Micro simulation involves modeling the behavior of individuals and other decision units taking into account the effects of policy parameters such as tax rates, eligibility rules for benefits and subsidies and compensation rates in the social security system. The model is simulated to analyze the impact of policy changes not only on mean behavior but also on the entire distribution of target variables. Micro simulation models have thus, for instance, been used to analyze how changes in the income taxes influence the tails of the income distribution (the incidence of poverty).
Micro simulation complements a more traditional economic analysis both of which have pros and cons. Micro simulation is demanding in terms of modeling effort, data requirements and computer capacity. The issues of statistical inference related to micro simulation are in principle no different from those in econometric modeling generally. In practice the large scale and complex structure of a typical micro simulation model and the shortage of good micro data raise inference issues of particular relevance for micro simulation such as the choice of estimation criteria, calibration to benchmarks and model validation. Some of these issues are discussed in this paper.
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Paper provided by Uppsala University, Department of Economics in its series Working Paper Series with number
2001:13.
Length: 29 pages Date of creation: 07 May 2001 Date of revision: Handle: RePEc:hhs:uunewp:2001_013
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Find related papers by JEL classification: B40 - Schools of Economic Thought and Methodology - - Economic Methodology - - - General C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
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