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Basic structure of the asymptotic theory in dynamic nonlinear econometric models

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Author Info
Benedikt Pötscher
Ingmar Prucha

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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.

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File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/07474939108800209&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
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Publisher Info
Article provided by Taylor and Francis Journals in its journal Econometric Reviews.

Volume (Year): 10 (1991)
Issue (Month): 3 ()
Pages: 253-325
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Handle: RePEc:taf:emetrv:v:10:y:1991:i:3:p:253-325

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Related research
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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