Dynamic Nonlinear Econometric Models

Asymptotic Theory

By: Benedikt M. Potscher, Ingmar R. Prucha

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Hardcover | 17 July 1997

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328 Pages

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Many relationships in economics, and also in other fields, are both dynamic and nonlinear. A major advance in econometrics over the last fifteen years has been the development of a theory of estimation and inference for dy namic nonlinear models. This advance was accompanied by improvements in computer technology that facilitate the practical implementation of such estimation methods. In two articles in Econometric Reviews, i.e., P¶tscher and Prucha {1991a,b), we provided -an expository discussion of the basic structure of the asymptotic theory of M-estimators in dynamic nonlinear models and a review of the literature up to the beginning of this decade. Among others, the class of M-estimators contains least mean distance estimators (includ ing maximum likelihood estimators) and generalized method of moment estimators. The present book expands and revises the discussion in those articles. It is geared towards the professional econometrician or statistician. Besides reviewing the literature we also presented in the above men tioned articles a number of then new results. One example is a consis tency result for the case where the identifiable uniqueness condition fails.

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Non-Fiction Mathematics Probability & Statistics Economics Economic Theory & Philosophy Optimisation Game Theory Applied Mathematics Mathematical Modelling Econometrics Economic Statistics

Preface
Introduction	p. 1
Models, Data Generating Processes, and Estimators	p. 9
Basic Structure of the Classical Consistency Proof	p. 15
Further Comments on Consistency Proofs	p. 23
Uniform Laws of Large Numbers	p. 37
Approximation Concepts and Limit Theorems	p. 45
Consistency: Catalogues of Assumptions	p. 79
Basic Structure of the Asymptotic Normality Proof	p. 83
Asymptotic Normality under Nonstandard Conditions	p. 95
Central Limit Theorems	p. 99
Asymptotic Normality: Catalogues of Assumptions	p. 105
Heteroskedasticity and Autocorrelation Robust Estimation of Variance Covariance Matrices	p. 121
Consistent Variance Covariance Matrix Estimation: Catalogues of Assumptions	p. 137
Quasi Maximum Likelihood Estimation of Dynamic Nonlinear Simultaneous Systems	p. 145
Concluding Remarks	p. 171
Proofs	p. 175
References	p. 287
Index	p. 305
Table of Contents provided by Blackwell. All Rights Reserved.

Dynamic Nonlinear Econometric Models

Asymptotic Theory

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Hardcover

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