1. ESPON 2006 Programme Action 1.1.4: THE SPATIAL EFFECTS OF DEMOGRAPHIC TRENDS AND MIGRATION 2nd interim report, August 2003 Lead partner and coordinator: Swedish Institute for Growth Policy Studies (ITPS), Stockholm, Sweden Partners: Centre for Geographical Studies (CEG), University of Lisbon Foundation (FUL), Lisbon University of Vienna, Institute for Geography and Regional Research, Vienna Universite Libre de Bruxelles (ULB), Departement de Geographie, Bruxelles University G.d'Annunzio, Department of Economy and History of the Territory, Pescara Norwegian Institute for Urban and Regional Reseach (NIBR), Oslo VÁTI, Hungarian Public Non Profit Company for Regional Development and Town Planning, Budapest

3. WP0: Management and administrationWP leader: ITPS WP1: Data gathering, indicators and conceptualisation WP Leader: ITPS Central role: ULB Inputs: All partners WP2: Natural population development and ageing WP Leader: ITPS Central role: NIBR Input: All partners WP3: Migration within and between European countries WP Leader: ULB Central role: University d'Annunzio, University of Vienna, VATI (especially, candidate countries) Inputs: All partners WP4: Fertility, migration and depopulation WP Leader: NIBR Central role: CEG Inputs: All partners WP5: Ageing, labour shortage and ‘replacement migration’ WP Leader: CEG Central role: University d'Annunzio Inputs: All partners WP6: Population, migration and spatial development – policy recommendations. Final report WP Leader: ITPS Inputs: All partners ESPON 1.1.4. Work packages and labour division

4. Key preliminary results in SIR – introduction and a summing-up Population development - total Natural population development Fertility development Ageing Dependency ratios Reproduction potentials Migratory balances Depopulation areas The need for replacement migration (intro to some case studies, all of them not yet decided) - ageing - labour shortage Typologies

5. Population change 1996-1999

6. Total population change 1996-1999, quartiles

7. Population change, base typology, 6 types 1PT>0PM>0PN>0 In-migration and young population/ ”high” TFR 2PT>0PM>0PN<0 In-migration but low fertility rate 3PT>0PM<0PN>0 Out-migration but young population/ ”high” TFR 4PT<0PM<0PN<0 Out-migration and “ageing”/ ”low” TFR 5PT<0PM>0PN<0 In-migration and “ageing”/ ”low” TFR 6PT<0PM<0PN>0 Out-migration but still young population/ ”high” TFR PT=Total population development PM=Net migration PN=Natural population development

8. Population change 1966-1999, six typologies

9. ESPON 1.1.4 Main preliminary results WP2: Natural population development and ageing Population change – more driven by migration than natural population development Half of the regions have a natural population decrease Ageing – more a function of earlier out-migration than low fertility No connection between ageing and total population change No connection between ageing and net-migration today – exception the Nordic countries Connection – ageing and dependency rates In Southern Europe – ageing and low fertility reinforce each other; consequences for the natural population development (reproduction potential)

10. Total Fertility Rates (TFR)1999

11. Ageing (65+)

12. “Natural Population Growth Potential 2000/2020

13. ESPON 1.1.4 Main preliminary results WP3: Migration within and between the European countries Borders – a hampering factor European growth zones – in-migration Economic discrepancy – still a driving force but weaker than before Suburbanisation and peri-urbanisation  internal migration (redistribution of people from the centre to the surrounding areas) Youngsters to the metro areas (studies, urban life-styles) – middle-aged and elderly people to the “peripheral” areas (environmental factors) Rural exodus still important In the Nordic countries and Eastern Europe – movements from peripheral areas to metropolitan areas are still of great importance “Monocentric” development at the European level – “polycentric” development at the regional level

14. Migratory balance 1996-1999

15. Typology based on migratory balances by ages Ages/Types20-2930-4450-64 1+-- 2+0- 3++- 4+++ 5+0+ 6++0 7+00 8-0- 9--0 10-++ 11-0+ 12-+ 13-00 140-- 150+- 160++ 1700+ 180+0 19000 + = balance > 7,5 or 10 for thousands - = balance < -7,5 or –10 for thousands 0 = balance between –7,5 (or10) and 7,5 (or 10) for thousands.

16. ESPON 1.1.4 Main preliminary results WP4: Fertility, migration and depopulation Most negative development: most sparsely populated areas in France, Spain and Portugal northern and southern parts of eastern Europe peripheral regions of Sweden and Finland Very strong depopulation is found in: Territories in countries with very low fertility rates and out-migration Analyses and maps based on both direct and indirect depopulation indicators

17. Depopulation areas

18. Preliminary typology, alternative 1, based on direct indicators of “depopulation” CODE, composit indicator (”typology”) of ”depopulation” TERRITORIAL LEVEL/Indicator NATION Total Fertility Rate 1999 NUTS 2 Recent population change/share of population in declining NUTS 3 units >25% of population in NUTS 2 region (1995-1999) NUTS 3 Recent population change (1995-1999) 1 Very strong depopulationExtremely lowDecline 2 Strong depopulationVery lowDecline 3 DepopulationExtremely lowDeclineNot decline Extremely lowNot declineDecline Very lowDeclineNot decline Very lowNot declineDecline 4 Possible depopulationLowDecline LowDeclineNot decline LowNot declineDecline 5 No depopulationExtremely lowNot decline Very lowNot decline LowNot decline

19. Direct indicator of depopulation, alternative 1

20. CODE, composit indicator (”typo-logy”) TERRITORIAL LEVEL/Indicator NATION Total Fertility Rate 1999 NUTS 2 Recent population change/share of population in declining NUTS 3 units > 25% of NUTS 2 population (1995-1999) NUTS 3 Recent populati on change (1995- 1999) 1 (Depopulation 1) Extremely low Decline 2 (Depopulation 2) Very lowDecline 3 (Depopulation 3) Extremely low DeclineNot decline Extremely low Not declineDecline Very lowDeclineNot decline Very lowNot declineDecline LowDecline 4 (No depopula- tion) Extremely low Not decline Very lowNot decline LowDeclineNot decline LowNot declineDecline LowNot decline Preliminary typology, alternative 2, based on direct indicators of “depopulation”

21. Direct indicator of depopulation, alternative 2

22. (Indirect) Depopulation Indicators IndicatorTemporal scopeTerritorial scale Structural indicators: 1. Share of children: 0-14/Tot.pop1990?, 2000NUTS 2 2. Ageing Population: 65+/Tot.Pop1990?, 2000NUTS 2 3. Ageing "Labour Force": 55-64/20-641990?, 2000NUTS 2 4. "Labour Force" Replacement Ratio: 10- 19/55-64 1990?, 2000NUTS 2 5. Post-Active Dependency Ratio: 65+/20- 64 1990?, 2000NUTS 2 6. Aged People vs. Youth: 65+/15-241990?, 2000NUTS 2 Average score on indirect "ageing"/ "depopulating" indicators 1990?, 2000NUTS 2 Structural growth potential: 7. Changes in Natural Growth Potential: 20-29 years in 2020 (born 1991- 2000)/20-29 years in 2000 (born 1971- 1980) 1990?, 2000NUTS 2

23. Average Score on Indirect Depopulation Indicators 2000

24. ESPON 1.1.4 Main preliminary results WP5: Ageing, labour shortage and “replacement migration” In an initial phase Two types of problems: Ageing Labour shortage Case studies with regard to e.g. labour shortage (not decided yet) Regions dominated by labour-intensive production Regions dominated by labour-intensive service production (e.g. elderly care) Metropolitan areas (specialists, low-skilled, different segments) Political controversial topic!

25. A simple model with regard to ageing, labour shortage and “replacement migration”

26. Ageing labour force 2000

27. Labour Force Replacement Ratio 2000

28. Av few tentative policy recommendations Difficult at this stage - still only “qualified” guesses Close the gap in living conditions (in a wider sense) between regions and nations Stimulate regional enlargement – larger local labour markets Better accessibility To get rid of the labour shortage – stimulate higher female labour force participation Stimulate child care – higher birth rates Don't hamper mobility – mobility is a lubricant in economic development and transformation

29. Challenges for the next phase - TIR Points of departure: SIR, Addendum, Common Platform Complete the data set Add data - new data, better data Refine the indicators More sophisticated analyses Develop and refine the typologies The temporal dimension will be more pronounced A dynamic approach – processes more explicitly analysed Replacement migration (ageing, labour shortage) - more explicitly analysed More explicit policy implications and recommendations

30. End of the show – thanks for your attention!