1. Macro-economic Impact of Migrations in Madrid Region INTRODUCTION Centre of Migration Research, Warsaw, November 2007 Dr. Mahía & Dr. de Arce Professors Univ. Autónoma de Madrid

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 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?

3. EXPONENTIAL GROWTH  Advances in theoretical analysis  Largeness and wideness Statistical collection  Increase of Computational power

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

5. LIMITATIONS Aggregations can obscure important underlying relationships Data are not always “high quality” 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 Reference paper: Piermartini, R. and Teh, R. (2005): “Demystifying Modelling Methods for Trade Policy”. WTO Discussion Papers, num. 10. September, 2005.

6. 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

7. KIND OF THECNICAL STRATEGIES FREQUENTLY USED IN INTERNATIONAL SIMULATIONS Traditional Econometrical Multiequational Models Optimization Models: Izquierdo, M., Jimeno, JF. and Rojas, JA (2007): “On the Aggregate Effects of Immigration in Spain”. Banco de España Working Papers. Gravitational Models Panel Data Models Leontief Based Models (I-O Models): Vicens et al. (2005): “Impacto Macroeconómico de la Inmigración en la Comunidad de Madrid”. Social Account Matrix Models

8. Inmigration Model “Comunidad de Madrid 2005” STARTING POINT More than 12% of Employed population are immigrants in Comunidad de Madrid Majority of immigrants have come to CM in last five years Estimation of economic aspects of immigration in Spanish Comunidad de Madrid in last five years

9. TOTAL IMMIGRANTS ESTIMATION FORMAL ECONOMY INFORMAL ECONOMY EMPLOYMENT & WAGES PADRÓNREGULARIZ. LAWOTHER DELPHI PUBLIC SOURCES ASSOCIATIONS EMBASSY ACADEMICALS BRANCHES DESEGREGATION CONSUMPTION BASKET ▲ INPUT TIO PRODUCTION & DEMAND Direct Effect Indirect Effect C O E F. E M P L O Y M E N T ▲ OUTPUT HEALTH EDUCATIONAL OTHER PUBLIC EXPENSES REMITTANCES BRANCHES DISTRIBUTION OF CONSUMPTION YIELD NEW DOMESTIC EMPLOYMENT GENERATION RATIO CONSUMPTION/INVESTMENT IMMIGRANTS CONSUMPTION STRUCTURE Immigration CM Model Schema

10. Main Outputs in CM Model 1)Estimation of the Total Number of Immigrants in “Comunidad de Madrid” 2)Estimation of wages in immigrant population (sector distribution and formal and informal differences) 3)Simulation Model: An unrealistic Economy without Immigrants – Gosh I-O Model 4)Productivity aspects in the whole economy 5)Firms Margins derived from immigrants activities 6)Indirect Effects in domestic employment derived from immigrants activities (production and consumption) 7)Public sector issues about Immigration: revenues and expenditures. Vital Cycle considerations in Fiscal Balance 8)Remittances of immigrants estimation: domestic financial sector implications and remittances destination considerations

11. Ghosh Supply Model (I) Distribution Coefficients: delivers of sector “i” to sector “j” over total Outputs of sector “i”. Sells structure of each sector (interdependence between sectors)

12. Ghosh Supply Model (and II) Followed from previous coefficients and in the same terms that Leontief Model, we can build one expression to impact from Value Added to Total Production: x' = VA(I-D) -1 +[(Tr+M+Taxes)*D](I-D) -1

13. coefficients of VA and Employment Value Added and Employment Generation from Ghosh Production: Static vs. Dynamic coefficients of VA and Employment

14. I-O Ghosh Model Implementation: Production Effect CHANGES IN VALUE ADDED VECTOR DIRECT PRODUCTION EFECT TOTAL PRODUCTON EFECT DISTRIBUTION BY BRANCHES (Matrix of Distribution Coefficients) Δ EMPLOYMENT Δ PRODUCTION Δ INTERMEDIATE PRODUCTION (Ghosh Inverse (I-D) -1 ) ESTIMATION OF EFFECT ON TRANSFERS, IMPORTS & TAXES Distribution Matrix D x' = VA(I-D)-1 +[(Tr+M+Taxes)*D] (I-D) -1 Δ ADDED VALUE COEFFICIENTS TRANSLATION

15. Leontief I-O Model Implementation: Demand Efect Δ TOTAL PRODUCTION DIRECT DEMAND EFECT INDIRECT DEMAND EFECT DISTRIBUTION BY BRANCHES Δ PRODUCTION / A.V Δ EMPLOYMENT Δ PRODUCTION / A.V. Δ INTERMEDIATE DEMAND (Leontief Inverse) TOTAL DEMAND EFECT: DIRECT + INDIRECTS Δ PRODUCTION / A.V. Δ EMPLOYMENT GROSS SALARIES YIELDTAXESSAVE Δ CONSUMPTION YIELD Δ EMPLOYMENT

16. MAIN RESULTS