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
1
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)
lustration: (environmental) taxes on energy goo
2
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
3
1. Analyzing the efficiency and distributional
effects of public policies

Some researchers prefer microsimulation
models to asses distributional effects of public
policies.
4
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
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
Other prefer macro models (CGE, normally
bottom-up)
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) which hide heterogeneity and do
not allow to analyze distribution
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
We propose a macro model for computing
efficiency and also use microdata for
distribution (analysis top-down). Same
methodology as Bourguignon et al (2003)
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 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
9
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)
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)

Problem for analyzing efficiency issues
11
Microsimulation framework
What 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
12
Standard structure of a
microsimulation model
Simulation
Population of
departure
Aggregation of
individual situations
Comparison
Population after
changes
Comparison
Aggregation of
individual situations
13
Standard structure of a behavioural
microsimulation model
Simulation
Econometric model
Population of
departure
Aggregation of
individual situations
Comparison
Population after
changes
Comparison
Aggregation of
individual situations
14
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
15
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
16
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?
17
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
18
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)
19
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

20
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)
21
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
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
Still partial equilibrium
IO models are static in the sense that
they do not include any sort of behaviour
23
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
24
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
25
CGEM


Our CGEM
Integration of micro and macro
models
26
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
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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
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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
29
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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THE
END
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