Microsimulación como instrumento de evaluación de las políticas públicas

1. Microsimulación como instrumento de evaluación de las políticas públicas Encuentro Fundación BBVA Madrid, 15-16 de noviembre de 2004 Microsimulación, economía ambiental e impuestos indirectos José M. Labeaga UNED, Madrid

2. Our approach will be guided by the sentence: Most public policies have efficiency and distributional effects (and we would like to compute both of them) Ilustration: (environmental) taxes on energy goods

3. Outline 1.Analyzing the efficiency and distributional effects of public policies(needs) 2. Partial equilibrium 1st step(household demand and microsimulation) 3. Partial equilibrium2nd step (input-output analysis plus household demand and microsimulation) 4. General equilibrium(alternatives for integrating a microsimulation model in a macro model) 5. Advantages and disadvantages of CGEM 6. Ilustration 7. Conclusions

4. 1. Analyzing the efficiency and distributional effects of public policies • Some researchers prefer microsimulation models to asses distributional effects of public policies.

5. 1. Analyzing the efficiency and distributional effects of public policies • Some researchers prefer microsimulation models to asses distributional effects of public policies. No possibility to analyze efficiency

6. 1. Analyzing the efficiency and distributional effects of public policies • Some researchers prefer microsimulation models to asses distributional effects of public policies. No possibility to analyze efficiency • Other prefer macro models (CGE, normally bottom-up)

7. 1. Analyzing the efficiency and distributional effects of public policies • Some researchers prefer microsimulation models to asses distributional effects of public policies. No possibility to analyze efficiency • Other prefer macro models (CGE, normally bottom-up) which hide heterogeneity and do not allow to analyze distribution

8. 1. Analyzing the efficiency and distributional effects of public policies • Some researchers prefer microsimulation models to asses distributional effects of public policies. No possibility to analyze efficiency • Other prefer macro models (CGE, normally bottom-up), which hide heterogeneity and do not allow to analyze distribution • We propose a macro model for computing efficiency and also use microdata for distribution (analysis top-down). Same methodology as Bourguignon et al (2003)

9. 1. Analyzing the efficiency and distributional effects of public policies • Some researchers prefer microsimulation models to asses distributional effects of public policies. No possibility to analyze efficiency • Other prefer macro models (CGE, normally bottom-up), which hide heterogeneityand do not allow to analyze distribution • We propose a macro model for computing efficiency and also use microdata for distribution (analysis top-down). Same methodology as Bourguignon et al (2003) • Both approaches have advantages and disadvantages

10. 2. Partial equilibrium 1st step • Standard approaches to analyze distributional issues with microdata • Arithmetic models (morning after effects of policy reforms) • Behavioural models (adjustments after policy reforms)

11. 2. Partial equilibrium 1st step • Standard approaches to analyze distributional issues with microdata • Arithmetic models (morning after effects of policy reforms) • Behavioural models (adjustments after policy reforms) • Problem for analyzing efficiency issues

12. Microsimulation frameworkWhat is a microsimulation model? • Tool that works with the characteristics (and behavior) of microeconomic units (individuals or households) and examine policy impacts at the micro level • In order to provide information at the macro level (revenue, for instance), results at the micro level are aggregated using grossing up factors • Comparisons micro–micro (pre–post) and micro– macro

13. Standard structure of a microsimulation model Simulation Population of departure Population after changes Comparison Aggregation of individual situations Aggregation of individual situations Comparison

14. Standard structure of a behavioural microsimulation model Simulation Econometric model Population of departure Population after changes Comparison Aggregation of individual situations Aggregation of individual situations Comparison

15. Advantages of microsimulation? • Dynamic versus static • Take account of reactions • Analyze cause for these reactions • Micro versus macro • Take into account heterogeneity of individuals • Avoid using the representative agent assumption • Ex-ante versus ex-post • Counterfactual analysis • Ex-post and ex-ante policy evaluation possible

16. Applications • Distributional impact of microeconomic policies • fiscal reforms • subsidies/transfers • public spending on health • employment programs • Distributional impact of macroeconomic policies or demographic changes • shocks (petrol, exchange rates) • pensions, illnesses

17. Steps to construct a microsimulation model • The data base (key aspect) • Economic framework • Microeconometric model (or macro – micro) • Model validation (both at the micro and macro levels) • Simulations and sensitivity analysis • Analysis of results • How does the model work in reality?

18. Household demand and microsimulation:an example • The first level simulation corresponds to the arithmetic case. But, we only focus on behavioural models. For the second level situation (incorporating behaviour) we need: • Economic model • Simulation method • Results

19. Household demand and microsimulation:advantages and disadvantages • Relatively easy to implement and to use. The only difficulty (?) is the adjustment of a microeconometric model (results crucially depend on a good adjustment)

20. Household demand and microsimulation:disadvantages and advantages • Relatively easy to implement and to use. The only difficulty (?) is the adjustment of a microeconometric model (results crucially depend on a good adjustment) • Only analysis of direct effects of public policies • We do not account for relationship among industries, which could react to taxes and change their structure of production and, as a result, the final effects of taxes on the different prices (direct and indirect) of the goods

21. 3. Parcial equilibrium 2nd step • Input-output methodology, household demand and microsimulation. This is the second level situation and corresponds to the case where we consider relationships among sectors (it is not GE). We need: • Input – output model (We impose a carbon tax and compute the effects on prices using an input-output demand model) • Economic model (as before) • Simulation method (as before withcorrespondence to IO) • Results (as before with adjustment)

22. Household demand, input-output model and microsimulation: inconvenients and advantages • Relatively easy to implement and to use (as before) • We do account for relationship among industries in order to compute price changes, in a simple way

23. Household demand, input-output model and microsimulation: inconvenients and advantages • Relatively easy to implement and to use (as before) • We do account for relationship among industries in order to compute price changes, in a simple way • Still partial equilibrium • IO models are static in the sense that they do not include any sort of behaviour

24. 4. General equilibrium • The same situation as before, but we use a Computable General Equilibrium Model at the first step • Only tool that can make a comprehensive evaluation of public policies on the economy? • Price changes after a tax are computed in the context of this CGEM

25. Integration of micro and macro models • Approach 1. Heterogeneity within the CGEM • Approach 2. Bottom-up (integrated or not) • Approach 3. Top-down (integrated or not) • Recent antecedents: Bourguignon, Robilliard and Robinson (2003) • Our example: transmission of the price changes on energy goods from macro to microsimulation model

26. CGEM • Our CGEM • Integration of micro and macro models

27. The integrated micro-macro model Computable General Equilibrium Model - Goods and expenditure: x - Prices: p - Production and emissions: Y, CO2 - All other variables: OV Microeconometric model (based on the ECPF) - Socio demographic characteristics: Zi - Demand equations: wi = f(Zi pi xi ) - Output (input for the microsim tool):  • Microsimulation tool (based on the ECPF) • - Socio demographic characteristics: Zi • Welfare equations (EV, CV): EVi =g(Zi pi xi ) • Outcomes: redistribution measures based on Zi

28. The integrated micro-macro model: advantages and disadvantages • Advantages • Theoretical consistency micro-macro model • Efficiency and distribution measures • Disadvantages • Simple CGEM (if it is not, very complicated and time consuming) • Data should be carefully taken • Results depend on econometric model

29. 6. Ilustration • Inputs • Parameters from the economic model • Changes in prices from the CGEM (given the process explained) • Outputs • Results on efficiency • Results on distribution

30. 7. Conclusions • Are useful microsimulation tools? • Are necessary microsimulation models? • Examples show (I think): • Importance of heterogeneity • Importance of results for policy (ex-ante) • What is still missing in these models? • Macro and distribution effects of government spending • Long run vs. short run

31. 7. Conclusions • Fully integrated models (CGEM with full heterogeneity) • Dynamic CGEM • Include firm microdata • Etc, etc, etc……….

32. THE END