Linear Nonlinear Simultaneous Equations by Dhrymes Phoebus (14 results)

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  • Language: English

    Published by Springer, 2011

    1461287316 / 9781461287315

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  • Language: English

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    1461287316 / 9781461287315

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  • Language: English

    Published by Springer, 2011

    1461287316 / 9781461287315

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  • Language: English

    Published by Springer, 1994

    0387941568 / 9780387941561

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  • Language: English

    Published by Springer, 1994

    0387941568 / 9780387941561

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    Condition: Very Good. Slight shelfwear to extremities of bookcovers, previous owners signature on the inside front cover and title page, otherwise fine.

  • Language: English

    Published by Springer 2011-09, 2011

    1461287316 / 9781461287315

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  • Language: English

    Published by Springer, 1994

    0387941568 / 9780387941561

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  • Language: English

    Published by Springer, 1994

    0387941568 / 9780387941561

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  • Language: English

    Published by Springer, 2011

    1461287316 / 9781461287315

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  • Language: English

    Published by Springer, 2011

    1461287316 / 9781461287315

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    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is intended for second year graduate students and professionals who have an interest in linear and nonlinear simultaneous equations mod els. It basically traces the evolution of econometrics beyond the general linear model (GLM), beginning with the general linear structural econo metric model (GLSEM) and ending with the generalized method of mo ments (GMM). Thus, it covers the identification problem (Chapter 3), maximum likelihood (ML) methods (Chapters 3 and 4), two and three stage least squares (2SLS, 3SLS) (Chapters 1 and 2), the general nonlinear model (GNLM) (Chapter 5), the general nonlinear simultaneous equations model (GNLSEM), the special ca'3e of GNLSEM with additive errors, non linear two and three stage least squares (NL2SLS, NL3SLS), the GMM for GNLSEIVl, and finally ends with a brief overview of causality and re lated issues, (Chapter 6). There is no discussion either of limited dependent variables, or of unit root related topics. It also contains a number of significant innovations. In a departure from the custom of the literature, identification and consistency for nonlinear models is handled through the Kullback information apparatus, as well as the theory of minimum contrast (MC) estimators. In fact, nearly all estimation problems handled in this volume can be approached through the theory of MC estimators. The power of this approach is demonstrated in Chapter 5, where the entire set of identification requirements for the GLSEM, in an ML context, is obtained almost effortlessly, through the apparatus of Kullback information.…

  • Language: English

    Published by Springer, 1994

    0387941568 / 9780387941561

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    Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is intended for second year graduate students and professionals who have an interest in linear and nonlinear simultaneous equations mod els. It basically traces the evolution of econometrics beyond the general linear model (GLM), beginning with the general linear structural econo metric model (GLSEM) and ending with the generalized method of mo ments (GMM). Thus, it covers the identification problem (Chapter 3), maximum likelihood (ML) methods (Chapters 3 and 4), two and three stage least squares (2SLS, 3SLS) (Chapters 1 and 2), the general nonlinear model (GNLM) (Chapter 5), the general nonlinear simultaneous equations model (GNLSEM), the special ca'3e of GNLSEM with additive errors, non linear two and three stage least squares (NL2SLS, NL3SLS), the GMM for GNLSEIVl, and finally ends with a brief overview of causality and re lated issues, (Chapter 6). There is no discussion either of limited dependent variables, or of unit root related topics. It also contains a number of significant innovations. In a departure from the custom of the literature, identification and consistency for nonlinear models is handled through the Kullback information apparatus, as well as the theory of minimum contrast (MC) estimators. In fact, nearly all estimation problems handled in this volume can be approached through the theory of MC estimators. The power of this approach is demonstrated in Chapter 5, where the entire set of identification requirements for the GLSEM, in an ML context, is obtained almost effortlessly, through the apparatus of Kullback information.…

  • Language: English

    Published by Springer, 2012

    1461287316 / 9781461287315

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    Paperback. Condition: Brand New. reprint edition. 418 pages. 9.25x6.10x0.96 inches. In Stock.

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    Language: English

    Published by Springer, 2011

    1461287316 / 9781461287315

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    Taschenbuch. Condition: Neu. Topics In Advanced Econometrics | Volume II Linear and Nonlinear Simultaneous Equations | Phoebus J. Dhrymes | Taschenbuch | xviii | Englisch | 2011 | Springer | EAN 9781461287315 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

  • Language: English

    Published by Springer New York, 1994

    0387941568 / 9780387941561

    • Hardcover

    Seller: Buchpark, Trebbin, GermanyBuchpark

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    Condition: Sehr gut. Zustand: Sehr gut | Seiten: 424 | Sprache: Englisch | Produktart: Bücher | This book is intended for second year graduate students and professionals who have an interest in linear and nonlinear simultaneous equations mod­ els. It basically traces the evolution of econometrics beyond the general linear model (GLM), beginning with the general linear structural econo­ metric model (GLSEM) and ending with the generalized method of mo­ ments (GMM). Thus, it covers the identification problem (Chapter 3), maximum likelihood (ML) methods (Chapters 3 and 4), two and three stage least squares (2SLS, 3SLS) (Chapters 1 and 2), the general nonlinear model (GNLM) (Chapter 5), the general nonlinear simultaneous equations model (GNLSEM), the special ca'3e of GNLSEM with additive errors, non­ linear two and three stage least squares (NL2SLS, NL3SLS), the GMM for GNLSEIVl, and finally ends with a brief overview of causality and re­ lated issues, (Chapter 6). There is no discussion either of limited dependent variables, or of unit root related topics. It also contains a number of significant innovations. In a departure from the custom of the literature, identification and consistency for nonlinear models is handled through the Kullback information apparatus, as well as the theory of minimum contrast (MC) estimators. In fact, nearly all estimation problems handled in this volume can be approached through the theory of MC estimators. The power of this approach is demonstrated in Chapter 5, where the entire set of identification requirements for the GLSEM, in an ML context, is obtained almost effortlessly, through the apparatus of Kullback information.…