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Basic structure of the asymptotic theory in dynamic nonlinear econometric models
Authors:Benedikt M Pötscher  Ingmar R Prucha
Institution:Department of Economics , University of Maryland , College Park, 20742, MD
Abstract:This is the second of two papers that provide an expository discussion of the basic structure of the asymptotic theory of M-estimators in dynamic nonlinear models and a review of the literature. The first paper, Pötscher and Prucha(1991), deals with consistency. In the present paper we discuss asymptotic normality. As an important ingredient to the asymptotic normality proof in dynamic nonlinear models we consider central limit theorems for dependent random variables. We also discuss the estimation of the variance covariance matrix of m-estimators under heteroscedasticity and autocorrelation.
Keywords:dynamic nonlinear econometric models  least mean distance estimators  generalized method of moments estimators  asymptotic normality  central limit theorems  variance covariance matrix estimators  mixing processes
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