Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/82890 
Year of Publication: 
2001
Series/Report no.: 
Working Paper No. 2001:13
Publisher: 
Uppsala University, Department of Economics, Uppsala
Abstract: 
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). <p> 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. <p>
Subjects: 
Micro simulation
Ceteris paribus assumption
Large scale modeling
Calibration
Constrained estimation
Validation
Method of simulated moments
JEL: 
B40
C50
Document Type: 
Working Paper

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