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Poland: Building Economic Modeling Capacity for Climate Policy Analysis Leszek Kąsek, Senior Economist, The World Bank, Warsaw Office Edward Basiński,

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Presentation on theme: "Poland: Building Economic Modeling Capacity for Climate Policy Analysis Leszek Kąsek, Senior Economist, The World Bank, Warsaw Office Edward Basiński,"— Presentation transcript:

1 Poland: Building Economic Modeling Capacity for Climate Policy Analysis Leszek Kąsek, Senior Economist, The World Bank, Warsaw Office Edward Basiński, Advisor, Ministry of Finance, Poland Western Balkans Climate Resilience Workshop Vienna, May 11-12, 2016

2  Objective of the modeling project  Complex policy questions  State-of-the-art economic and sectoral models  Innovation Comprehensiveness Collaboration Transparency Contents

3  Create solid in-house modeling capacity for low-emissions growth analysis  Sustainable  Formalized  Transparent  Inter-connected system enabling efficient analysis of climate policies by the public administration in Poland Objective

4  Long-term business-as-usual (baseline) growth path  Global, EU and national energy and climate policy  GHGs emissions reduction potential by sectors  Technical abatement potential and cost  Economic and fiscal consequences  Impact on poverty and income distribution Complex policy questions

5 Historical perspective (Kaya/LMDI decomposition) Source: World Bank staff calculations based on WIOD database.

6 Complex policy questions Starting point

7 Global CGE model for Poland in GAMS (PLACE) Questions: global, EU policies Data: global I-O from GTAP8 and WIOD Output: results for Poland and other regions Example: ROCA, GEM-E3 model National CGE model for Poland in GAMS (PLANE) Questions: national, sectoral policy Data: national I-O from the CSO and sectoral balances Output: results for Poland Example: MEMO, PLANE, Remind-D model, MakMod (National) interlinked sectoral models (PL- ENER) Question: sectoral, reallocation effects Coverage: energy, transport, others Example: MARKAL/Times, Primes, NEMS Micro simulations model Questions: poverty and distribution effect Data: Households budget survey Built upon existing MOF model Toolbox for Poland, but with the EU dimension

8 Comprehensiveness

9 Approach to uncertainty  Model transparency - the need to present uncertainty of model outcomes and its sources  Uncertainty: model specification, parameters, data - systematic sensitivity analysis of parameters  Empirical validation of CGE and sectoral models is a huge undertaking  Results interpretation and drivers -assumptions drive results -reflection of policy priorities and preferences

10 Collaboration

11 Thank you Questions?

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