1. SIMULATION MODELS 1 st Week INTRODUCTION Master économie Internationale et Développement Université Paris Dauphine Dr. Rafael de Arce Professeur Univ. Autónoma de Madrid http://www.uam.es/rafael.dearce

2. WHY DO POLICY-MAKERS NEED MODELS? Reference paper: Piermartini, R. and Teh, R. (2005): “Demystifying Modelling Methods for Trade Policy”. WTO Discussion Papers, num. 10. September, 2005. Economic models provide a theoretically consistent, rigorous and quantitative way of evaluating different policy analysis. Multiple options, multiple actors. A simulation of the model can confirm that judgment and provide estimate of the likely gains Models can alert about effects in inter-related issues But, what’s first? “The tail shouldn’t wag the dog” Master économie Internationale et Développement, Université Paris Dauphine

3. WHY DO POLICY-MAKERS NEED MODELS?

5. EXPONENTIAL GROWTH  Largeness and wideness Statistical collection (“Big data and Macro/Micro data availability)  Increase of Computational power  Advances in theoretical analysis Master économie Internationale et Développement, Université Paris Dauphine

8. Moore Law “Sylicone chip procesor doubles its capacity in 18 months....”

9. STRENGTHS Reflects Inter-dependency of economic variables Computer based models allow us to track all of these interactions Simulation of several scenarios is available Simulations are performed in a transparent hypothesis frame They discipline thinking about how economies actually work Master économie Internationale et Développement, Université Paris Dauphine

10. LIMITATIONS Aggregations can obscure important underlying relationships Data are not always “high quality” All the quantitative models are subject to error Responsiveness of supply and demand to price changes are not necessarily accurate Choices among scenarios and model specification can imply very different results Technical comprehension is only available for experts Master économie Internationale et Développement, Université Paris Dauphine

11. CHOICE THE MODEL  COMPARATIVE STATIC AND DYNAMIC ANALYSIS Static: changes in policies and direct transmission to endogenous variables of model Dynamic: final and intermediate process of change  PARTIAL OR GENERAL EQUILIBRIUM ANALYSES “Ceteris Paribus” criteria Whole economy linkages Master économie Internationale et Développement, Université Paris Dauphine

12. Reference paper: Piermartini, R. and Teh, R. (2005): “Demystifying Modelling Methods for Trade Policy”. WTO Discussion Papers, num. 10. September, 2005. Whole economy linkages

13. KIND OF THECNICAL STRATEGIES FREQUENTLY USED IN INTERNATIONAL SIMULATIONS Traditional Econometric Multiequational Models Optimization Models Gravity Models Panel Data Models Leontief Based Models (I-O Models) Social Account Matrix Models Master économie Internationale et Développement, Université Paris Dauphine

14. Exogenous  Endogenous Relationship Optimization: –One target function –Constraints to be accomplished –Linear and non linear available linkages –Sometimes, more than one solution (local optimum) Master économie Internationale et Développement, Université Paris Dauphine

15. Exogenous  Endogenous Relationship Gravity Models: Example: Gravity Panel Data Model used in Arce and Mahia (2008): “DETERMINANTS OF BILATERAL IMMIGRATION FLOWS BETWEEN THE EUROPEAN UNION AND SOME MEDITERRANEAN PARTNER COUNTRIES: ALGERIA, EGYPT, MOROCCO, TUNISIA AND TURKEY”. FEMISE 2008: Master économie Internationale et Développement, Université Paris Dauphine

16. Exogenous  Endogenous Relationship: Leontief Based Models (I-O Models) and Computable General Equilibrium (CGM): –Actors –Activities –Commodities –Factors –Enterprises –Households –Government –Capital Account –Rest of the World –Behavioral parameters –Elasticity of producers and consumers to price changes –Value Added –Armington –Demand/income Master économie Internationale et Développement, Université Paris Dauphine

17. SAM Structure

18. “The most important thing between the screen and the keyboard is the person who is in the middle of them.”