Efficient Simulation-Based Minimum Distance Estimation and Indirect Inference
AbstractGiven a random sample from a parametric model, we show how indirect inference estimators based on appropriate nonparametric density estimators (i.e., simulation-based minimum distance estimators) can be constructed that, under mild assumptions, are asymptotically normal with variance-covarince matrix equal to the Cramér-Rao bound.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 16608.
Date of creation: Mar 2009
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Simulation-based minimum distance estimation; indirect inference;
Find related papers by JEL classification:
- C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
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