Generalized Method of Moments Estimation
By: Mátyás, László (ed.)
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Material type: 
BookSeries: Themes in Modern Econometrics. Publisher: Cambridge, Cambridge University Press, 1999Description: 316 pages.ISBN: 0-521-66967-7.Subject(s): econometrics | estimation | generalized method of moments (GMM) estimation | panel data modelsGenre/Form: text bookOnline resources: Publisher's website Summary: 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 mathemat
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| Anthology | Library | C4 19 (Browse shelf) | Available | 40358 |
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 mathemat
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