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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.
This book has become one of the main statistical tools for the
analysis of economic and financial data. Designed for both
theoreticians and practitioners, this book provides a comprehensive
treatment of GMM estimation and inference. All the main statistical
results are discussed intuitively and proved formally, and all the
inference techniques are illustrated using empirical examples in
macroeconomics and finance. 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.
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