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Dynamic Nonlinear Econometric Models

Asymptotic Theory

  • Book
  • © 1997

Overview

Authors:
  1. Benedikt M. Pötscher

    1. Department of Statistics, Operations Research and Computer Science, University of Vienna, Vienna, Austria

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  2. Ingmar R. Prucha

    1. Department of Economics, University of Maryland at College Park, College Park, USA

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    You can also search for this author in PubMed   Google Scholar

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xi
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  2. Introduction

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 1-7

  3. Models, Data Generating Processes, and Estimators

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 9-13

  4. Basic Structure of the Classical Consistency Proof

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 15-21

  5. Further Comments on Consistency Proofs

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 23-35

  6. Uniform Laws of Large Numbers

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 37-44

  7. Approximation Concepts and Limit Theorems

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 45-77

  8. Consistency: Catalogues of Assumptions

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 79-82

  9. Basic Structure of the Asymptotic Normality Proof

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 83-93

  10. Asymptotic Normality under Nonstandard Conditions

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 95-98

  11. Central Limit Theorems

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 99-103

  12. Asymptotic Normality: Catalogues of Assumptions

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 105-120

  13. Heteroskedasticity and Autocorrelation Robust Estimation of Variance Covariance Matrices

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 121-136

  14. Consistent Variance Covariance Matrix Estimation: Catalogues of Assumptions

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 137-143

  15. Quasi Maximum Likelihood Estimation of Dynamic Nonlinear Simultaneous Systems

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 145-169

  16. Concluding Remarks

    • Benedikt M. Pötscher, Ingmar R. Prucha
    Pages 171-173

  17. Back Matter

    Pages 175-312
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Keywords

About this book

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., Pötscher 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.

Authors and Affiliations

  • Department of Statistics, Operations Research and Computer Science, University of Vienna, Vienna, Austria

    Benedikt M. Pötscher

  • Department of Economics, University of Maryland at College Park, College Park, USA

    Ingmar R. Prucha

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