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Generalized Method of Moments Estimation

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Generalized Method of Moments Estimation

Generalized Method of Moments Estimation

Laszlo Matyas, Budapest University of Economic Sciences
April 1999
Available
Paperback
9780521669672
    Description

    The generalized method of moments (GMM) estimation has emerged over the past decade 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, the first devoted entirely to the GMM methodology, is to offer a complete and up to date 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.

    • Examines a quickly developing area of economics
    • Written by well-known experts in the field and is using a unified language, notation, so it is likely to become the standard reference book in the area
    • It can also be used as a textbook in advanced econometric theory courses

    Product details

    February 2011
    Adobe eBook Reader
    9780511825651
    0 pages
    0kg
    14 tables
    This ISBN is for an eBook version which is distributed on our behalf by a third party.

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    Contents

    Table of Contents

    • Preface
    • 1. Introduction to the generalized method of moments estimation David Harris and László Mátyás
    • 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 Jörg Breitung and Michael Lechner
    • 10. Simulation based method of moments Roman Liesenfeld and Jörg Breitung
    • 11. Logically inconsistent limited dependent variables models J. S. Butler and Gabriel Picone
    • Index.
      • Show more
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    Additional Information
    About the authors
      Contributors

    • David Harris, László Mátyás, Masao Ogaki, Matthew J. Cushing, Mary G. McGarvey, Alastair R. Hall, Jan M. Podivinsky, Frank Kleibergen, Seung C. Ahn, Peter Schmidt, Jörg Breitung, Michael Lechner, Roman Liesenfeld, J. S. Butler, Gabriel Picone

      • Editor
    • Laszlo Matyas , Budapest University of Economic Sciences

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