Finite sample properties of GMM estimators and tests
Mátyás, L. (eds.)
Generalized Method of Moments Estimation.
Cambridge University Press
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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;
||The generalized method of moments (GMM) estimation has emerged over the last 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. The work is likely to become a standard reference for graduate students and professionals in economics, statistics, financial modeling, and applied mathematics.
||28 Jun 2007
||16 Apr 2017 22:18
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