1. SPATIAL SCENARIOS AND ORIENTATIONS IN RELATION TO THE ESDP AND EU COHESION POLICY (2004-06) Roberto Camagni e Roberta Capello Politecnico di Milano ESPON National Meeting, 18 Gennaio 2005

2. Project 3.2 Lead Partner: Free University of Brussels - IGEAT Project Parners: Politecnico di Milano AETS – Agence Européenne “Territoire et Synergie” BBR University of Leeds – CUDEM CRS – HAS – Hungarian Academy of Science MCRIT – Spagna NISR – Paesi Bassi NORDREGIO UMS 2414 – Réseau Interdisciplinaire pour l’Amenagement

3. Aims of the project: To synthetise all data and information collected in ESPON projects and on the basis of this information to build territorial scenarios on possible and (un)desirable futures in order to deduce policy recommandations

4. Two parallel scenario approaches: - A qualitative scenario approach - A quantitative scenario approach

5. The qualitative scenario approach Past trends in each strategic macro-theme (i.e. demography, economy, energy, etc..) Thematic scenarios. In each theme there will different scenarios according to different driving forces Cross-thematic scenarios

6. Thematic scenarios on: Demography (2) Economy (4) Energy (1) Transport (3) Enlargement (4) Governance (4) Rural development (2) Environment (2) Socio-cultural issue (not yet studied)

7. Examples of driving forces for the thematic scenarios: -Demography: More or less restrictions on immigration; Impact of immigration on activity rate and skills of population Economy: External competition and globalisation will continue Four possible policy developments (competitiveness and equity; equity; laissez-faire – competitiveness within European regions – competitiveness);

8. Present situation Past trends developed Thematic scenario sketches – development in 2005. Cross-thematic scenarios – next year

9. The quantitative scenario approaches To measure the effects on territory - in terms of efficiency and cohesion – of some qualitative cross-thematic scenarios (MASST Model); To measure European Territorial Cohesion Index (ETCI); To predict future flows of people and goods in order to identify future transport bottlenecks (KTEN model).

10. MASST is an econometric model estimating the determinants of local development and its forecasts. Local development is divided into two components, the national component and the local differential shift component. The Masst model estimates both of them. The structure of the model is represeted in the following chart: MASST Model

11. Conceptual underpinnings Socio-cultural changes New technological paradigms Policies Driving forces (scenario elements) Enlargement Structural macroeconomic elements Macreconomic elements Territorial filters: geographical position and productive structure Territorial context Regional differetial component National component Outcomes Regional development and imbalance Economic effects Short term macroeconomic elements

12. Submodel 1: National component Submodel 2: Regional differential component Exchange rate movements € / $, national currencies Internal consumption Δ Efficiency wage (inflation and productivity increases) Exports Macroeconomic elements Interest rates Investments (including FDI) Institutional distance Differential shift Regional differential component Hhuman capital policies Infrastructural policies Innovative policies Structural policies PAC Human capital Infrastructural level Innovative capacity Regional structural elements Capital / labour ratio Population Macroeconomic policies Territorial context Geographical position Urban structure Productive structure National component National growth - attractiveness - economic success Regional growth - attractiveness - economic success - spatial spillovers Regional equity disparities Final economic effect Public expenditure Imports Accessibility

13. Driving forces - macroeconomic - technological - institutional -socio-cultural

14. Macroeconomic driving forces -trend in the euro/$ exchange rate -trend in fiscal morality (trend in public debts, revision of the Maastricht parameters) -trend in interest rates - trend in inflation rate -geo-political orientation of FDI -rebalancing of external accounts of big emerging countries (China, etc..) -increase in energy price

15. Technological driving forces - Infrastructure development -R&D development -New technological paradigm

16. Institutional driving forces -Enlargement -Restructuring of Community Agricultural Policy -Reorientation and size of structural funds -Attitude towards East-West and North-South migration

17. Socio-cultural driving forces -Trend in fertility rate -Trend in population aging -Trend in saving ratio

18. Characteristics of scenarios based on MASST - the results of the exercise will be territorial scenarios (at NUTS2 level); - each scenario will be based on general driving forces; -single driving force impact forecasts will be produced; - the MASST scenarios will be the result of a combination of different hypotheses on the driving forces; -each scenario will be the result of a cause-effect chain, which will influence variables of different nature (demographic, technological, macroeconomic); -a limited number of scenarios will be produced;

19. Present situation - Database in cross-section and time-series nearly completed; - Model specification

20. Future steps - Model calibration; - Identification of the scenario hypotheses; - Scenario estimates.