Presentation on theme: "ET2050 Meta Analysis of Model Results Michael Wegener ET2050 TPG Meeting, Brussels, 18-19 February 2014."— Presentation transcript:
ET2050 Meta Analysis of Model Results Michael Wegener ET2050 TPG Meeting, Brussels, February 2014
2 Meta Analysis
3 Meta analysis method The co-ordinated application of several complex socio-economic models to a common task is a unique opportunity to cross-validate the models, i.e. to check their validity by comparing their results.
4 Meta analysis method The comparison between scenarios is difficult because of different forecasting horizons different theoretical logics of the models different assumptions about external trends different assumptions about policies These difficulties can be overcome by standardi- sation of indicators, e.g. by comparing average annual change rates differences to reference scenario
5 Meta analysis method A meta analysis of scenario results treats scenarios as observations with attributes distinguishes between input and output attributes explores cause-effect relationships between input and output attributes applies univariate/multivariate statistical analyses
6 Meta analysis method The full application of the meta analysis method is not possible in ET2050 because only two (three) models are available no information on input variables are available Therefore only the results of two models, for which comparable results are available, can be compared and the reasons for the differences between them discussed.
7 Economic Development
8 Economic development GDP change all scenarios MASST v. SASI (% p.a.)
9 Economic development The GDP results of the MASST and SASI models differ in two respects: In MASST it is assumed that the most crisis- stricken countries in southern Europe will suffer from high inflation and taxation and continue to stagnate economically. In SASI it is assumed that all countries will continue to grow, though more slowly than before the crisis, and that the new member states will catch up in productivity. These differences are visible in all scenarios.
10 Economic development GDP change Baseline scenarios MASST v. SASI (% p.a.)
11 Economic development GDP change Baseline scenario MASST v. ECFIN (% p.a.)
12 Economic development GDP change Baseline scenario SASI v. ECFIN (% p.a.)
13 Economic development GDP change ECFIN v. OECD (% p.a.)
14 Economic development The MASST and SASI models differ with respect to the eastern and southern countries: MASST is more pessimistic with respect to the southern countries SASI is more optimistic with respect to the eastern countries. Both models therefore differ from the forecasts of DG ECFIN and the OECD. Also the economic forecasts of ECFIN and OECD differ from each other.
15 Population Development
16 Population development GDP change MULTIPOLES v. MASST (% p.a.)
17 Population development Population change MASST v. SASI (% p.a.)
18 Population development Population change Baseline scenarios MULTIPOLES v. ECFIN (% p.a.)
19 Population development Population change Baseline scenario MASST v. ECFIN (% p.a.)
20 Population development Population change Baseline scenario SASI v. ECFIN (% p.a.)
21 Population development Net migration all scenarios MULTIPOLES v. SASI (%)
22 Population development Population forecasts can be compared between three models (MULTIPOLES, MASST and SASI) and the 2012 Ageing Report by DG ECFIN: The population forecasts by MULTIPOLES are very similar to those of ECFIN. The population forecasts by MASST differ from those of MULTIPOLES through their different assumptions about migration. The population forecasts by SASI differ from both MULTIPOLES and MASST by its much larger net migration.
24 Conclusions If we had wanted to present a common Baseline scenario, we should have conducted this meta analysis earlier. However, it is also possible to interprete the two perspectives as two fundamental options for the future of the European project. Compared with these fundamental options, the spatial scenarios make no great difference. Even in the optimistic option, the absolute gap in income between EU15 and EU12 is becoming wider.
25 Conclusions GDP gap GDP gap
26 More information European Commission: The 2012 Ageing Report. Economic and Budgetary Projections for the 27 EU Member States ( ). Brussels: DG Economic and Financial Affairs. _economy/2012/pdf/ee _en.pdf OECD (2012): Looking to 2060: A Global Vision of Long-Term Growth. Economics Department Policy Note 15. Paris: OECD. Wegener, M. (2010): Meta Analysis of Scenario Results. Technical Note S&W STEPs 03. Dortmund: Spiekermann & Wegener Stadt- und Regionalforschung. spiekermann-wegener.de/pro/pdf/SuW_STEPs_03.pdf