Generalized Method of Moments
Seiten
2004
Oxford University Press (Verlag)
978-0-19-877521-8 (ISBN)
Oxford University Press (Verlag)
978-0-19-877521-8 (ISBN)
Generalized Method of Moments (GMM) has become one of the main statistical tools for the analysis of economic and financial data. This book provides an introduction to the method combined with a unified treatment of GMM statistical theory and a survey of the important developments in the field.
Generalized Method of Moments (GMM) has become one of the main statistical tools for the analysis of economic and financial data. This book is the first to provide an intuitive introduction to the method combined with a unified treatment of GMM statistical theory and a survey of recent important developments in the field. Providing a comprehensive treatment of GMM estimation and inference, it is designed as a resource for both the theory and practice of GMM: it discusses and proves formally all the main statistical results, and illustrates all inference techniques using empirical examples in macroeconomics and finance.
Building from the instrumental variables estimator in static linear models, it presents the asymptotic statistical theory of GMM in nonlinear dynamic models. Within this framework it covers classical results on estimation and inference techniques, such as the overidentifying restrictions test and tests of structural stability, and reviews the finite sample performance of these inference methods. And it discusses in detail recent developments on covariance matrix estimation, the impact of model misspecification, moment selection, the use of the bootstrap, and weak instrument asymptotics.
Generalized Method of Moments (GMM) has become one of the main statistical tools for the analysis of economic and financial data. This book is the first to provide an intuitive introduction to the method combined with a unified treatment of GMM statistical theory and a survey of recent important developments in the field. Providing a comprehensive treatment of GMM estimation and inference, it is designed as a resource for both the theory and practice of GMM: it discusses and proves formally all the main statistical results, and illustrates all inference techniques using empirical examples in macroeconomics and finance.
Building from the instrumental variables estimator in static linear models, it presents the asymptotic statistical theory of GMM in nonlinear dynamic models. Within this framework it covers classical results on estimation and inference techniques, such as the overidentifying restrictions test and tests of structural stability, and reviews the finite sample performance of these inference methods. And it discusses in detail recent developments on covariance matrix estimation, the impact of model misspecification, moment selection, the use of the bootstrap, and weak instrument asymptotics.
Alastair R. Hall is Professor of Economics at North Carolina State University, where he has taught since 1985. He has also visited at the University of Pennsylvania, the University of Wisconsin-Madison's Graduate School of Business, and at the University of Birmingham.
1. Introduction ; 2. The Instrumental Variable Estimator in the Linear Regression Model ; 3. GMM Estimation in Correctly Specified Models ; 4. GMM Estimation in Misspecified Models ; 5. Hypothesis Testing ; 6. Asymptotic Theory and Finite Sample Behaviour ; 7. Moment Selection in Theory and in Practice ; 8. Alternative Approximations in Finite Sample Behaviour ; 9. Empirical Examples ; 10. Related Methods of Estimation ; Appendix: Mixing processes and Nonstationarity
| Erscheint lt. Verlag | 23.12.2004 |
|---|---|
| Reihe/Serie | Advanced Texts in Econometrics |
| Zusatzinfo | numerous figures |
| Verlagsort | Oxford |
| Sprache | englisch |
| Maße | 164 x 241 mm |
| Gewicht | 747 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik |
| Wirtschaft ► Volkswirtschaftslehre ► Ökonometrie | |
| ISBN-10 | 0-19-877521-0 / 0198775210 |
| ISBN-13 | 978-0-19-877521-8 / 9780198775218 |
| Zustand | Neuware |
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