Socio-Economic and Spatial Impacts
of Trans-European Transport Networks


Model Structure


Michael Wegener, Dieter Bökemann


Summary of:
Wegener, M., Bökemann; D. (1998): The SASI Model: Model Structure. SASI Deliverable D8. Report to the European Commission. Institut für Raumplanung, Universität Dortmund.


The SASI model is to consistently forecast socio-economic and spatial impacts of transport infrastructure investment and transport system improvements in Europe. From this purpose the following requirements can be derived: The model must be responsive to changes in European transport policy, in particular to different scenarios and time schedules of expanding and improving the trans-European rail and road networks, and it must produce regional indicators of socio-economic development and cohesion that are relevant from the point of view of policy objectives of the European Union.

The first of these two requirements is addressed by calculating regional accessibility indicators expressing the location of each region within the strategic European rail and road networks defined for SASI. Changes in the trans-European networks affect the distribution of accessibility and the economic advantage across regions. However, regional socio-economic development cannot be explained by transport changes alone. Therefore other (non-transport) factors determining regional socio-economic development are included in the model. These factors include assumptions about European developments as well as factors expressing the endowment, or suitability and capacity for economic activities, of regions. When comparing different scenarios of transport network development, the non-transport factors have to be kept constant.

The second requirement determines the output and hence necessary submodels of the model. As indicated above, the goals of the European Union are the promotion of harmonious and balanced economic development, stable, non-inflationary and sustainable growth, convergence of economic performance, high levels of employment and social security, improvement of the quality of life and economic and social coherence and solidarity between the member states. Since sustainability objectives are (for the time being) excluded from SASI, efficiency and equity objectives remain as the relevant goals. Despite their acknowledged weaknesses the most commonly used indicators of regional economic efficiency are regional output and employment or, in operational terms, gross domestic product (GDP) per capita and rate of unemployment. This implies that not only economic output and employment but also population and labour force have to be modelled. Equity or cohesion indicators finally express the distribution of GDP per capita and unemployment across regions.

Based on the above considerations, the SASI model has six forecasting submodels: European Developments, Regional Accessibility, Regional GDP, Regional Employment, Regional Population and Regional Labour Force. A seventh submodel calculates Socio-Economic Indicators with respect to efficiency and equity.


1. Submodels

In this section the seven submodels of the SASI model and the interrelationships between them are briefly described. Figure 1 visualises the interactions between the seven submodels.

The SASI model

Figure 1. The SASI model


European Developments
Here assumptions about European developments are entered that are processed by the subsequent submodels. European developments include assumptions about the future performance of the European economy as a whole and the level of immigration and outmigration across Europe's borders. They serve as constraints to ensure that the regional forecasts of economic development and population are consistent with external developments not modelled. Given the expected rapid population growth and lack of economic opportunity in many origin countries, total European immigration will be largely a function of immigration policies by national governments of the countries of the European Union. Another relevant European policy field are transfer payments by the European Union via the Structural Funds or the Common Agricultural Policy or by national governments to assist specific regions, which, because of their concentration on peripheral regions, are responsible for a sizeable part of their economic growth. The last group of assumptions are those about policy decisions on the trans-European networks. As these are of focal interest in SASI, they are modelled with considerable detail. A network scenario is a time-sequenced investment programme for addition, upgrading or closure of links of the road, rail or air networks. Besides a 'baseline' scenario several TETN scenarios will be specified.

Regional Accessibility
This submodel calculates regional accessibility indicators expressing the locational advantage of each region with respect to relevant destinations in the region and in other regions as a function of travel time or travel cost (or both) to reach these destinations by the strategic road, rail and air networks.

Regional GDP
This is the core submodel of the SASI model. It calculates a forecast of gross domestic product (GDP) per capita by industrial sector (agriculture, manufacturing, services) generated in each region as a function of endowment indicators and accessibility. Endowment indicators are indicators measuring the suitability or capacity of the region for economic activity. Endowment indicators may include traditional location factors such as availability of skilled labour and business services, capital stock (i.e. production facilities) and intraregional transport infrastructure as well as 'soft' location factors such as indicators describing the spatial organisation of the region, i.e. its settlement structure and internal transport system, or institutions of higher education, cultural facilities, good housing and a pleasant climate and environment. Accessibility indicators are derived from the Regional Accessibility submodel. In addition to endowment and accessibility indicators, monetary transfers to regions by the European Union such as assistance by the Structural Funds or the Common Agricultural Policy or national governments are considered, as these account for a sizeable portion of the economic development of peripheral regions. The results of the regional GDP per capita forecasts are adjusted such that the total of all regional forecasts multiplied by regional population meets the exogenous forecast of economic development (GDP) of Europe as a whole by the European Developments submodel.

Regional Employment
Regional employment is derived from regional GDP by exogenous forecasts of regional labour productivity by industrial sector (GDP per worker) modified by effects of changes in regional accessibility.

Regional Population
Regional population changes due to natural change and migration. Births and deaths are modelled by a cohort-survival model subject to exogenous forecasts of regional fertility and mortality rates. Interregional migration within the European Union is modelled in a simplified migration model as annual net migration as a function of regional unemployment and other indicators expressing the attractiveness of the region as a place of employment and a place to live, whereas immigration to and outmigration from the European Union are modelled separately. The migration forecasts are adjusted to comply with total European immigration and outmigration forecast by the European Developments submodel and the limits on immigration set by individual countries. In addition educational attainment, i.e. the proportion of residents with higher education, is forecast as a function of national education policy.

Regional Labour Force
Regional labour force is derived from regional population and exogenous forecasts of regional labour force participation rates modified by effects of regional unemployment.

Socio-economic Indicators
Total GDP and employment are related to population and labour force by calculating total regional GDP per capita and regional unemployment. Accessibility, besides being a factor determining regional production, is also considered a policy-relevant output of the model. In addition, equity or cohesion indicators describing the distribution of accessibility, GDP per capita and unemployment across regions are calculated.


2. Space and Time

The SASI model forecasts socio-economic development in the 201 regions at the NUTS-2 level defined for SASI for the fifteen EU countries. These are the 'internal' regions of the model. The 27 regions defined for the rest of Europe are the 'external' regions which are used as additional destinations when calculating accessibility indicators. The four regions representing the rest of the world are not used.

The spatial dimension of the system of regions is established by their connection via networks. In SASI road, rail and air networks are considered. The 'strategic' road and rail networks used in SASI are subsets of the pan-European road and rail networks developed by IRPUD and recently adopted for the GISCO spatial reference database of Eurostat. The 'strategic' road and rail networks contain all TETN links laid down in Decision No. 1692/96/CE of the European Parliament and the Council (European Communities, 1996) and the east European road and rail corridors identified by the Second Pan-European Transport Conference in Crete in 1994 as well as additional links selected for connectivity reasons. The SASI system of regions and the strategic networks used in SASI are also used in the concurrent DGVII projects STREAMS, EUNET and STEMM.

The temporal dimension of the model is established by dividing time into discrete time intervals or periods of one year duration. By modelling relatively short time periods both short- and long-term lagged impacts can be taken into account. The base year of the simulations is 1981 in order to demonstrate that the model is able to reproduce the main trends of spatial development in Europe over a significant time period of the past with satisfactory accuracy. The forecasting horizon of the model is 2016.


3. Model Output

Output of the model are indicators measuring socio-economic and spatial impacts of the simulated policies. Three groups of output indicators were defined:

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Gross domestic product (GDP) was chosen to represent the economic performance of a region. GDP per capita allows to draw conclusions on regional income levels. Despite its well-known theoretical and methodological drawbacks this indicator continues to be the most commonly used indicator of regional economic efficiency.

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The unemployment rate is used to indicate the social condition of a region. This indicator, too, presents measurement problems because there exist large differences in the definition of unemployment in European countries. Nevertheless unemployment remains the most widely used social indicator and is easily related to policy goals.

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In addition to the above regional indicators macro indicators expressing the distribution of GDP and unemployment across regions are used as indicators of cohesion between the regions of the European Union. Cohesion indicators inform about the degree of spatial concentration or dispersion of GDP or unemployment and if applied to modelled policies show whether the implementation of a policy would contribute to the political goal of reducing socio-economic disparities or not.

Using these indicators it can be shown that cohesion and integration policies of the European Union have not always been successful. In fact there is no evidence that regional income differences in Europe have been reduced during the 1980s. In terms of regional unemployment, the gap between successful and declining regions even seems to have widened (Bökemann et al., 1997).


4. Conclusions

The model of socio-economic and spatial impacts of large-scale European transport infrastructure investments presented in this paper has a number of advantages compared with other approaches to modelling the impacts of transport infrastructure investments and transport system improvements:

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The model predicts not only regional production but also regional population and so is capable of modelling regional unemployment, which is of major importance for policy making of the European Union.

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The model stands out by its comprehensive geographical coverage including all regions of the fifteen member states of the European Union at NUTS-2 level and as external regions the rest of Europe with the European part of Russia.

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In methodological terms the model steers a middle course between the complexity of a multi-regional input-output framework and aggregate econometric modelling approaches by modelling transport infrastructure investments and transport system improvements on regional production by regional production functions in which transport infrastructure is represented by spatially disaggregate accessibility indicators.

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The model is particularly flexible in incorporating 'soft' non-transport factors of regional economic development beyond the economic factors traditionally included in regional production functions.

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The dynamic character of the model enables it to appropriately deal with the range of different dynamics associated with interactions processes determining regional socio-economic development.

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The cohesion indicators calculated by the model make it particularly relevant for studying the impacts of transport infrastructure investments and transport system improvements on the convergence (or divergence) of socio-economic development in the regions over time.

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The model has relatively moderate data requirements and does not require highly disaggregate classifications of industries or population or an input-output table nor road, rail and air networks coded with excessive detail.

The ongoing work phase in the SASI project concentrates on making the model operational and completing the calibration of the model equations. Programming work for implementing a prototype of the model as outlined in this paper is underway. The completion of the air network will soon make it possible to calculate accessibility by air and multimodal (fastest-mode and logsum) accessibility. Data collection and estimation of missing data are nearing completion. The statistical analyses to test different hypotheses about factors to be included in the regional production and migration functions are in progress.

The calibrated and validated model will be used to forecast the impacts of future additions or modifications to the base TETN with respect to the indicators discussed in Section 3.4.

As a reference or 'baseline' scenario the implementation of all new or upgraded TETN links on which decisions already have been taken will be used. Other TETN scenarios will be developed by adding to the baseline scenario different subsets of the remaining TETN links laid down in Decision No. 1692/96/CE of the European Parliament and the Council (European Communities, 1996) and the east European road and rail corridors identified by the Second Pan-European Transport Conference in Crete in 1994 such as

- baseline network + all planned TETN road projects
- baseline network + all planned TETN rail projects
- baseline network + all planned TETN road and rail projects

Further scenarios may be developed as modifications of the above scenarios by assuming different time schedules or priorities for the completion of selected road or rail projects both within the European Union or in the east European corridors. If accessibility indicators based on generalised cost are applied, it is also possible to investigate impacts of road pricing policies.


References

Bökemann, D., Hackl, R. and Kramar, H. (1997) Socio-Economic Indicators Model and Report. SASI Deliverable D4. Report to the European Commission. Institut für Stadt- und Regionalforschung, Technische Universität Wien.

European Communities (1996): Decision No. 1692/96/CE of the European Parliament and of the Council of 23 July 1996 on the Community guidelines for the development of the trans-European transport networks. Official Journal of the European Communities 39, L 228, 9 September 1996, 1-104.



© 1998 Michael Wegener, Dieter Bökemann




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