Generalized Method of Moments Estimation

Generalized Method of Moments Estimation

by Laszlo Matyas
ISBN-10:
0521660130
ISBN-13:
9780521660136
Pub. Date:
04/13/1999
Publisher:
Cambridge University Press
ISBN-10:
0521660130
ISBN-13:
9780521660136
Pub. Date:
04/13/1999
Publisher:
Cambridge University Press
Generalized Method of Moments Estimation

Generalized Method of Moments Estimation

by Laszlo Matyas

Hardcover

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Overview

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.

Product Details

ISBN-13: 9780521660136
Publisher: Cambridge University Press
Publication date: 04/13/1999
Series: Themes in Modern Econometrics
Pages: 332
Product dimensions: 6.18(w) x 9.29(h) x 0.94(d)

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.
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