external economic impacts to transport cost reductions. Kernohan and Rognlien (2011) implicates that an infrastructure investment can produce benefits through the following mechanisms of effects that are additional to the standard approach of evaluation: Agglomeration impacts: Improved accessibility and the decrease of transport costs may lead to firms to relocate closer to their intermediate suppliers to enjoy lower upstream (buying) and downstream (supplying) costs. The outcome of this process is intensified regional industrial clustering i.e. agglomeration. This may also facilitate specialisation of economic activities enabling increased efficiency from economies of scale. Further, the improved accessibility increases interaction between economic actors and better transfer of knowledge (=> productivity). The increased agglomeration – as well as the induced impacts – has effects on the prices in the region involved. Imperfect market impacts: CBA measures the value of time saving as a saving in gross labour cost assuming perfect competition. There are, however, price-cost margins caused by e.g. taxation and imperfect competition. The improved accessibility and trade between spatial markets. If there are persistent Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 9 The wider economic impacts of transport investments externalities in other markets that are affected by a transport scheme, a reduction or increase in output can diminish or augment the cost of these externalities. Labour supply and job relocation impacts: The improved accessibility affects labour markets in two ways. The higher commuting speed increases the labour accessibility from current locations, and attracts more jobs to locate in the region (to benefit from the agglomeration). According to Graham (2012), there is a strong theoretical case for extending conventional transport appraisal to cover wider economic impacts. Agglomeration economies form the largest component of these wider impacts, and there are differences between different kinds of transport projects in different regions. Therefore, the expansion of the transport project assessment to cover also the wider economic impacts in of significance in the decision-making. Agglomeration impacts can arise from small scheme as well as large schemes, and across different modes of investment. Further, the agglomeration benefits do not only arise in urbanised areas but any location may benefit from improvements in accessibility. 2.5 The spatial scope According to U.S. Department of Transportation (2006), there are three categories of economic impacts that should be taken into account while assessing economic benefits and costs of any infrastructure investments: Evaluation of national level first-order and second-order infrastructure efficiency benefits (e.g., reduced costs to goods transport operators and customers, relocation of logistic activities) Evaluation of national-level economic growth or productivity (e.g., GDP, exports) Evaluations of local and regional economic impacts for local and regional funding decisions (e.g., employment, Gross Regional Product, household income). The spatial scope is of great relevance in the assessment of economic impacts. At a national level, the changes in the economy will probably be seen as “internal redistributions”. At a regional level the changes may be perceived as “new activities”. The best level to capture impacts on economic development is the regional one. The size, structure and maturity of the economies and the transport system may vary greatly between the regions. The size and nature of the economic impacts varies, too. At a local level the spill over effects might be negative for some municipalities (for example an exit of a logistic centre due to the increased accessibility). On the other hand, there are municipalities that will win and receive new business via the agglomeration effects. Berechman (2009) points out that the economic development consequences in a region are further affected by spatial policies, too. The predicted economic development benefits of an investment may not fully transpire, if they are not accompanied by supporting land-use, housing and industrial policies. Figure 2. The role of supporting policies and decision-making in the causality of economic impacts. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 10 The wider economic impacts of transport investments 3 THE ECONOMIC DEVELOPMENT IMPACTS OF TRANSPORT INVESTMENTS 3.1 Impacts on economic growth and employment In addition to the direct and indirect effects of a transport investment and the operation of the improved system, the changes in transport environment may cause changes in the regional economic structures and shifts of economic activities between regions in the long run. The economic impacts of a transport investment are to a large extent based on the effects the investment has on accessibility. Faster train connections and increased supply and quality of transport services lower the costs of personal mobility and goods transport. This makes the trade of goods and services more profitable and the communication and interaction between people easier. Improved accessibility makes it possible for enterprises to enhance their geographical market areas (if the size of the market area depends on accessibility). This may increase competition in some locations but at the same time it makes it possible to deeper specialization which increases productivity. Accessibility improvements may also make the labour market areas larger because job centres can be reached from longer distances within reasonable time. This tends to increase commuting and it causes an improvement in the balance of labour demand and supply. The more polarised and specialised are the labour markets the more beneficial it is to enhance the labour market areas. The connection between accessibility and the regional economy is described in Figure 3. Figure 3. The process of impacts of accessibility improvements in a labour market area. As long as business transport is a factor in the production function of the firm faster and better quality business mobility (meetings etc.) has a direct effect on the cost and productivity of firms. Especially communication intensive firms, typically business services, can get competitiveness advantage and can enhance their business to neighbour regions. This supports the growth potential of firms in the region and may attract new firms to the Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 11 The wider economic impacts of transport investments region. This may have an impact on the demand for labour in the growing region and at the same time the supply of labour may increase due to the enhancement of the labour market area. Improvement of accessibility affects also the availability of various services and leisure mobility. Finally, the increase of the overall attractiveness of the region may lead to increases in-migration and population growth. As a whole, the improvement of accessibility may lead to growth by two different processes: widening of the functional labour market area and inward growth via jobs and population. However, the growth may take place, at least partly, at the cost of the firms in other regions. 3.2 Impacts on agglomeration, competition and labour supply Significant improvements in accessibility may cause a strong growth impulse for a region. This is especially possible if new connections are created or two or more transport modes are developed simultaneously (e.g. fast railway and highway) for a region with growth potential but previously underdeveloped transport system (World Bank 2009). In this case the accessibility improvements function as a catalyst for growth but in the long run the larger size makes it possible for the region to create agglomeration benefits for firms and households which may lead to further growth. Agglomeration benefits refer to positive externalities by which economic actors (firms and households) benefit from the closeness of other economic actors and of the increasing number of them and output growth created by them. Agglomeration benefits can be divided to localization benefits and urbanization benefits (e.g. Laakso & Loikkanen 2004). Localization benefits are based on the big size of a certain sector in the region. This makes it possible to exploit scale benefits in the input markets and logistics and supports the creation and distribution of innovations within the region. Urbanization benefits are based on the large size and diversification of the whole urban region. For firms urbanization means more competition, wider goods variation, better possibilities for specialization and cooperation. For households urbanization means a wider range of consumption possibilities. For labor markets large size of the urban region means better match of the demand for and supply of work. An important factor is the possibility to spreading of knowledge, innovations and technologies between the sectors. There is a lot of research evidence about the benefits to firms of the location near other firms of same industries or other industries. Agglomeration benefits the economic and social interaction between firms and their employees. This increases the probability of innovations and flow of knowledge between firms. In addition growing urban areas provide urbanization benefits, like the benefits of the large market area, well working labour markets and benefits from the diversification of industries. At the same time, agglomeration can increase price level and congestion (Laakso & Loikkanen 2004; Laakso & Moilanen 2011). Industries differ from each other with respect to the significance of the various dimensions of accessibility and the sensitivity to the changes in accessibility. According to Graham (2007; 2012) the productivity of firms increase with respect to the accessibility to a major economic centre but the elasticity varies between industries. The elasticity is higher in services than in manufacturing or construction. The highest effect 1 is in business services, finance, telecommunication and transport while in retail trade and accommodation and catering it is lower but still higher than in manufacturing. This explains to the large extent the fact that in Finland more than three quarters of the jobs of business services, finance and telecommunication are located in the 10 largest urban areas with the biggest local market for their services and best accessibility to other concentrations. (Laakso & Moilanen 2011) According to estimation results from UK the elasticity is 0,2–0,25 in most accessibility sensitive industries while it is below 0,1 in manufacturing and construction. 1 Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 12 The wider economic impacts of transport investments Figure 3 shows that the intensity of business communication between enterprises in different regions depends both on the characteristics of the transport system and on the industry structure and specialization. The density and efficiency of the transport system determines the accessibility of other regions. On the other hand, the industrial specialization based on competitiveness benefits of regions influence the potential of business communication between firms from different regions. In general, good accessibility of a region tends to attract firms with large market areas and much need for business communication in a large geographical area. Figure 4. The process of market area enhancement of firms Empirical studies from Jönköping region (Andersson et al 2005) are based on the framework of the impact of accessibility on the business contacts and enhancement of market areas. According to their estimation results the intensity of business trips increases extremely fast between the transport distances from 60 min (1h) to 180 min (3h). This means that the fastening of transport connection especially within this time frame increases significantly business communication based on face to face contacts. The SAMLOK model (Anderstig et al 2007) is based on the hypothesis that an improvement in the accessibility affects the labour market from two directions. First, the number of potential workers for which job concentrations are reasonably well accessible increases. Second, the number of potential jobs which are reasonably well accessible from housing locations of the residents who are active in labour market increases. In addition, there are other influencing factors, like the supply of housing and characteristics of residential areas and supply of jobs and the characteristics of job areas which influence the realization of the functional labour market area. The key concepts of the model are “market potential for jobs” and “market potential for labour”. The estimation results of Anderstig et al indicate that both aspects of market potential are deeply interlinked. According to the results based on regional panel data show that more than half of labour (population) change can be explained by the change of the market potential for jobs. 3.3 Impacts on land use and property values In urban areas transport investment may affect the land use and property values in the long run. The potential for the change concentrates first of all in the vicinity of new or improved transport links, like railway stations (railway investments), road junctions (road investments) and airports (airport investments) but the effects may also influence a wider area or the whole urban region if the investments acts as a catalyst for a process based on agglomeration effects. In the following we concentrate on the potential land use effects of railway investments improving person transport. The accessibility improvements caused by rail investments make the locations near the old or new railway stations more attractive for firms and households. Firms benefit from improved access by rail especially to other regions but also within the same region. This makes the business to business contacts easier improving the communication accessibility for firms. This is most important for communication intensive firms, like business services. It also improves the possibility for firms to get labor due to faster and better quality commuting from a Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 13 The wider economic impacts of transport investments larger area. The increased passenger flows in the surroundings of the stations make the location more attractive for retail trade and other services for households. The improved transport accessibility and changing locations of jobs and services may also make the locations more attractive for housing. These improvements of accessibility influence the rent level firms are ready to pay in the vicinity of improved accessibility. This leads to the increase of the rents and prices of old and new business premises. This is further capitalized in the land value of the area. These price changes create also pressure for the change of land use in two ways. First, the increased land value leads to demand for increasing density in the area. Second, the industrial structure in the area tends to change. The old activities, like manufacturing and storage, tend to move to new locations while they are replaced by the industries benefiting from improved accessibility, like business services, retail trade and other household services. The increased level of land value and the changed land value distribution creates pressure for planning. The requirement for higher land efficiency (higher buildings and less vacant space) increases. In addition, the area where construction is profitable becomes larger. However, planning rules restrict the realization of the land use changes. There may be political reasons to restrict the construction efficiency and the access of new land use in the area. Old buildings may be protected. The citizen or business community may oppose the land use changes. The land ownership may restrict or postpone the changes. These restrictions may lead to the realization of the second or third best alternatives compared with the market based land use. It must be pointed out that land use changes as a consequence of a transport investment typically take years, often tens of years. Are the land value changes caused by transport investments a zero sum game at regional level? The long run land use changes as a consequence of a transport investment are at least partly realized at the cost of other locations in the region. When the demand for land use in one location increases it normally decreases, at least marginally, in other locations, respectively. However, it is not a zero sum game if the land use of the region becomes more effective increasing the productivity of firms benefitting the land use changes. Increasing productivity raises also the capability of firms to pay rent and consequently, the total land value of the whole urban area increases as a consequence of taking advantage of the improved accessibility and increased efficiency of land use. 3.4 Potential for wider development of land use Bannister & Berechman (2000) point out that in developed countries where the quality of the transport infrastructure is basically already at a good level further investment in infrastructure will not on its own result in economic growth. Instead, transport infrastructure investments act as a complement to other underlying conditions which must also be met if further economic development is to take place. According to B&B there are three sets of necessary conditions: 1. Economic conditions: There must be possibility for positive economic externalities, such as agglomeration and labor market economies, the availability of a good quality labor force and underlying dynamics in the local economy. 2. Investment conditions that relate to the availability of funds for the investment, the scale of the investment and its location, the network effects and the actual timing of the investment. 3. Political and institutional conditions that are related to the broader policy environment within which transport decisions must be taken. To achieve economic development, complementary decisions and a facilitating environment must be in place; otherwise the impacts may be counterproductive. Included in this group of factors are the sources and methods of finance, the level of investment at different regional levels, the supporting legal, organizational and institutional policies and processes and various necessary complementary policy actions. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 14 The wider economic impacts of transport investments It must be noted that individually, the necessary conditions will have little or no impact on development. Even if two of the three conditions are met the effect will be limited. For example, if both the investment condition and political conditions are satisfied accessibility changes can be expected but economic growth impact will be limited because of lacking economic conditions. In this case relative attractiveness of locations affected may change but this is merely redistribution of existing activities rather than additional growth. Similarily, if only the investment and economic conditions are met, economic development effects may not follow because of the lack of supporting policies. A typical example is the land use policy that prevents firms and households from benefitting from the accessibility improvements by restricting the adaption of land use to changed conditions and maintaining the past land use. Another example is conflicting transport policies, e.g. separate and competing rail and road investments not supporting to each other. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 15 The wider economic impacts of transport investments 4 TOOLS FOR ECONOMIC DEVELOPMENT IMPACT ASSESSMENT 4.1 Transport project assessment (cost benefit analysis CBA) Cost benefit analysis (CBA) is generally used by governments and private sector to evaluate the desirability of a given policy. It is an analysis of the expected benefits and costs that aims to provide a basis for comparing alternatives within a given project, and for comparing different projects. CBA determines, whether an investment or decision is feasible. Theoretically, an accurate CBA identifies choices that increase welfare from a utilitarian perspective. The quality of the CBA depends heavily, among other things, on the valuation of present and future costs and benefits, on the definition of the reference alternative and, on the quality of relevant forecasts. Transport project assessment is the main instrument used in the planning and decision-making of transport investments. It follows the principles of practical cost benefit analysis. Project assessment includes an analytic estimation of the costs and benefits of a given project in monetary terms. The underlying idea is socio-economic efficiency – that is efficient allocation of scarce resources with the aim of maximising the welfare of society as a whole. The form and various details of project appraisal methodology vary from one country to another. There is no universal agreement on the extent to which costs and benefits should be disaggregated, which impacts should be included in the analysis and how they should be monetarily quantified. Both Finland and Sweden have used CBA-based project assessment in the transport sector for decades (see e.g. Eliasson 2013). All major national transport investments in both countries have been evaluated using a harmonised assessment framework. One of the main purposes of the harmonised guidelines is to make sure that transport investment suggestions from different parts of the countries concerning different modes of transport are comparable to a reasonable degree. Most or all major transport investments in Finland and in Sweden are financed through the State budget with no or relatively little regional funding. The methodological details within the framework (discount rate, unit values, calculation period, transport modelling, etc.) have been under continuous development. There are several differences between the project assessment methodologies in Finland and in Sweden. 2 The standard transport project assessment (or CBA) includes the estimates, valuation and analysis of the following components: – – – – – – – Investment costs and maintenance costs of the transport authority Generalised user costs (time, operating costs, convenience, etc.) in private travel, business travel and freight transport Traffic safety (the number and costs of fatalities, injuries and material damages) Producer surplus for transport operators Transport-related tax revenues (fuel tax, congestion tax, vat of tickets) Emissions (the amount and costs of CO2, NOx, SO2, particles) Noise (the magnitude and costs of noise exposure). There are several generally recognised weaknesses in transport Cost benefit analysis, namely (OECD 2002): – – – It favours some groups of users (bias resulting from CBA’s reliance on willingness-to-pay as a measure of opportunity costs) It fails to incorporate all of the external effects of projects (e.g. environmental impacts, social effects and wider economic effects) It fails to deal with distributional effects (e.g. impacts on deprived areas). The differences relevant in the context of wider economic benefits are in focus in Chapters 5.2 and 6.1 of this report. 2 Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 16 The wider economic impacts of transport investments There are two ways to respond to these weaknesses. The first is to expand the monetary valuation of impacts to incorporate more non-monetised impacts into the CBA methodology. The second is to incorporate the CBA analysis and results into a wider appraisal framework. These two approaches are complementary to each other. In Finland and in Sweden, transport project assessment includes also qualitative or sometimes quantitative estimation and analysis of a number of non-monetised impacts. The standard transport project assessment is needed to estimate and value the direct economic impacts of any transport investment. This knowledge may not be sufficient enough for the decision-making, as already discussed earlier in this report, but it is necessary for the estimation of the wider economic impacts. 4.2 Surveys, interviews and market studies 4.2.1 Interviews and surveys Interviews and surveys can give both qualitative and quantitative information about the expected economic development impacts of an investment. One method is to conduct interviews with local businesses and officials focusing on their views and plans regarding the transport investment in question. Survey-type methods used for economic impact analysis include (Sinha and Labi 2007): Expert interviews: Interviews of persons who have accumulated information and experience in business conditions in the region. Leaders and planners of local governments and researchers in the local universities, for example, may be useful contacts in this context. Business surveys: Surveying local business leaders, representatives of business organisations, for example, to collect data concerning the potential short-term effects of the proposed investment. Questionnaires may be delivered by Internet, by post or by interviews conducted in person or by telephone. Shopper origin-destination surveys: Surveying shoppers in the local communities to collect data of how the shopping and trip-making patterns could be affected by changes following the proposed investment. Corridor inventory methods: Surveying the users of a particular transport corridor by windshield surveys, vehicle origin-destination logs and business activity data collection. Case Järvenpää–Lahti motorway and Kerava–Lahti direct rail line in Finland The Järvenpää–Lahti motorway was opened to traffic in two phases during the years 1998-99. The Kerava–Lahti direct rail line was completed in the year 2006. Information on the traffic and socioeconomic impacts along this transport corridor was compiled and analysed by Meriläinen et. al. (2011). Statistical data and information from separate studies were completed by a questionnaire study for rail passengers and road users as well as by interviews in Lahti and Mäntsälä. According to the study, freight transport volumes on the new railway-line have been lower than expected. About half of rail passengers and one-fifth of road users indicated that the direct rail line increased their train travel. Regarding travellers between the Helsinki and Lahti regions, a share of almost 30 % of rail passengers indicated that the direct rail line affected their choice of residence or job location. Positive net migration from the Helsinki Metropolitan Area to Mäntsälä and also to the Lahti urban region has further accelerated after the completion of the direct rail line. New residential areas have been constructed in the vicinity of stations. Lahti station area has also developed into a specialised business district due to faster railway connections. Business development that requires cargo transport has totally relied on motorway connections. New competing business and logistics areas have emerged and existing areas have strengthened their position in interchange areas, although this development has not been very strong. Missing sidings to industrial areas prevent the development railway freight transport operations. New transport infrastructure has increased municipal expenses due to new construction, population growth and business development. Tax revenues will also increase, but surplus in municipal economy can only happen in the longer run. It is, however, difficult to separate the impacts of transport infrastructure development from the impacts of, for example, economic trends and steering mechanisms of municipal economy. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 17 The wider economic impacts of transport investments 4.2.2 Market studies Market studies are smaller-scale analyses typically related to impacts to local business within a region, not across regions. Market studies can help estimate the existing levels of supply and demand for the main business activities within the study area and then to estimate the expected changes with improved accessibility and reduced transport costs. Market studies may use various kinds of tools to collect and analyse information about the local economy. Interviews and surveys (see chapter 4.2.1) are useful. Gravity models are also used to predict effects on business activities. Gravity models are based on the assumption that changes in business activities are proportional to changes in accessibility (Sinha and Labi 2007): ∑ where Ai is the accessibility of location i, Dj is the number of business opportunities of a particular type at location j, tij is the generalised cost of travel from i to j and α is a calibrating factor that is typically between 1,5 and 2,0. 4.3 Comparative analysis – Case studies Comparative analysis or case studies are based on the assumption that impacts of a particular transport investment are to a large extent similar to the impacts of a same kind of investment in the past. This approach is applicable if the study area is relatively small and comparable case studies are available. Case studies are particularly useful in public communications and hearings to facilitate common understanding of the possible economic effects with concrete examples instead of complex economic analyses. The selection of the appropriate case studies, however, can be subjective and the argumentation for the project in question may be intentionally directed to a desired direction. (Sinha and Labi 2007.) A meta-analysis of a large number of case studies, on the other hand, can be very fruitful in drawing an overall view of the wider economic impacts. The key findings of the case of T-Pics (see case below) are in line with the generalised descriptions of the wider economic impacts presented in chapters 2 and 3 of this report. Case Transportation Project Impact Case Studies (T-PICS), USA T-PICS (2013) is a web-based viewing and analysis system for the case studies of wider economic impacts of road investments in the USA. The project was carried out under the second Strategic Highway Research Program (SHRP 2) of Transportation research board of the National academies. The economic impacts were studied by producing 100 before and after case studies of the impacts on economic and land development of highway and highway/intermodal infrastructure projects. A national database of case studies was created, and a web tool for viewing and using the findings. The case studies included statistical analysis of empirical data and identification of common themes from the qualitative interview reports. Key findings of the case studies were (TRB 2012): a) Transport infrastructure projects lead to multifaceted forms of economic development impact, which may include effects on employment, income, land use, property values, or building construction. b) The form of impact varies by the type and setting of the project. c) Impacts unfold over time, so no single project will necessarily show every type of impact at the same time. For that reason, multiple impact measures and an appropriate period of observation are needed to fully capture economic development impacts. d) Overall, 85% of the projects show evidence of positive economic impacts, while the rest show either no net impact or a small negative impact. However, the impacts were measured at different spatial scales depending on the size and breadth of the project, which varied from 2-mile, short-access roads to major in- Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 18 The wider economic impacts of transport investments e) f) g) h) 4.4 terstate highways spanning several hundred miles. Project cost and job growth impacts vary by project size, type, and location. Project location matters. Larger numbers of jobs are generated by projects in metropolitan settings than by those in rural settings. Rural projects tend to have lower costs and take less time to build than those in metropolitan settings, although job growth in rural areas also tends to take longer to emerge than in metropolitan areas. The economy and business climate of the project area are critical factors affecting the magnitude of project impacts. Projects in economically vibrant areas with complementary infrastructure and zoning regulations tend to generate more long-term jobs than do projects in areas without those features. Motivations for projects differ, and projects with a coordinated economic development effort (involving complementary policies) generally facilitate more long-term job growth than do projects that lack local supporting policies. Land-use–transport interaction simulation models Several simulation-based models have been developed and used to predict how the markets respond to changes in land-use and transport accessibility. These so called LUTI-models are a type of microeconomic simulation models that treat in detail the factors affecting the location decisions of firms and households. The models include explicit modelling of both transport and land-use. The basic interactions of the LUTI-modelling is as follows: Changing transport time or costs changes the accessibility to jobs, workers, and location of consumption, which in turn will over time affect the location of firms and households. The changes of land use patterns will have feedbacks on transport costs which in turn will affect location decisions. (Sinha and Labi 2007, Kernohan and Rognlien 2011.) LUTI-models typically take the region’s economic and demographic projections as fixed input and predict the redistribution of these following a transport investment. The LUTI-models are thus appropriate for understanding the dynamics of urban or regional economic impacts but do not take into account the impacts on economic growth. Economic multiplier – Input –output (IO) models 4.5 Input-Output models trace the flow of industries’ income and calculate how changes in one industry affect growth in the rest of the economy (Guide, 2006). According to Wallis (2009) correctly defined, IO models evaluate the wider economic effects as follow: Indirect production effects: re-spending by firms that receive income from the sale of commodities to firms undertaking the direct activities; Induced consumption effects: resulting from re-spending by households receiving income from employment in direct and indirect activities. The main outputs of analyses using IO models are changes in GDP/GSP (Gross Domestic Product and Gross State Product), employment and income. The results of IO models are typically reported for given years in the project construction period and the project operational period and can be of regional, multiregional, or national scope. IO results can be seen as short-run effects, because only the output effects are denoted. In the longer run also the price effect must be accounted for. While IO models have rather limited use for transportation impact analysis, these models are widely used to present the labour and income impacts of operating or expanding infrastructure investments. However, estimation of the impact of changes in costs or market access, which are the two key impacts of most of the infrastructure investments, cannot be obtained via IO models. The IO model is often chosen by policy makers due to its rather simple structure, comparing to other methods, and to its sometimes mandatory status. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 19 The wider economic impacts of transport investments 4.6 An overview of computable general equilibrium (CGE) models Computable General Equilibrium models are used in Europe and the world as models of the economy for large regions and nations. CGE models usually have a spatial component, tracking transportation connections and trade among regions, and an industry component, tracking the cost of freight transportation by commodity group between regions. The models estimate the economic impact of infrastructure projects and policies by calculating their impact on interregional infrastructure cost, value of capital stock, effective labour supply, and overall factor productivity. This may include effects of changing travel times, reliability, accident rates, congestion levels, and operating costs. In the end, the macroeconomic response is estimated as changes in industry growth and related to it changes in commodity trade between regions (NCFRP, 2011). Using CGE models is one method of dealing with the limitations of the IO models. CGE models represent a microand macro-economic approach to analysing transport infrastructure. They often use intermediate demand and other data from the I-O tables. The main data source for the Social Accounting Matrices (SAMs) is national and regional economic accounts. CGE models use econometric estimates for the parameters and elasticity values. CGE models allow for the resource constraints on availability of labour, capital and land. Also the structures for private consumption and government spending can be added to the model. In fact, the CGE models include not only the influence of the changes in the output, but also the price impacts coming from changes in relative prices. The models can thus be used in both short and long run scenarios. For these reasons, CGE models deal better with economic interactions and represent more sophisticated modelling approach than IO models. CGE models use wide quantitative information relating to labour market data, detailed commodity flows, and national and regional accounts data. The economy is presented as a system of flows of goods and services between sectors, including produced commodities and primary factor services (labour, capital, land). Typically, the decision makers include the household, several industry sectors, government and the foreign sector. It is the ability to incorporate constraints (i.e. behavioural assumptions) into modelling that favour CGE models among the other assessment methods. The behavioural assumptions indicate how linked sectors respond to given shocks (changes in the economic environment) and how these shocks are transferred to other sectors. CGE models make particular assumptions of the behaviour of consumers, producers and investors using established micro- and macro-economic theories, well tested methods of econometrics and reliable algorithms from applied mathematics. Similarly to IO models, results for CGE models are usually reported for given years in the project construction and operational period (Wallis, 2009). The impacts of infrastructure investments measured by CGE models include usually the effects on GDP/GSP, employment, investments, trade (imports and exports), consumption, wages and taxes, which makes CGE models particularly attractive for decision makers. According to Sue Wing et al. (2007) recent applications of CGE have made advances by presenting travel time as a negative impact on the utility and production functions of households and firms, and treating transport supply and demand interactively within the models. As is the case of all evaluation methods, CGE has its drawbacks that are presented in Table 1. Among CGE models one can distinguish comparative-static, dynamic and spatial models; all three are possible to apply for infrastructure investment assessment, but are not equally adequate for it. Comparative-static CGE model is the most commonly used CGE model worldwide. It does not have a time dimension and it omits inter-temporal relationships between endogenous variables. It is often criticised for its incapability of analysing the impacts of transport investments that have a ‘long tail’ with respect to construction expenditures and flow-on impacts within the local area. The infrastructure investment will therefore affect local and global economies for many years, as local development gradually takes advantage of the new infrastructure facilities (Docwra & West, 1999). Dynamic CGE model in a contrast, explicitly trace each variable through time. For example, a dynamic CGE model can link changes in the capital stock in one period with past levels of investment and savings (using specified Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 20 The wider economic impacts of transport investments elasticity measures) where all of these are defined as endogenous variables (Docwra & West, 1999). Labour dynamics are often included, where the change of population due to the infrastructure investment is estimated. Dynamic CGE model is said to be more realistic, but at the same time more difficult to construct and solve. Spatial CGE model (SCGE) is either a comparative-static or a dynamic model of interregional trade and location based in microeconomics, using utility and production functions with substitution between inputs. SCGE models have a sophisticated theoretical foundation and non-linear, rather complex mathematics enabling to model (dis)economies of scale, external economies of spatial clusters of activity (Ivanova et al., 2007). According to Williams (et al., 2002) SCGE models can successfully represent the relationship between economic development and transport demand. By taking into account both technological change and the recycling of revenues from infrastructure charging policies through the economy, SCGE models provide a constant framework for economic responses. Sundberg (2009) lists, as one of the reasons of increased used of SCGE, the increased demand for tools that may assist in the assessment of policies, especially for the assessment of the economic impacts of infrastructure investments and other transport related policies. One example of SCGE model successfully used in infrastructure investment assessment is CGEurope developed by Johannes Bröcker. Its main goal is to quantify regional welfare effects of transport related and financial-economic policies (Tavasszy, 2007). Table 1. Comparison of IO and CGE models (partially based on MOTOS 2007 and Wallis 2009) Model IO Major output Advantages Disadvantages/Limits I-O vs. CGE Range of macroeconomic variables; employment, income and GDP/GSP Provides measure of macro-economic impacts of interest to policy makers Fixed Price equilibrium Complexity: medium/large Simple technique for common decision maker May be more practical for modelling small regions than CGE CGE Range of macroeconomic variables; relative prices, employment, consumption, investment, taxes, exports and imports, industry output impacts and GDP/GSP Provides measure of macro-economic impacts of interest to policy makers Non-linear behaviour, flexible structure Flexible description of the supply and demand side of the economy Linear Leontief structure High data requirements Tend to exaggerate economic benefits Does not allow for constraints on various factors, resulting in overestimate of impacts No allowance for environmental and some accident externalities, partial allowance for non-work travel time Does not provide clear and direct measure of net project benefits (costs) Usually of comparative-static character High data requirements Determination of parameter and elasticity values Usually no allowance for environmental and some accident externalities, partial allowance for nonwork travel time Highly complex, expensive and data required process Modelling approach is not transparent and open (black box) Questionable assumptions and relationships may be hidden Complexity: Large IO can be used as a base for CGE Allowance for constraints provides more realistic modelling of outputs than IO and more comprehensive approach to the estimation of regional economic effects Unlike IO; specific assumptions about the behaviour of consumers, producers and investors Selected CGE and other models dealing with the economic impacts of infrastructure investments from Finland, Sweden, Norway, Poland and Germany are presented in an appendix of this report. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 21 The wider economic impacts of transport investments 4.7 The RegFinDyn model Regional CGE RegFinDyn3 model is well designed for infrastructure impacts estimations and it has many advantages over the older, linear calculation methods such as IO. RegFinDyn model includes and takes into account a large number of economic factors, among others: constraints on total availability of factors of production (labour, capital, land) sectorial production and their demand for factors of production dependencies of producer sectors in expenditures and sales effects from differences in business structure between the regions transport services presented as three sectors (Rail, Road, Other) transport margins and productivity changes substitution guided by relative prices between Rail and Road transportation transportation infrastructure investments operation phase of transportation infrastructure investments, households’, businesses’ and public sector’s non-linear decision-making investors’ cautious profit-seeking behaviour time dimension capital stock accumulation via net investments guided by the changes in the rate of return to capital wage differences between the regions regional population changes and demographics money flows into-and out from the region through domestic and international trade. RegFinDyn is a dynamic version of the comparative-static RegFin model; influenced by famous Australian ORANI, MONASH, MMRF and TERM models (Wittwer 2012). The family of RegFin models has been developed and used since 1998. The model is built on a neo-classical economic theory (Figure 2). Figure 5. RegFinDyn model’s theory 3 The basic CGE description is presented in publications Törmä (2008) and Rutherford and Törmä (2010). The detailed description of the model can be found in Törmä and Zawalinska (2010, 2011) and with emphasis on transport impact in Metsäranta (et al., 2012). See also http://www.helsinki.fi/ruralia/research/regfin.htm Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 22 The wider economic impacts of transport investments In RegFinDyn, like in all CGE models, the key principle is that in the regional economy ‘everything affects everything’. For this reason, no part of the economy can be analysed separately. Figure 6. Interdependencies in the RegFinDyn model Relative prices are the engines of economic adaptation. In the change of economic conditions, the relative prices changes guide the economy towards new equilibrium. In RegFinDyn the relative prices and quantities can find their correct new values only when all markets in the economy are in equilibrium, so supply is equal to demand. In this case the whole economy is said to be in general equilibrium. In some model versions labour markets are not in equilibrium due to existing unemployment. RegFinDyn model takes into account all money flows into and out from the analysed region, so calculations are done on a net basis. Figure 7. Money flows into and out from the region Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 23 The wider economic impacts of transport investments As for every dynamic model, the additional feature of RegFinDyn over the RegFin model is the time dimension. Economic impacts are calculated year by year for a specific time period, for example years 2007-2020. Dynamic calculations require setting up the baseline that is the image of the future without the considered changes. With the calculation over the time, the model shows the dynamics through the interdependence between sectorial investments and capital stocks. Another distinguish feature of RegFinDyn among other CGE models is the population module. The factors affecting the regional population in the model are birth and death rates and domestic and foreign net migration (inminus out- migration). The model produces the population structure by gender in 1-year-cohorts up to 100 years of age. The importance of the population module lies in its link to the labour force, citizens’ well-being as well as the high interest of public sector in anticipating demographic changes causing changes in provision of public services. Agglomeration (see Chapter 3.2) is measured in RegFinDyn through each region’s share of national labour costs compared to previous year. Thus, we use the share of regional labour cost as a simple proxy for effective density. Regions increasing their share of labour use enjoy an additional increase in productivity. However, agglomeration impacts are assumed to vary by industry according to elasticity estimates reported by Kernohan and Rognlien (2011). The productivity gain from agglomeration is largest in knowledge-intensive services like financing (elasticity 0,08–0,09) and smallest in primary production (elasticity 0,03–0,04). In transport-related services the elasticity is 0,057. Integrated CGE – transport models 4.8 Integrated models are the promising yet expensive and complicated methods of estimating economic impacts of infrastructure investments. Linking economic modelling (CGE) with traditional transport modelling aims in exploration of the advantages of the two approaches. However, there are significant complications due to the many inherent differences in the methodologies, but also the differences between ‘language’ of the engineers and economists. CGE models operate on data from a normal of most recent year and on an aggregated scale, while traditional transport models are based on cross-sectional analyses, often applying a detailed spatial resolution to precisely describe route choice. CGE models estimate monetary flows by economic sectors based on, e.g., CPA classification, while transport models use commodity classification, both methods are difficult to combine. Integrated models are still rather scarce. Among few European cases are (See: MOTOS, 2007, Monzón et al., 2010, Vold et al., 2002, 2007): 4.9 The national freight models in Norway: SCGE model of Norwegian economy (PINGO) and the network model for freight transport within Norway and between Norway and other countries (NEMO); TRANS-TOOLS: European transport network model including simplified CGEurope model. Conclusions The standard transport project assessment (CBA) is the basic tool to estimate the direct economic impacts of a transport investment. This is necessary but not sufficient for the estimation of the wider economic impacts. There is a growing need to know more about the wider economic impacts regarding individual infrastructure projects and also more generally concerning transport policies. There are several analytical techniques for the estimation of these economic development impacts, varying from simple case studies and surveys to complex economic simulation modelling. However, a single analytical tool that is equally useful to all of the information needs in the planning and decision making, is impossible to name. The general rule for the selection of the analytical tool is to match the tool to the purpose and level of desired sophistication of the analysis – and the given resources (NCFRP 2011, Sinha and Labi 2007). Considering a solid analysis of the wider economic development impacts, one can name the necessary core features of a capable assessment tool (US DoT 2006, Williams et. al. 2002, De Jong and Gunn 2004): Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 24 The wider economic impacts of transport investments an analysis of how changes in transport related costs and access factors affect the growth/decline of various productive activities within an economy the indicators need to be structured and aggregated in a way that allow for reporting of the economic impacts from different perspectives: by affected parties (e.g., households, private or public sector), by geographic incidence (local, regional, national) or by economic sectors (e.g., transportation versus nontransportation sectors) sufficient sectorial detail in the commodity types (from 15 to 100+) with an explicit representation of the transport sector fast and straightforward policy analysis tool and interlinked modules. Focus on the quantitative assessment of wider economic effects narrows the choice to three most common methods: Input-Output models (IO), Computable General Equilibrium models (CGE) and Integrated models (transport models with CGE). Both IO and CGE models measure economic impacts rather than economic efficiency or net benefits, which are measured by CBA. The RegFinDyn model can be considered a powerful tool to be used in the assessment of economic impacts of infrastructure investments. For the purposes of the BGLC project, the authors of the RegFinDyn have built its twin model called RegSweDyn for Sweden. RegSweDyn is based on the same modelling structure as its Finnish equivalent. It is adjusted to the Swedish criteria and available data. Both models cover the Bothnian corridor by calculating the impacts separately for each country, Finland and Sweden. The use of the actual RegFinDyn or RegSweDyn-models is, however, not straightforward and fast but requires specific skills and knowledge. This project aims to tackle the contradicting needs for a complex CGE-modelling and the fastness and straightforwardness of the analysis: A spreadsheet tool with a streamlined interface that uses the results of a large number of previously made CGE-model simulations. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 25 The wider economic impacts of transport investments 5 A PLANNINGTOOL FOR ECONOMIC IMPACT ASSESSMENT 5.1 Introduction to the methodology The guidelines for the development and design of a planning tool to assess the wider economic impacts of infrastructure investments have been set as follows: 1) 2) 3) 4) 5) The input parameters set by the user can be derived form a standard project assessment Dynamic, multi-sector and inter-regional CGE simulation will be needed to determine the economic development impacts The tool must be applicable to rail investments within the area of Bothnian corridor in Finland and in Sweden The tool must consider the development impacts from the construction spending and from the benefits when in use The results must focus on the key indicators of economic development considering the spatial distribution. The development of the tool led to twin tools that were named WebRailFin and WebRailSwe – describing the purpose of the tools to estimate the wider economic benefits of rail investments in Finland and Sweden, respectively. An overview of the tools is presented in Figure 5 and discussed below. Figure 8. An overview of the WebRailFin and WebRailSwe assessment tools. The tools are made for a quantitative approximation of the wider economic impacts of large rail investments in the national areas of Sweden or Finland. The wider economic impacts calculated by this tool are supplementary to the results of a standard project assessment (CBA). Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 26 The wider economic impacts of transport investments The tools use generalised results of RegFinDyn and RegSweDyn CGE-modelling. The Swedish tool covers 8 national areas (Nuts 2) and is based on a total of 64 scenarios of investment costs and 64 scenarios of benefits (cost savings). The Finnish tool covers 4 national areas (Nuts 2) and is based on a total of 160 scenarios of investment cost simulations and 40 scenarios of benefits (cost savings). The results of the CGE-modelling are stored in the planning tool to be used in the estimation of the wider economic impacts caused by the shocks of investment and cost savings of the investment project in question. The regional economic effects of rail investments can then be evaluated for both the investment and operation period. Main interest is on the results related to economic growth and labour-markets. 5.2 5.2.1 Required background information and preparatory work The basic calculation The user must insert the relevant input parameters into the assessment tool. The necessary information can be found in the project assessment (CBA) of the investment project in question. If the user wants to assess a project that’s planning is on a very preliminary stage, the input parameters have to be defined based on user’s own expertise based on e.g. project assessments of previous projects. The national area in focus Choose the national area (Nuts 2) in focus. The tool calculates the results for only one area at one time. The year of the price-level in the assessment Insert the price-level used in the cost benefit analysis of the investment. The basic rule in CBA is that the investment cost and the monetised benefits are at the same price level. The investment cost Insert the investment cost used in the project assessment. The amount of actual spending during the construction will usually be more than this, but the important sum here is the difference between the investment and the reference alternative (that is assumed to be part of the base scenario). Our tool assumes that the investment is carried out in equal shares during the investment phase. Another assumption is that the state finances the investment by raising VAT during 20 years' time, and thereafter lowers VAT to its original level. This assumption is made to avoid giving a too optimistic view on the infrastructure investments. Unfunded "helicopter money" financing will always look beneficial to economy in this kind of models. The first year of the construction work Insert the year when the construction works of the project will start. In this version of the tool, the latest possible year to start the construction in the tool is 2020, so that the model has enough years in the base run for calculation of the impacts which accumulate during many years before reaching the maximum effect. However, if the user is only interested in relative results (% change from the baseline), one can apply time frames that go beyond year 2040, as then baseline values are not needed in the calculus of the absolute effects. Length of the investment period Insert the duration of the construction period in years. The maximum length of the construction period in this version of the tool is 10 years. The first year of user benefits Insert the first full year of operation after the construction. Direct economic impacts from the CBA per year Insert the annual (per one year) benefits from as positive values (+) and disbenefits as negative values (-). The annual value of economic benefits should be from first years of operation i.e. excluding the impact of traffic growth. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 27 The wider economic impacts of transport investments Infrastructure maintenance cost savings Maintenance of railways: Directly from the project assessment. Maintenance of roads: Directly from the project assessment. Replacement investments in railways: Directly from the project assessment. Benefits for the goods transport operators Operating cost savings and time-cost savings: Directly from the project assessment. Benefits for the passenger transport operators Increase of ticket revenues: Directly from the project assessment. Operating cost savings: Directly from the project assessment. User benefits Time savings for business trips: Only the share of business trips must be considered here taken also into account the higher unit cost of time savings. One important point in costing of the time savings is that they should be valued in terms of labour costs to employer, not as net wages to employees. External benefits Accident cost savings regarding the loss of production: The share of production loss is approximately 3 % - 5 % of the total monetary value of accidents involving personal injuries. The loss of production should be valued in terms of labour costs, not as net wages to employees. The reduction of wear and tear of roads: Directly from the project assessment. Figure 9. The view of entering user-defined parameters into the WebRailSwe -tool. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 28 The wider economic impacts of transport investments 5.2.2 Additional options There are additional options in the following parameters: The regional distribution of user or producer benefits and costs in the worksheet "Options of productivity shock". This distribution matrix determines the final size of the shock that is allocated to the region where the investment is taking place. The exchange rate SEK/Euro can be updated or adjusted. The currency in the CGE-modelling is Euro. The changing of the exchange rate changes the absolute size of the investment and productivity shocks that in turn change the results of the calculation. The inflation rate. In this version on the tool, historical data on inflation is coupled with an assumption of low, constant inflation rate. This should be updated with the newest data once new information becomes available. The regional distribution of the benefits has a considerable effect on the results of the calculation. Sensitivity analyses are recommended. The user can choose the ready-made assumptions or make own assumptions. The ready-made distributions (Table 2) are based on the following assumptions: Table 2. 5.3 shock to public consumption (changes in maintenance costs and replacement investments) is allocated completely to the area in question shock to rail operators (changes in operating costs) is allocated to areas according to the distribution of value added of railway traffic in the Base scenario shock to consumer preferences (changes in ticket revenues) is allocated to areas according to the distribution of private consumption of railway traffic in the Base scenario shock to labour productivity (changes in time costs) is allocated to areas according to the distribution of labour costs in the Base scenario shock to construction markets (investment costs) is allocated completely to the area in question. The assumed regional distributions of the productivity shocks. The results The tool calculates the absolute and relative values of the wider economic impacts in the area in focus. The impacts of the investment shock are calculated on a national level, too. The selected economic indicators are: Real GDP is the standard measure of the real value (not ‘nominal’ market value) of final goods and services produced by the area of the country during one year. Real GDP takes into account the price changes due to inflation and shows the change in the volume of production, i.e. changes apart from price changes. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 29 The wider economic impacts of transport investments Household consumption expenditure is typically the largest component of final uses of GDP. It is an indicator of demand in the consumption markets, and it can be used as proxy measure for welfare of the households. Employment change is an indicator of the volume of the labour markets. Is can be thought to measure mainly demand side changes, as long as there are unemployed in the labour market, or labour supply is not changing much. Population change, apart from being a size measure for the society, is also a closely related to the supply side of the labour markets. Population is a stock variable and thus the cumulative changes are not reported. The results shown in the tool are based on averaging the results from several model runs by a CGE-model RegSweDyn built specifically for this purpose. Therefore, changes in the details of an investment project cannot be studied with this tool. The results simply apply for an average-type large rail investment project. In the construction of the tool, Umeå–Luleå railway was assumed to represent a typical major rail investment. The construction period and the use phases are thought to follow each other chronologically. However, it is possible to make other assumptions on this issue, as investment and use phase calculations are conducted separately. The tool is able to calculate the absolute values of results until the year 2040 that is the last year of the Base scenario. However, relative impacts of the productivity shock even beyond 2040 may be found on the detailed results, too. 5.4 The CGE-modelling to create the result data banks for the planning tools 5.4.1 Data sources and dimensions The two models RegFinDyn and RegSweDyn have the same structural design built on national and regional data from the respective country. The main data sources used in this case were the national and regional accounts of Statistics Finland (Tilastokeskus) and Statistics Sweden (Statistiska centralbyrån). National Supply and Use tables are available from both countries. They provide picture of the supply of goods and services by domestic production and imports and the use of goods and services for intermediate consumption and final use (private and public consumption, gross fixed capital formation, exports). The Use table also shows how the components of value added (compensation to employees, other net taxes on production, consumption of fixed capital, net operating surplus) are generated by industries in the domestic economy (Eurostat, 2008). The databases for the two CGE models were created in two stages (Figure 6). 1. 2. National data was used to create national databases. The national Supply and Use tables are useful, since they give detailed information on the production processes, the interdependencies in production, the use of goods and services and formation of income generated in production. Automated routines were used to check the quality, balance and matching of the tables. One important test is making sure that supply equals demand for all sectors. After checking, corrections and balancing, the Supply and Use tables provide coherent data linking industries, products and sectors. National Social Accounting Matrices or SAMs, together with corresponding national CGE databases are created in this process. National databases are regionalised by using additional data from regional level. This requires sector and region specific data in matrix format for instance on production, investment, labour income, and population shares. Automated routines were used to create the regional SAMs and the corresponding CGE databases. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 30 The wider economic impacts of transport investments Figure 10. The process of creating the CGE-database for the tool. The national Supply and Use tables have 59 sectors representing primary production, manufacturing and services. Since we need aforementioned shares in regionalisation, the availability of regional data becomes important. Shares are received from regional statistics, and their region and sector dimensions determine the corresponding dimensions of the regional CGE databases. Regional accounts of Finland cover 19 regions and 30 sectors at NUTS 3 (maakunta) level. At NUTS 2 (suuralue) level the dimension is 5 regions and 18 sectors. In Sweden, regional accounts cover only 3 sectors at NUTS 3 (län) level, which is too little for the planning tool. The availability of data increases at NUTS 2 (riksåmroden) level into 8 regions and 15 sectors. In all regional data sources transportation and storage is a separate sector but an aggregate. We chose to create regional CGE database for Finland both at the NUTS 3 and NUTS 2 level. For Sweden, this was possible only for NUTS 2 level. The “engine” of the planning tool was based on NUTS 2 databases to gain comparability between the countries. The names of the regions are the following. Table 3. Regions of the CGE models RegFinDyn and RegSweDyn Finland South Finland West Finland East Finland North Finland The Åland islands 5 NUTS 2 (suuralue) regions Sweden Stockholm East Middle Sweden South Sweden North Middle Sweden Middle Norrland Upper Norrland Småland and the islands West Sweden 8 NUTS 2 (riksområde) regions The sector transport and storage was necessary to disaggregate 4 in order to study how rail transportation services react to railroad investments. We managed to distinguish between seven sub-sectors for both countries: rail transport, road transport, water transport, air transport, warehousing, transport services, and post and courier services. There are altogether 35 sectors in the Finnish, and 20 sectors in the Swedish model (Appendix 2). The supply and demand structures were taken for Finland from the most detailed national Supply and Use tables covering 172 sectors. For Sweden there was a special report on the subject available (Bohlin, Levin and Sayeed, 2013). 4 Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 31 The wider economic impacts of transport investments 5.4.2 Population dynamics It is possible that the rail investment affects population and its demographics in the target region. There may not be enough labour to cover the increased demand during the investment phase. A specific population module was included into the models to handle this chain of impacts. Figure 11. Change of population in the CGE models. The analysis begins from year T, for instance 2012 for which we have realised population statistics. The goal is to estimate the population for the next years, for instance 2013 (T + 1) – 2030 by using certain explanatory variables: births, deaths, domestic and foreign net migration (in migration minus out migration). The population module keeps record on the population structure according to age cohorts up to 95 years of age. The module follows the life of a person: she/he is born, gets older every year, goes to school, starts working, is retired and finally dies. The model evaluates the size of the regional population till the end of the scenarios, year 2040. The initial fertility and mortality rates are known from the statistics and their development over the future years follow the assumptions made by the national statistical offices. Migration is dependent on unemployment differential between the region and nation. The statistically estimated value of net migration elasticity was 0,05. This means that if the unemployment differential changes in favour of the region by one percentage point, then net migration to this region increases by 0,05 percentage points. The consequence is that a big part of the change in employment is covered by migration within the region, commuting or by changed participation rate. Out-migration is assumed to be a constant share of population, but this share is adjusted to balance domestic net migration. This is because net migration must be zero over the regions by definition. The population module directs foreign net migration mostly to the regions where there are bigger towns and higher growth rate of population. The model, however, does not keep record on the ethnic background of the population structure. The model foresees that the total supply of labour in the region changes as the age structure changes since every age cohort has its own labour market participation rate, which is assumed to be constant with respect to age and gender (base run) or change marginally along with the wage rate changes (policy run). The population statistics for the base year as well as parameters for births, deaths and migration are available from Statistics Finland and Sweden for the base year. Additional, but not complete information on the components of the national forecasts are freely available. The fact that net migration has been modelled as an endogenous variable means that the population prediction will not be totally according to official projections. The model calculates for every year of the scenario changes in population by age cohort and gender. The results can be aggregated according to need, for instance the change of population in working age (16–64). Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 32 The wider economic impacts of transport investments 6 DEMONSTRATION OF THE TOOL 6.1 Exploring the wider economic impacts of a major rail investment 6.1.1 Norrbotniabanan In Sweden a major rail investment within the Bothnian corridor is The North Bothnia Line (Norrbotniabanan), a new railway between Umeå and Luleå (270 km). The estimated investment cost is 21 725 million SEK (2 508 million euros). According to the project assessment (Banverket 2009), the major benefits of the investment are time savings (net present value 8 639 million SEK), transport cost savings (4 098 million SEK) and increased ticket revenues for rail operators (2 397 million SEK). The total net present value of the investment is 208 million SEK meaning that the investment is feasible with a very small margin. The SamLok-calculations (see also Chapter 3.2) of the Norrbotniabanan show, that the increased accessibility increases the number of employees (+0,0..+0,3 %) in the region and on the total income of the households (+650 million SEK per year ten years after opening). On the other hand, there are negative impacts on the built and natural environment. The overall conclusion of the project assessment is that the positive margin of the benefits is stable. As regards the non-monetised impacts, the positive impacts on the regional economy are considered more valuable than the negative impacts on the environment. (Banverket 2009.) Table 4. A summary of the input parameters for WebRailSwe in the case of Norrbotniabanan. The input parameters entered by the user Source of information; calculations by the user 1. The national area in focus SE33 2. The year of the price-level in the assessment 2006 3. The investment cost (million SEK) 4. 5. 6. 7. The first year of the construction work (max 2020) Length of the investment period, years (max 10) The year of annual impacts from the CBA Direct economic impacts from the CBA per year Maintenance of railways (million SEK) Maintenance of roads (million SEK) Replacement investments in railways Operating cost savings and time-cost savings (million SEK) Increase of ticket revenues (million SEK) Operating cost savings (million SEK) 21 000 The investment cost here must be the same as in the cost-benefit calculation (the difference between the investment alternative UA and the reference alternative JA) 2010 9 2020 -13,0 38,0 69,0 257 140,0 -92 Time savings for business trips (million SEK) 148 Accident cost savings regarding the loss of production (million SEK) 1,6 The reduction of wear and tear of roads The productivity and investment are directed to Upper Norrland area 8 The values of maintenance cost savings, benefits for the transport operators are directly from the costbenefit calculus of the project. The budget effects (changes of tax revenues) are omitted here since they are endogenous parameters in the calculation. This value has been derived from the net present value (8 639 million SEK) by using information presented in the background reports and ASEKguidance: The share of business travel on this railway is 38 % of all travel, the value of business travel time is 274 crowns/h, the discount rate is 4 %, the annual growth of travel is 1,7 % and the annual increase of the value of time is 1,2 %. This value has been derived from the annual value (31 million SEK) by using information presented in the ASEK-guidance: The share of production loss of the accident costs is 5 %. Directly from the cost-benefit calculus of the project. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 33 The wider economic impacts of transport investments The main results of the calculation of the wider economic impacts are presented in the Figures 12 and 13 below: The investment spending leads to considerable positive economic impacts in the area of Upper Norrland. The investment shock increases the economic growth in Upper Norrland by 1–2 % compared with the base scenario. The increase of household consumption is 1–3 %. The investment increases employment and population in the area, too. According to the base scenario, however, the demand and supply of labour in the area will continue to decrease. The direct economic benefits of the investment cause an annually growing positive impact on economic growth, employment and population. These impacts are relatively small (0,002 % … 0,12 %) compared with the baseline. From a national perspective, the investment has negative economic impacts because the investment in Upper Norrland means other opportunities of investments forgone. In the tool, the national opportunity cost of an investment is measured by increasing the value added tax to finance the investment, which dents the profitability of all the economic activities. What is the added value of this information compared with the original CBA? Firstly, the economic implications of the very large sum of investment spending are not considered in the traditional project assessment. According to the WebRailSwe calculation, the government spending increases the economic growth in the Upper Norrland area more than the actual spending is. On the other hand, the negative impacts of financing the investment become visible on a national level. Secondly, the WebRailSwe calculation show the wider economic impacts following the direct cost savings of the investment considerable smaller than in the SamLok-calculation referred in the project assessment. The impacts are, however, positive and thus confirm the conclusions made in the project assessment. Figure 12. Summary of results extracted from the WebRailSwe case calculation of Norrbotniabanan. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 34 Figure 13. Figures of results extracted from the WebRailSwe case calculation of Norrbotniabanan. 6.1.2 Seinäjoki–Oulu In Finland a major rail investment within the Bothnian corridor is the Seinäjoki–Oulu -railway project (335 km). The section between Seinäjoki and Oulu is one of Finland's busiest single-track lines. The estimated investment cost is 860 million EUR. According to the project assessment (Ratahallintokeskus 2006), the major benefits of the investment are savings in the accident and environmental costs due to increased rail travel (net present value 290 million EUR) and consumer surplus of the rail operator (270 million EUR). The benefit cost ratio of the investment was 1,64 in the 2006 assessment when the cost estimate was 500 million EUR instead of current 860 million EUR. Considering the increase of the investment cost, the project is still feasible (B/C > 1). Table 5. A summary of the input parameters for WebRailFin in the case of Seinäjoki–Oulu. The input parameters entered by the user Source of information; calculations by the user 1. The national area in focus The investment spending is directed to Western Finland area (40 %) and Northern Finland area (60 %). The share of benefits is directed to Eastern Finland (40 %), Northern Finland (40 %) and other parts of Finland (20 %). 2. 3. 4. 5. 6. 7. The year of the price-level in the assessment The investment cost (million euro) The first year of the construction work (max 2020) Length of the investment period, years (max 10) The year of annual impacts from the CBA Direct economic impacts from the CBA per year Maintenance of railways (million euro) Maintenance of roads (million euro) Replacement investments in railways (million euro) Operating cost savings and time-cost savings (million euro) Increase of ticket revenues (million euro) Operating cost savings (million euro) FI19, FI20 2006 860 2008 10 2018 -0,34 .. .. 11,33 19,34 -2,68 Time savings for business trips (million euro) 6,43 Accident cost savings regarding the loss of production (million euro) 0,25 The reduction of wear and tear of roads (million euro) 0,28 The values of maintenance cost savings, benefits for the transport operators are directly from the costbenefit calculus of the project. The budget effects (changes of tax revenues) are omitted here since they are endogenous parameters in the calculation. This value has been derived from the annual value of time savings (12,16 million euro) by using information presented in the background reports and appraisal guidance: The share of business travel on this railway is 24 % of all travel, the value of business travel time is 25,60 euro/h and that of other travel 7,22 euro/h (2005). This value has been derived from the annual value (8,4 million euro) by assuming the share of production loss of the accident costs to be 3 %. Directly from the cost-benefit calculus of the project. The main results of the calculation of the wider economic impacts are presented in the Figures 13, 14 and 15 below: The investment spending leads to positive economic impacts in the areas of Northern Finland and Western Finland. The investment shock increases the economic growth in Northern Finland by 0,2– 0,6 % compared with the base scenario. The increase of household consumption is 0,2–1,0 %. The investment increases employment and population in the area, too. In Western Finland, the impact on economic growth is 0,05–0,25 % compared with the base scenario. The increase of household consumption is 0,05–0,35 %. The investment population in the area increases. There is however negative impacts in terms of decreasing employment. This happens because in the tool the investment is financed by increasing the value added tax for a period of 20 years. Money is directed to more capital intensive purposes and employment decreases though the other economic indi- The wider economic impacts of transport investments Figure 14. cators are positive. From a national perspective, all the indicators are on the negative side because of the tax increase. The direct economic benefits of the investment cause an annually growing positive impact on economic growth, employment and population. These impacts are small compared with the baseline or with the impacts of the investment spending. Summary of results extracted from the WebRailFin case calculation of Seinäjoki–Oulu. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 37 The wider economic impacts of transport investments Figure 15. Figures of results extracted from the WebRailFin case calculation of Seinäjoki–Oulu in the area of Northern Finland. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 38 The wider economic impacts of transport investments Figure 16. Figures of results extracted from the WebRailFin case calculation of Seinäjoki–Oulu in the area of Western Finland. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 39 The wider economic impacts of transport investments 6.2 6.2.1 Exploring the regional differences of wider economic impacts Comparing similar investments in different national areas of Sweden The wider economic impacts vary between the national areas, because the economic characteristics of the areas are different. These differences can be assessed with the WebRailSwe -tool by locating a same sized investment shock or a same sized productivity shock in different national areas of Sweden. For this demonstration we assume first a rail investment of 10 000 million SEK, and then an accessibility improvement worth 200 million SEK (time savings in business travel). The question of regional differences of economic impacts is of interest when there are competing investments of similar magnitude and impacts in various parts of the country. The results of the investment shock calculations are summarised in Table 6. The absolute values of the economic impacts are larger in the large economies like Stockholm and West Sweden. On the contrary, the relative size of the economic impacts is larger in the smaller economies like Upper Norrland and Middle Norrland. Table 6. Wider economic impacts of a 10 000 million SEK investment (2010–2019) shock in the national areas of Sweden in 2019. Real GDP of the area, million SEK % of Base scenario Household consumption, million SEK % of Base scenario Employment change, persons % of Base scenario Population change, persons (stock) % of Base scenario Stockholm East Middle Sweden Småland and the islands South Sweden West Sweden North Middle Sweden Middle Norrland Upper Norrland 1 925 1 840 1 794 1 877 1 862 1 772 1 692 1 747 0,19 % 0,36 % 0,64 % 0,39 % 0,27 % 0,66 % 1,39 % 0,98 % 1 148 1 344 1 249 1 288 1 293 1 250 1 225 1 247 0,27 % 0,52 % 0,91 % 0,56 % 0,39 % 0,94 % 1,97 % 1,40 % 469 614 589 599 568 568 580 546 0,04 % 0,08 % 0,15 % 0,09 % 0,06 % 0,15 % 0,35 % 0,24 % 477 653 577 651 586 588 523 524 0,02 % 0,04 % 0,07 % 0,04 % 0,03 % 0,07 % 0,14 % 0,10 % The results of the productivity shock calculations are summarised in Table 7. The general observation is that the relative sizes of the economic impacts are not so different between the national areas. One main explanation for this is that the accessibility benefits of rail investment are generally widely spread. What could be concluded from this kind of an analysis if we had two equally efficient competing projects - one in the South Sweden area and the other in the Middle Norrland area, for example? From a national point of view, a larger positive effect would be achieved by allocating the investment spending to the South Sweden area. From a regional policy point of view, on the other hand, investing in Middle Norrland would reduce the economic gaps between the national areas of Sweden. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 40 The wider economic impacts of transport investments Table 7. Wider economic impacts of an accessibility improvement worth 200 million SEK a year in the national areas of Sweden in 2019. Stockholm East Middle Sweden Småland and the islands South Sweden West Sweden North Middle Sweden Middle Norrland Upper Norrland 91,8 46,8 33,6 46,9 93,2 28,9 15,7 22,8 0,0089 % 0,0092 % 0,0119 % 0,0098 % 0,0135 % 0,0107 % 0,0129 % 0,0128 % 26,7 16,7 11,5 15,8 31,6 10,0 5,6 8,0 0,0062 % 0,0065 % 0,0084 % 0,0069 % 0,0095 % 0,0075 % 0,0090 % 0,0090 % 19,0 13,1 9,0 12,5 24,0 7,6 4,1 5,7 0,0017 % 0,0018 % 0,0023 % 0,0019 % 0,0026 % 0,0021 % 0,0025 % 0,0025 % 6,4 4,7 3,1 4,6 8,2 2,8 1,5 2,0 0,0003 % 0,0003 % 0,0004 % 0,0003 % 0,0004 % 0,0003 % 0,0004 % 0,0004 % Real GDP of the area, million SEK % of Base scenario Household consumption, million SEK % of Base scenario Employment change, persons % of Base scenario Population change, persons (stock) % of Base scenario 6.2.2 Comparing similar investments in different national areas of Finland As regards Finland and the WebRailFin -tool, we assume a rail investment of 200 million euros, and then an annual accessibility improvement worth 5 million euros (time savings in business travel). The results of the investment shock calculations are summarised in Table 8. The economic impacts vary with the size of the economy: The larger the economy the larger the absolute economic impact. On the contrary, the relative size of the economic impacts increases when the size of the economy decreases. Table 8. Wider economic impacts of a 200 million euros investment (2015–2019) shock in the national areas of Finland in 2024. Southern Finland Eastern Finland Western Finland Northern Finland Real GDP of the area, million EUR 189,30 37,32 87,61 58,64 % of Base scenario 0,16 % 0,21 % 0,18 % 0,28 % Household consumption, million EUR % of Base scenario Employment change, persons % of Base scenario Population change, persons (stock) % of Base scenario 81,44 20,41 37,43 27,77 0,13 % 0,22 % 0,15 % 0,25 % 31,47 68,57 25,94 47,73 0,003 % 0,032 % 0,005 % 0,02 % 208,04 55,80 131,38 93,64 0,007 % 0,009 % 0,009 % 0,014 % The results of the productivity shock calculations are summarised in Table 9. The relative sizes of the economic impacts are relatively bigger in Eastern Finland and in Northern Finland than in Southern Finland and Western Finland. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 41 The wider economic impacts of transport investments Table 9. Wider economic impacts of an accessibility improvement worth 5 million euros a year in the national areas of Finland in 2019. Real GDP of the area, million EUR % of Base scenario Household consumption, million EUR % of Base scenario Employment change, persons % of Base scenario Population change, persons (stock) % of Base scenario Southern Finland Eastern Finland Western Finland Northern Finland 5,02 0,92 2,12 1,05 0,0042 % 0,0051 % 0,0044 % 0,0051 % 2,63 0,50 1,11 0,58 0,0043 % 0,0053 % 0,0046 % 0,0052 % 15,70 3,20 7,47 3,68 0,0013 % 0,0015 % 0,0014 % 0,0015 % 7,00 1,85 3,67 1,98 0,0002 % 0,0003 % 0,0003 % 0,0003 % The WebRail -tools are operating at the Nuts 2 level. As far as regional planning is concerned, the use of Nuts 3 resolution of calculation would be more useful. In this project, the number of scenario simulations could not have been larger. It is however reasonable to assume, that the relative size of an economic impact in a Nuts 2 area is approximately the same in the Nuts 3 regions within the area. This assumption allows the user of the WebRail -tool to estimate economic impacts at Nuts 3 level based on the WebRail-tool’s results and regional statistics (see Table 10 for demonstration). Table 10. Estimation of the economic indicators for selected Nuts 3 regions based on the baseline and results of the WebRailFin –tool and regional statistics (Statistics Finland 2012). Step 1: Get the economic data for the Nuts 3 regions in question from the National statistics. Calculate the growth rate for each indicator/Nuts 2 area in question by using the Base scenario of the WebRail -tool. Western Southern Finland OstroGrowth bothnia 2011 => 2024 Ostrobothnia Northern Finland Growth 2011 => 2024 Central Ostrobothnia Northern Ostrobothnia Real GDP of the area 2011, million EUR Estimation of Real GDP of the area 2024 16,14 % 5 467 6 349 6 384 7 414 16,23 % 2 262 2 630 6 384 7 420 Household consumption 2011, million EUR Estimation of Household consumption 2024 16,44 % 3 303 3 846 3 046 3 546 17,65 % 1 115 1 311 6 459 7 599 Employment 2011, persons Estimation of Employment 2024 -1,33 % 87 992 86 826 86 568 85 421 -3,52 % 31 420 30 313 164 166 158 384 Population 2011, persons Estimation of Population 2024 4,10 % 193 620 201 560 178 526 185 848 3,27 % 68 403 70 641 396 426 409 399 Step 2: Use the relative results from the WebRail -tool for each Nuts 3 region within the respective Nuts 2 area. Calculate the absolute values for each region by using the regional estimates of step 1. Real GDP of the area, million EUR % of Base scenario Household consumption, million EUR % of Base scenario Employment change, persons % of Base scenario Population change, persons (stock) % of Base scenario Western Finland Southern Ostrobothnia Ostrobothnia Northern Finland Central Ostrobothnia Northern Ostrobothnia 87,61 0,18 % 37,43 0,15 % 25,94 0,005 % 131,38 0,009 % 11,43 0,18 % 5,77 0,15 % 4,34 0,005 % 18,14 0,009 % 13,35 0,18 % 5,32 0,15 % 4,27 0,005 % 16,73 0,009 % 58,64 0,28 % 27,77 0,25 % 47,73 0,020 % 93,64 0,014 % 7,36 0,28 % 3,28 0,25 % 6,06 0,020 % 9,89 0,014 % 37,88 0,28 % 19,00 0,25 % 31,68 0,020 % 57,32 0,014 % Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 42 The wider economic impacts of transport investments 6.3 6.3.1 Exploring the Base scenario for regional projections Sweden The Base scenario defined for the WebRailSwe -tool (see Chapter 5.3 for more detailed explanation) may be useful data as such in various planning projects (not only rail investments). A time series 2013–2040 for each of the four economic result indicators is produced in the “Base scenario” -worksheet for the selected national area. An example of printing the Base scenario indicators is presented in Tables 11–14. In Table 11 we see that Stockholm and South Sweden are the most expansive regions, where the GDP growth reaches 70 per cent during 2015–2040. In turn, Upper Norrland and North Middle Sweden grow by around 50 per cent during the same period. This outcome is a compound result of past trends in migration, structure of economy, as well as of continued agglomeration forces that make economic development faster in the central regions and slower in peripheral regions. Table 11. WebRailSwe Base scenario of real GDP in the national areas of Sweden (million SEK rounded to hundreds). 2015 2020 2025 2030 2035 2040 Stockholm 929 000 1 059 200 1 180 400 1 311 100 1 455 000 1 611 800 East Middle Sweden 465 500 518 600 567 300 619 700 677 800 741 300 Småland and the islands 259 400 286 100 310 900 338 000 368 000 400 900 South Sweden 431 900 488 800 542 200 600 200 664 300 734 000 West Sweden 632 400 703 200 767 500 837 000 913 600 997 200 North Middle Sweden 249 200 273 600 295 600 319 300 345 700 374 800 Middle Norrland 111 700 124 100 135 300 147 300 160 900 176 000 Upper Norrland 163 800 180 900 196 100 211 900 229 500 248 700 In broad terms, the development of private consumption mirrors that of GDP (Table 12). However, there are some differences as well. Upper Norrland does relatively better in this comparison, as its consumption volume is closer to a median growth rate. Table 12. WebRailSwe Base scenario of real household consumption in the national areas of Sweden (million SEK rounded to hundreds). 2015 2020 2025 2030 2035 2040 Stockholm 386 000 438 400 488 800 543 500 603 900 669 800 East Middle Sweden 236 600 263 600 288 000 314 300 343 500 375 400 Småland and the islands 125 800 139 200 151 200 164 300 178 700 194 400 South Sweden 206 800 233 600 259 400 287 500 318 700 352 800 West Sweden 305 100 339 400 370 300 403 600 440 300 480 400 North Middle Sweden 122 000 135 000 146 000 157 700 170 700 184 900 Middle Norrland 56 400 63 600 69 700 76 300 83 700 91 800 Upper Norrland 80 900 90 700 99 000 107 600 116 800 126 800 The indicators of employment and population growth (Tables 13 and 14) tell more or less the same story: Stockholm and South Sweden are growing fastest, while northern regions fall behind, even in absolute terms. Actually, employment declines in all the regions north of East Middle Sweden, which reflects the combined effect of unfavourable age structure and lack of labour demand, as well problems in attracting investments, as well problems in attracting the youth to stay in their native region. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 43 The wider economic impacts of transport investments Total population declines in the three northernmost regions, while other regions are expected to have at least some growth during 2015–2040. Table 13. WebRailSwe Base scenario of employment in the national areas of Sweden (number of persons rounded to hundreds). Stockholm 2015 2020 2025 2030 2035 2040 1 061 300 1 125 200 1 163 200 1 195 400 1 224 300 1 252 200 East Middle Sweden 728 100 743 300 750 400 756 300 763 000 771 900 Småland and the islands 391 200 394 700 394 700 395 200 397 000 400 300 South Sweden 638 100 669 200 686 300 701 300 715 700 730 300 West Sweden 911 900 927 300 931 700 935 100 939 500 946 600 North Middle Sweden 370 100 367 100 362 100 358 300 356 300 356 400 Middle Norrland 168 200 166 500 164 700 163 500 163 200 163 900 Upper Norrland 233 400 229 400 223 800 219 200 216 100 214 600 Table 14. WebRailSwe Base scenario of population in the national areas of Sweden (number of persons rounded to hundreds). 2015 2020 2025 2030 2035 2040 Stockholm 2 205 500 2 363 400 2 461 000 2 538 900 2 603 600 2 663 700 East Middle Sweden 1 616 500 1 673 200 1 708 400 1 732 900 1 749 700 1 764 500 Småland and the islands 827 300 849 900 861 400 868 600 872 800 876 300 South Sweden 1 458 700 1 543 900 1 591 900 1 629 000 1 659 400 1 688 300 West Sweden 1 936 700 2 001 900 2 039 500 2 064 600 2 080 600 2 093 900 North Middle Sweden 830 200 838 000 838 900 836 900 832 500 828 200 Middle Norrland 369 200 371 500 371 400 370 400 368 700 367 500 Upper Norrland 509 600 509 600 504 700 498 400 491 400 485 000 6.3.2 Finland The Base scenario indicators within the WebRailFin -tool are presented in Tables 15–18. In Table 15 we see that also in Finland the economic development is faster in the central regions and slower in peripheral regions. In Southern Finland is the GDP growth reaches 60 per cent during 2015–2040. Western Finland and Northern grow by around 50 per cent, while in the Eastern Finland the growth is only 38 % during the same period. Table 15. WebRailFin Base scenario of real GDP in the national areas of Finland (million EUR rounded to hundreds). 2015 108 900 2020 117 700 2025 129 900 2030 143 700 2035 158 300 2040 174 700 Eastern Finland 16 900 17 700 19 000 20 300 21 800 23 400 Western Finland 44 000 46 900 51 100 56 000 61 200 67 000 Northern Finland 19 100 20 400 22 200 24 200 26 300 28 700 Southern Finland Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 44 The wider economic impacts of transport investments The development of private consumption follows that of GDP in the Southern Finland (Table 16). The other areas do relatively better in this comparison. The growth of consumption in Western Finland, Northern Finland and Eastern Finland is 53 %, 52 % and 41 %, respectively. Table 16. WebRailFin Base scenario of real household consumption in the national areas of Finland (million EUR rounded to hundreds). Southern Finland 2015 56 000 2020 60 400 2025 66 500 2030 73 500 2035 81 100 2040 89 500 Eastern Finland 8 800 9 300 10 000 10 700 11 500 12 400 Western Finland 22 500 24 000 26 200 28 600 31 300 34 300 Northern Finland 10 200 10 900 12 000 13 100 14 300 15 600 The indicators of employment and population growth (Tables 17 and 18) repeat the previous conclusions. Southern Finland is growing fastest in terms of population (14 % between 2015 and 2014) and employment (9 %). The population is expected to grow in Western Finland (8 %) and Northern Finland (6 %), too, but unemployment will increase. In Eastern Finland, the total population declines by 9 % and employment by 16 % during 2015–2040. Table 17. WebRailFin Base scenario of employment in the national areas of Finland (number of persons rounded to hundreds). 2015 1 217 900 2020 1 225 200 2025 1 244 400 2030 1 267 900 2035 1 295 900 2040 1 326 400 Eastern Finland 230 900 214 200 203 400 197 200 194 400 193 400 Western Finland 558 200 550 300 550 800 556 200 565 000 575 000 Northern Finland 247 000 240 400 238 300 239 000 241 500 244 400 Southern Finland Table 18. WebRailFin Base scenario of population in the national areas of Finland (number of persons rounded to hundreds). Southern Finland Eastern Finland Western Finland Northern Finland 2015 2 766 900 2020 2 860 600 2025 2 947 100 2030 3 023 900 2035 3 090 600 2040 3 149 200 640 700 628 600 619 500 611 300 603 000 594 500 1 382 500 1 412 000 1 439 200 1 461 800 1 479 800 1 494 400 657 000 668 500 678 500 686 300 692 000 696 300 Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 45 The wider economic impacts of transport investments 7 FINAL CONCLUSIONS AND RECOMMENDATIONS Investments in transport capital reduce the costs of transport and production, and thus contribute to economic growth and productivity in the long run. The investment spending as such has more immediate economic impacts during the construction phase. The ways in which new or improved transport capacity influences economic system are complex and often indirect in nature. The improved transport infrastructure will not improve the economic vitality of a region unless other positive factors are present. The characteristics of the economy affected as well as land-use and other policies must be receptive and supportive to the investment and its impacts. Transport sector has a long tradition of using the principles of practical cost benefit analysis (CBA) in transport project appraisal that analyses the primary impacts of transport project proposals. There is, however, a growing need to know more about the wider economic impacts regarding individual infrastructure projects and also more generally concerning transport policies. Thus far, the only general and widely spread guideline for the assessment of wider economic impacts is that there may be such impacts but those must not be added to the basic cost-benefit calculus to avoid double counting. One may identify several analytical techniques for the estimation of the economic development impacts. There is a large variety of tools and methodologies from simple case studies to complex economic simulation modelling. However, there is no single analytical tool that is equally useful to all of the information needs in the planning and decision making. The purpose and level of desired sophistication of the analysis varies. In Sweden, there is already a selected tool for the estimation of wider economic benefits. The SamLok -model is based on an estimated relationship between labour income and workplace accessibility. In Finland there have not been efforts to define a common tool to assess the wider economic impacts of transport investments – until the launch of this project. The concept of an assessment tool was defined here to be a quantitative model system that uses direct cost estimates from the CBA as input parameters and calculates the wider economic impacts on a regional level. The original idea in the beginning of this project was to use the RegFinDyn CGE-model in the assessment, and to develop its twin model RegSweDyn for Sweden. The literature review confirmed that CGE-models in general are the most powerful tools to handle the complexity of the economic development impacts. The use of the actual RegFinDyn or RegSweDyn-models is, however, rather time-consuming and requires specific skills and knowledge. In this project we tried to develop an assessment tool that combines the complex general equilibrium simulations with the idea of a relatively simple user interface in MS Excel workbook that uses the results of a large number of previously made CGE-model simulations. The result of the tool development was twin tools that were named WebRailSwe and WebRailFin. The tools are made for a quantitative approximation of the wider economic impacts of large rail investments in the national areas of Sweden or Finland. The wider economic impacts calculated by this tool are supplementary to the results of a standard project assessment (CBA). The assessment of improved options is not included in either of these methodologies (Figure 17). The tools use generalised results of RegSweDyn and RegFinDyn CGE-modelling. The Swedish tool covers 8 regions (Nuts 2) and is based on generalised results of 128 scenario simulations. The Finnish tool covers 4 regions (Nuts 2 except Åland) and is based on a total of 200 scenario simulations. Both tools contain the following main parts: Basic calculation where the user enters the input parameters and receives the main results of the calculation Base scenario (2013–2040), that defines the development of the four economic indicators used here (GDP, household consumption, employment and population) as a reference alternative for the investment under investigation Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 46 The wider economic impacts of transport investments Calculation of the investment shock that takes the user-defined input parameters of the investment spending and returns the values of the economic indicators Calculation of the productivity shock that takes the user-defined input parameters of the user and producer benefits and returns the values of the economic indicators. The basic case of using the tool is to calculate the wider economic impacts of a particular rail investment. The tool can also be used to compare the economic impacts of similar investment in various areas. The projection of the Base scenario may be useful as such. It has been proved that it is possible to have a tool that is relatively simple to use but gives results that are based on comprehensive CGE-modelling. This can be considered a promising start for a wider use of advanced modelling of economic impacts in the transport sector. However, the results of this project, WebRailFin and WebRailSwe, are only applicable to rather large rail investments, and the results are calculated and presented on a spatial resolution that is rather coarse. Further work is needed to define similar tools for road investments and other forms of transport improvements. The spatial resolution should then be defined, too. Figure 17. The complementary role of WebRailSwe and WebRailFin -tools in the context of transport infratsructure impact assessment. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 47 The wider economic impacts of transport investments 8 REFERENCES Abrell, J. (2009), Transport under Emission Trading - A Computable General Equilibrium Assessment, Disertation, University of Dresden. Andersson, M. & Johansson, B. & Klaesson, J. (2005). Transportsystem och ekonomisk miljö. En vägledning för analys av infrastrukturförändringar och fyra fallstudier med beräknade regionalekonomiska effekter av förändrad transportinfrastruktur. Jönköping International Business School. Anderstig, Ch., Berglund, S., Börjesson J., Kanerva E. (2007), Trafikverkens inriktningsplanering – analyser av regionala utvecklingseffekter med SamLok-modellen, WSP Sverige AB. Bannister, D. & Berechman, J. (2000). Transport Investment and Economic Development, Routledge. Abrell, J. (2009), Transport under Emission Trading - A Computable General Equilibrium Assessment, Disertation, University of Dresden. Banverket (2009). Norrbotniabanan, etapp 1. Samlad effektbedömning. Banverket, Vägverket, Sjöfartsverket, Luftfartsstyrelsen. Stockholm. Berechman, J. (2009). The evaluation of transportation investment projects. Routledge Advances in Management and Business. New York. Bohlin, L. (2010), Taxation of Intermediate Goods, A CGE Analysis, Örebro University. Bohlin L., Levin J., and Sayeed Y. (2013). A Swedish Regional Social Accounting Matrix with trade and transport, Department of Economics, Örebro University. De Jong, G., Gunn, H.F. (2004), National and international freight transport models: an overview and ideas for suture development, Transport Reviews, 24(1). Docwra, G., & West, G. (1999), Predicting the Impacts of Road Investment on Gross State Product and Employment’, Contributed paper presented at 23rd Australasian Transport Research Forum, Perth, Australia. Eliasson, J. (2013). International Comparison of Transport Appraisal Practice. Annex 4 Sweden Country Report. University of Leeds, Instititute for transport studies, Royal Institute of Technology, Stockholm, Centre for transport studies, Stockholm. Eurostat (2008). Eurostat Manual for Supply, Use and Input-Output tables. Eurostat Methodologies and Working Papers. Graham, D. (2007), Agglomeration Economies and Transport Investment. Joint Transport Research Centre. Disussion Paper No. 2007-11. Graham, D. (2012). Wider economic benefits of transport investment and the role of agglomeration. A slide presentation. Imperial college London. Guide to Quantifying the Economic Impacts of Federal Investments in Large-Scale Freight Transportation Projects, Cambridge Systematics, Inc., Economic Development Research Group, Inc., Boston Logistics Group, Inc. 2006. Honkatukia J. (2009), VATTAGE – A dynamic, applied general equilibrium model of the Finnish Economy, Research Reports 150, Government Institute for Economic Research. Ivanova, O., Heyndrickx, Ch., Spitaels K., Tavasszy, L., Manshanden, W., Snelder M., Koops, O. (2007), RAEM: version 3.0, First report, Transport & Mobility Leuven. Karlsson, R., Vierth, I., Johansson, M. (2012), An outline for a validation database for SAMGODS, VTI. Kernohan D., Rognlien L. (2011), Wider economic impacts of transport investments in New Zealand, NZ Transport Agency research report 448. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 48 The wider economic impacts of transport investments Laakso, S., Loikkanen, H. (2004), Kaupunkitalous. Johdatus kaupungistumiseen, kaupunkien maankäyttöön sekä yritysten ja kotitalouksien sijoittumiseen (Urban Economics. An introduction to urbanisation, urban land use and the location of firms and households), Gaudeamus, Helsinki. Laakso, S., Moilanen, P. (2011), Yritystoiminnan sijoittuminen ja työpaikkakeskittymien muodostuminen monikeskuksisessa aluerakenteessa (Location of enterprises, specialization and the formation of economic concentrations in a polycentric regional structure), Sektoritutkimuksen neuvottelukunta, alue ja yhdyskuntarakenteet ja infrastruktuuri, 5-2011. Littman, T. (2019). Evaluating Transportation Economic Development Impacts. Victoria Transport Policy Institute. Meriläinen, A., Tervonen, J., Kiiskilä, K., and Teerihalme, H. (2011). Impact assessment of the Lahti motorway and the Kerava–Lahti direct rail line, study after implementation. Finnish Transport Agency, Transport Planning. Helsinki 2011. Research reports of the Finnish Transport Agency 34/2011. Helsinki. Metsäranta, H., Laakso, S., Rinta-Piirto, J., Haapamäki, T., Törmä, H. K., Määttä, S. & Reini, K. (2012), Pisara-radan laajemmat yhteiskunnalliset vaikutukset, Liikenneviraston tutkimuksia ja selvityksiä; 11. Monzón, A., Ndiaye, A. B., Pfaffenbichler, P. C., Wegener, M.(2010), Evaluation of TRANS-TOOLS Version 2, Report for the European Commission Joint Research Centre (JRC) Institute for Prospective Technological Studies (IPTS) Seville. MOTOS (2007), Transport Modelling: Towards Operational Standards in Europe, MOTOS Handbook containing guidelines for constructing national and regional transport models. NCFRP (2011), Framework and Tools for Estimating Benefits of Specific Freight Network Investments, NCFRP Report 12, Washington. OECD (2008), The Wider Economic Benefits of Transport: Macro-, Meso and Micro Transport Planning and Investment Tools, Discussion Paper No. 2008-6. Ratahallintokeskus (2006). Seinäjoki–Oulu-radan palvelutason parantaminen. Yhteiskuntataloudelliset tarkastelut. (The improvement of the Seinäjoki–Oulu railway. Socio-economic assessment.) Ratahallintokeskus, Strafica Oy. Helsinki. Rutherford, T. F., Törmä, H. (2010), Efficiency of Fiscal Measures in Preventing Out Migration from NorthFinland, Regional Studies Vol. 44.4, 465 - 475. Available from http://www.helsinki.fi/ruralia/research/regfin.htm Röcklinger, M. (2012), Verktyg för dynamiska effekter av infrastruktur inför kommande åtgärdsplanering, Trafikverket. Sinha C K ja Labi S (2007). Transportation Decision Making. Principles of Project Evaluation an Programming. John Wiley & Sons, Inc. New Jersey, USA. Sue Wing, I., Anderson, W.P., Lakshmanan, T.R. (2007), The Broader Benefits of Transportation Infrastructure, Boston University Centre for Transportation Studies, OECD/ITF. Statistics Finland (2012). Statistical yearbook of Finland 2012. Helsinki. Sundberg, M. (2005), Spatial Computable General Equilibrium Modelling - Static and Dynamic Approaches, Royal Institute of Technology. Sundberg, M. (2009), Essays on Spatial Economies and Organization, Royal Institute of Technology. Tavasszy, L. (2007), Freight Modelling An Overview of International Experiences, Radboud University Nijmegen. TRB (2012). Interactions Between Transportation Capacity, Economic Systems, and Land Use. Second strategic highway research programme. Transportation Research Board of the National Academies, Report S2-C03-RR-1. Washington DC, USA. Törmä, H. (2008), Do Small Towns Development Projects Matter, and Can CGE Help? Journal of Spatial Economic Analysis, Vol. 3, No. 2, 247 - 268. Available from http://www.helsinki.fi/ruralia/research/regfin.htm Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 49 The wider economic impacts of transport investments Törmä H., Kinnunen J., Määttä S. and Zimoch U. (2013). Effects on regional and municipal economy, population and demographics of Sodankylä’s Kevitsa mine. Ruralia Institute Reports 102 (in Finnish, English Abstract). Available from http://www.helsinki.fi/ruralia/research/regfin.htm Törmä, H., Zawalinska, K. (2007), Technical descriptions of the CGE REgFin/RegPol models, Ruralia Institute, University of Helsinki. Törmä, H., Zawalinska, K. (2010), Methodological description of the CGERegEU model. FP7 CAPRI-RD project, Deliverable 3.2.2. Available from http://www.ilr1.unibonn.de/agpo/rsrch/capri-rd/del.htm Törmä, H., Zawalinska, K. (2011), Final documentation of the CGERegEU+ model, FP7 CAPRI-RD project, Deliverable 3.2.3. Available from http://www.ilr1.unibonn.de/agpo/rsrch/capri-rd/del.htm Vold, A., Andersen, J., Hovi, I. B., Ivanova, O., Jean-Hansen, V., Lervåg, L.-E.,. Meland, S., Wahl, R. (2002), NEMO Network model for freight transport within Norway and between Norway and other countries, Oslo. Vold, A., Jean-Hansen, V. (2007), PINGO – A model for prediction of regional and interregional freight transportation in Norway, Institute of Transport and Economics, Norwegian Centre for Transport Research. Wallis, I. (2009), Economic Development Benefits of Transport Investment, NZ Transport Agency Research Report 350. Williams, I., Tavaszy L., Muskens J. (2002), Feasibility Study of SCGE Models of Goods Flows in Sweden, SIKA – Swedish Institute for Transport and Communications Analysis, Stockholm, Sweden. Wittwer, G. (Ed.). (2012). Economic Modeling of Water: The Australian CGE Experience. Global Issues in Water Policy 3. Springer. World Bank (2009), World development report. Reshaping economic geography. Zawalinska, K. (2009) Instruments and effects of European Union support for regional rural development in Poland, Institute of Rural and Agricultural Development, Polish Academy of Sciences, Warsaw. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 50 The wider economic impacts of transport investments APPENDIX 1 Examples of CGE models in BGLC countries Country Finland Sweden Name of model RegFinDyn Type of model Dynamic regional CGE VATTAGE Dynamic CGE SAMLOK Localisation model SAMGODS The Swedish national freight model system Transport model multi-sectorial input-output SAINT Comparativestatic CGE The Öresund model Comparativestatic SCGE Main features Applicable to NUTS 1, 2 and 3 levels, top-down technique for municipalities Many sectors, 18-28 (primary, industry, services) depending on the regional level Calibrated to economic structure of the latest normal year 2008 Data source: Statistic Finland Calculations used in more than 50 scientific case studies, many of which are investment studies Used in Pisara railway investment evaluation project and in several other infrastructure, like mining investment studies Model of the Finnish economy (a whole country model) Database based on national accounts and IO data, includes behavioural parameters Supporting transactions between institutional sectors of the economy Used for public policy analysis Carlino and Mills (1987) modelling approach The only Swedish model that provides a simultaneous determination of the location of population and employment Uses accessibility measures generated by SAMPERS (The Swedish National Travel Demand Forecasting Tool) Estimated on a beneficial measure of changes in accessibility Used to estimate wider economic effects by Swedish transport authorities Estimations are based on “quasi-disaggregate” data on the “kommun” (=”municipality”, roughly corresponding to “cities”, but large cities typically consist of many municipalities) Aggregate-disaggregate-aggregate (ADA) model system Sweden is divided into 288 zones, plus 174 regions abroad 34 commodity groups Simplistic model structure Short and long run simulations Providing base line for larger projects Used for 2030 national prognoses Plans to include a SCGE module to the model have been already presented A development of the IFPRI model Used for closed economies as well as for small open economies Flexible modelling of trade margins Data based on SAM 55 commodity groups Base year 2001 Data source: Statistic Sweden Basic model structure developed by Bröcker Calibrated to pre-bridge data from the year 1999 5 regions: 3 from Sweden and 2 from Denmark Based on SAM separately for Swedish and Danish regions 17 sectors after aggregation Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 51 The wider economic impacts of transport investments Extensions: treatment of trade with the rest of the world, possibility of including barriers to trade, and calibration procedures to fit available data Norway Poland Germany PINGO A model for prediction of regional and interregional freight transport in Norway RegPolDyn Comparativestatic SCGE 19 regions (NUTS 3) plus one region that corresponds to all other countries Data source: Statistic Norway, NEMO, the Foreign Trade Statistics 13 commodity groups Data organised as SAM Includes imports and exports Dynamic SCGE Technology Rich CGE Model of Germany Static CGE Similar technical features like RegFinDyn, except the population module Operating on NUTS 2 data: 16 regions with 15 sectors per region Benchmark year: 2006 Data source: Central Statistical Office of Poland and Regional Statistical Offices Small open economy assumption Based on IO table Detailed representation of electricity generation, private transport, and congestion effects Transport module includes: type of vehicle, distance, time periods, road networks 18 sectors 4 transport sectors include: aviation, water, rail, and other land transport Benchmark year: 2004 Sources: Metsäranta et. al., 2012; Sundberg, 2005; Vold et al., 2007; Törmä, H., Zawalinska, K., 2007; Zawalinska, 2009; Bohlin, 2010; Abrell, 2009; Anderstig et al., 2007; Karlsson et al., 2012; Röcklinger, 2012; Honkatukia, 2009 Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 52 The wider economic impacts of transport investments APPENDIX 2 Sectors of the CGE models. Finland 1. Agriculture and hunting 2. Forestry and logging 3. Fishing and aquaculture 4. 5. 6. 7. 8. Mining and quarrying Food, beverages and tobacco products Textiles, wearing apparel, leather and related products Wood and products of wood and cork etc., except furniture Paper and paper products, printing and reproduction of recorded media 9. Coke and refined petroleum products, chemicals and chemical products, basic pharmaceutical products and pharmaceutical preparations, rubber and plastic products 10. Other non-metallic mineral products 11. Basic metals, fabricated metal products, except machinery and equipment 12. Computer, electronic and optical products, electrical equipment 13. Machinery and equipment n.e.c. 14. Motor vehicles, trailers and semi-trailers, other transport equipment 15. Furniture, other manufacturing, repair and installation of machinery and equipment 16. Electricity, gas, steam and air conditioning supply, water supply, sewerage, waste management and remediation activities 17. Construction 18. Wholesale and retail trade, repair of motor vehicles and motorcycles 19. Rail transport 20. Road transport Sweden 1. Agriculture, forestry and fishing 2. Mining, quarrying and manufacturing industry 3. Electricity, gas, steam and air conditioning, water supply, waste 4. Construction 5. Wholesale and retail trade 6. Rail transport 7. Road transport 8. Water transport 9. Air transport 10. Warehousing 11. Transport services 12. Post and courier services 13. Hotels and restaurants 14. Information and communication 15. Financial services and insurance activities 16. Real estate activities 17. Professional, scientific, technical and administrative activities 18. Public authorities and national defence 19. Education 20. Human health and social work activities; personal and art services 21. Water transport 22. Air transport 23. Warehousing 24. Transport services 25. Post and courier services 26. Accommodation and food service activities 27. Information and communication 28. Financial and insurance activities 29. Other real estate activities 30. Renting and operating of own or leased real estate 31. Professional, scientific and technical activities 32. Administrative and support service activities 33. Public administration and defence, compulsory social security 34. Education 35. Human health and social work activities, arts, entertainment and recreation, other service activities, activities of households as employers etc. Contact: Jukka Lindfors E-mail: [email protected] Phone: +358 3 2481235 53
