Generalized method of moments estimation

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Bibliographic Information

Generalized method of moments estimation

László Mátyás, editor

（Themes in modern econometrics）

Cambridge University Press, 1999

  • : hard
  • : pbk

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Includes bibliographical references and index

Description and Table of Contents

Description

The generalized method of moments (GMM) estimation has emerged as providing a ready to use, flexible tool of application to a large number of econometric and economic models by relying on mild, plausible assumptions. The principal objective of this volume is to offer a complete presentation of the theory of GMM estimation as well as insights into the use of these methods in empirical studies. It is also designed to serve as a unified framework for teaching estimation theory in econometrics. Contributors to the volume include well-known authorities in the field based in North America, the UK/Europe, and Australia. The work is likely to become a standard reference for graduate students and professionals in economics, statistics, financial modeling, and applied mathematics.

Table of Contents

  • Preface
  • 1. Introduction to the generalized method of moments estimation David Harris and Laszlo Matyas
  • 2. GMM estimation techniques Masao Ogaki
  • 3. Covariance matrix estimation Matthew J. Cushing and Mary G. McGarvey
  • 4. Hypothesis testing in models estimated by GMM Alastair R. Hall
  • 5. Finite sample properties of GMM estimators and tests Jan M. Podivinsky
  • 6. GMM estimation of time series models David Harris
  • 7. Reduced rank regression using GMM Frank Kleibergen
  • 8. Estimation of linear panel data models using GMM Seung C. Ahn and Peter Schmidt
  • 9. Alternative GMM methods for nonlinear panel data models Joerg Breitung and Michael Lechner
  • 10. Simulation based method of moments Roman Liesenfeld and Joerg Breitung
  • 11. Logically inconsistent limited dependent variables models J. S. Butler and Gabriel Picone
  • Index.

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