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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. Our approach will be guided by the sentence:. - PowerPoint PPT Presentation
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Microsimulación como instrumentode evaluación de las
políticas públicas
Encuentro Fundación BBVAMadrid, 15-16 de noviembre de 2004
Microsimulación, economía ambiental e impuestos
indirectos
José M. LabeagaUNED, Madrid
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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
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Outline
1. Analyzing the efficiency and distributional effects of public
policies (needs)
2. Partial equilibrium 1st step (household demand and microsimulation)
3. Partial equilibrium 2nd 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
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1. Analyzing the efficiency and distributional effects of public policies
Some researchers prefer microsimulation models to asses distributional effects of public policies.
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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
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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)
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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
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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)
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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
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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)
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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
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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
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Standard structure of a microsimulation model
Population of departure
Population of departure
Population after changes
Population after changes
Aggregation of individual situations
Aggregation of individual situations
Aggregation of individual situations
Aggregation of individual situations
SimulationSimulation
ComparisonComparison
ComparisonComparison
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Standard structure of a behavioural microsimulation model
Population of departure
Population of departure
Population after changes
Population after changes
Aggregation of individual situations
Aggregation of individual situations
Aggregation of individual situations
Aggregation of individual situations
SimulationSimulation
Econometric modelEconometric model
ComparisonComparison
ComparisonComparison
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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
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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
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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?
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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
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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)
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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
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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 with correspondence to IO) Results (as before with adjustment)
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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
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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
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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
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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
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CGEM
Our CGEM Integration of micro and macro
models
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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):
The integrated micro-macro model
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
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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
The integrated micro-macro model: advantages and disadvantages
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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
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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
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7. Conclusions
Fully integrated models (CGEM with full heterogeneity)
Dynamic CGEM Include firm microdata Etc, etc, etc……….
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ENDTHE