Efficient Simulation-Based Minimum Distance Estimation and Indirect Inference

Given 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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Year of publication:	2009-03
Authors:	Nickl, Richard ; Pötscher, Benedikt M.
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	Simulation-based minimum distance estimation \| indirect inference

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Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C01 - Econometrics
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005078668