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Aggiungi al carrelloPF. Condizione: New.
Condizione: New. pp. 228.
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Aggiungi al carrelloPaperback. Condizione: Brand New. 214 pages. 9.25x6.25x0.75 inches. In Stock.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Generalized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive distributional assumptions and remains computationally attractive when ML estimation becomes burdensome or even impossible. This book presents an in-depth treatment of the conditional moment approach to GMM estimation of models frequently encountered in applied microeconometrics. It covers both large sample and small sample properties of conditional moment estimators and provides an application to empirical industrial organization. With its comprehensive and up-to-date coverage of the subject which includes topics like bootstrapping and empirical likelihood techniques, the book addresses scientists, graduate students and professionals in applied econometrics.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Conditional Moment Estimation of Nonlinear Equation Systems | With an Application to an Oligopoly Model of Cooperative R&D | Joachim Inkmann | Taschenbuch | Lecture Notes in Economics and Mathematical Systems | viii | Englisch | 2000 | Springer | EAN 9783540412076 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: Mispah books, Redhill, SURRE, Regno Unito
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 228.
Lingua: Inglese
Editore: Springer Berlin Heidelberg, 2000
ISBN 10: 3540412077 ISBN 13: 9783540412076
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes supplementary material: sn.pub/extrasGeneralized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive .
Lingua: Inglese
Editore: Springer, J.B. Metzler Nov 2000, 2000
ISBN 10: 3540412077 ISBN 13: 9783540412076
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Generalized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive distributional assumptions and remains computationally attractive when ML estimation becomes burdensome or even impossible. This book presents an in-depth treatment of the conditional moment approach to GMM estimation of models frequently encountered in applied microeconometrics. It covers both large sample and small sample properties of conditional moment estimators and provides an application to empirical industrial organization. With its comprehensive and up-to-date coverage of the subject which includes topics like bootstrapping and empirical likelihood techniques, the book addresses scientists, graduate students and professionals in applied econometrics.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 228 pp. Englisch.
Lingua: Inglese
Editore: Springer Berlin Heidelberg Nov 2000, 2000
ISBN 10: 3540412077 ISBN 13: 9783540412076
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 96,29
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Generalized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive distributional assumptions and remains computationally attractive when ML estimation becomes burdensome or even impossible. This book presents an in-depth treatment of the conditional moment approach to GMM estimation of models frequently encountered in applied microeconometrics. It covers both large sample and small sample properties of conditional moment estimators and provides an application to empirical industrial organization. With its comprehensive and up-to-date coverage of the subject which includes topics like bootstrapping and empirical likelihood techniques, the book addresses scientists, graduate students and professionals in applied econometrics. 228 pp. Englisch.