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Topics In Advanced Econometrics: Volume Ii Linear And Nonlinear Simultaneou... - edition reliée, livre de poche

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Dhrymes, Phoebus J.:

Topics In Advanced Econometrics: Volume II Linear and Nonlinear Simultaneous Equations - edition reliée, livre de poche

1994, ISBN: 0387941568

[EAN: 9780387941561], Used, very good, [PU: Springer 1994-01-07], Item is in very good condition. If supplemental codes/CDs for textbooks are required please contact us prior to purchasin… Plus…

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Phoebus J. Dhrymes:
Topics in Advanced Econometrics: Volume II Linear and Nonlinear Simultaneous Equations - edition reliée, livre de poche

1994

ISBN: 0387941568

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Dhrymes, Phoebus J.:
Topics In Advanced Econometrics: Volume II Linear and Nonlinear Simultaneous Equations - edition reliée, livre de poche

1994, ISBN: 0387941568

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Dhrymes, Phoebus J.:
Topics In Advanced Econometrics: Volume II Linear and Nonlinear Simultaneous Equations - edition reliée, livre de poche

1994, ISBN: 0387941568

[EAN: 9780387941561], New book, [PU: Springer], Books

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Topics In Advanced Econometrics Hardcover | Indigo Chapters

This textbook is intended for graduate students and professionals who have an interest in linear and nonlinear simultaneous equation models. These models arise in a great many settings in econometrics. The author's aim is to present a readable account, starting from an introduction to the general linear structural econometric model. From there, the book covers the identification problem, maximum likelihood methods, two and three stage least square methods, the general nonlinear model, and more advanced topics such as the general nonlinear simultaneous equations model. The reader is assumed to have a basic background in probability theory but otherwise this account is self-contained.

Informations détaillées sur le livre - Topics In Advanced Econometrics Hardcover | Indigo Chapters


EAN (ISBN-13): 9780387941561
ISBN (ISBN-10): 0387941568
Version reliée
Date de parution: 2007
Editeur: Springer New York
424 Pages
Poids: 0,795 kg
Langue: eng/Englisch

Livre dans la base de données depuis 2007-11-06T17:37:19+01:00 (Paris)
Page de détail modifiée en dernier sur 2023-08-02T20:07:56+02:00 (Paris)
ISBN/EAN: 0387941568

ISBN - Autres types d'écriture:
0-387-94156-8, 978-0-387-94156-1
Autres types d'écriture et termes associés:
Auteur du livre: dhrymes, phöbus
Titre du livre: topics advanced econometrics, linear and nonlinear


Données de l'éditeur

Auteur: Phoebus J. Dhrymes
Titre: Topics In Advanced Econometrics - Volume II Linear and Nonlinear Simultaneous Equations
Editeur: Springer; Springer US
402 Pages
Date de parution: 1994-01-07
New York; NY; US
Poids: 1,700 kg
Langue: Anglais
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
POD
XVIII, 402 p.

BB; Economic Theory/Quantitative Economics/Mathematical Methods; Hardcover, Softcover / Wirtschaft/Volkswirtschaft; Wirtschaftstheorie und -philosophie; Verstehen; econometrics; forecasting; inequality; probability theory; value-at-risk; Quantitative Economics; BC; EA

1 Extension of Classical Methods I.- 1.1 Introduction.- 1.2 A Brief Historical Review.- 1.3 The Nature of the GLSEM.- 1.4 The GLSEM: Assumptions and Notation.- 1.4.1 Assumptions and Conventions.- 1.4.2 Notation.- 1.5 Inconsistency of OLS Estimators.- 1.6 Two Stage Least Squares (2SLS).- 1.6.1 The Original Derivation.- 1.6.2 An Alternative Formulation.- 1.7 Three Stage Least Squares (3SLS).- 1.8 Restricted 2SLS and 3SLS Estimators.- 1.9 Tests of Prior Restrictions.- 1.9.1 Generalities.- 1.9.2 A Restricted Least Squares Interpretation of 2SLS and 3SLS.- Questions and Problems.- Appendix to Chapter 1.- Preliminaries to Hausman’s Test.- Examples.- 2 Extension of Classical Methods II.- 2.1 Limiting Distributions.- 2.1.1 Preliminaries.- 2.1.2 Limiting Distributions for Static GLSEM.- 2.1.3 Limiting Distributions for Dynamic GLSEM.- 2.2 Forecasting from the GLSEM.- 2.2.1 Generalities.- 2.2.2 Forecasting from the URF.- 2.2.3 Forecasting from the RRF.- 2.3 The Vector Autoregressive Model (VAR).- 2.4 Instrumental Variables (IV).- 2.4.1 2SLS and 3SLS as IV Estimators.- 2.4.2 2SLS and 3SLS as Optimal IV Estimators.- 2.5 IV and Insufficient Sample Size.- 2.5.1 The Nature of the Problem.- 2.5.2 Iterated Instrumental Variables (IIV).- 2.6 k-class and Double k-class Estimators.- 2.7 Distribution of LM Derived Estimators.- 2.8 Properties of Specification Tests.- 2.8.1 Single Equation 2SLS.- 2.8.2 Systemwide 2SLS and 3SLS.- 2.8.3 Relation to Hausman’s Test.- Questions and Problems.- Appendix to Chapter 2.- Convergence of Second Moment Matrices.- Convergence for Dependent Sequences.- Preliminaries and Miscellaneous.- Convergence of Second Moments of Final Form Errors.- 3 Maximum Likelihood Methods I.- 3.1 Introduction.- 3.2 The Identification Problem.- 3.2.1 Generalities.- 3.2.2 The Simple Supply-Demand Model.- 3.2.3 Identification by Exclusion Restrictions.- 3.2.4 Identification by Linear Restrictions.- 3.2.5 Identification and the Reduced Form.- 3.2.6 Covariance and Cross Equation Restrictions.- 3.2.7 A More General Framework.- 3.2.8 Parametric Nonlinearities and Identification.- 3.3 ML Estimation of the RF.- 3.3.1 General Discussion and ILS.- 3.3.2 Estimation of the Reduced Form.- 3.4 FIML Estimation.- 3.5 Simplified FIML Estimators.- 3.6 Properties of Simplified Estimators.- 3.6.1 Consistency.- 3.7 Limiting Distribution of FIML.- Questions and Problems.- 4 LIML Estimation Methods.- 4.1 The “Concentrated” Likelihood Function.- 4.1.1 A Subset of m* Structural Equations.- 4.2 The Single Equation LIML Estimator.- 4.3 Consistency of the LIML Estimator.- 4.4 An Interesting Interpretation of LIML.- 4.5 Indirect Least Squares (ILS).- 4.6 Relation of LIML to Other Estimators.- 4.7 Limiting Distribution of LIML Estimators.- 4.8 Classic Identifiability Tests.- Questions and Problems.- Appendix to Chapter 4.- Limiting Distribution of (T? — 1).- 5 Nonlinear ML Methods.- 5.1 Motivation.- 5.2 A Mathematical Digression.- 5.3 Aspects of Likelihood Functions.- 5.3.1 An Interesting Inequality.- 5.4 Fisher Information.- 5.4.1 Alternative Representation of the Information Matrix.- 5.5 The Cramer-Rao Bounds.- 5.6 Martingale Properties of Likelihood Functions.- 5.7 Kullback Information.- 5.8 Convergence A.C. of ML Estimators.- 5.8.1 Independent Observations.- 5.8.2 Generalizations.- 5.9 The General Nonlinear Model (GNLM).- 5.9.1 Consistency.- 5.9.2 Identification.- 5.9.3 Asymptotic Normality.- 5.10 The GNLM with Restrictions.- 5.11 Tests of Restrictions.- 5.11.1 Generalities.- 5.11.2 The Conformity Test.- 5.11.3 The Likelihood Ratio Test.- 5.11.4 The Lagrange Multiplier Test.- 5.11.5 Equivalence of the Three Tests.- Questions and Problems.- 6 Topics in NLSE Theory.- 6.1 Nonlinear ML.- 6.1.1 Identification.- 6.1.2 Consistency of the ML Estimator.- 6.1.3 Limiting Distribution of ML Estimators.- 6.1.4 Relation of Structural and Covariance Parameter (ML) Estimators.- 6.1.5 Estimators in Structurally Misspecified Models.- 6.2 Nonlinear 2SLS.- 6.2.1 Identification and Consistency of NL2SLS.- 6.2.2 Asymptotic Normality of NL2SLS.- 6.2.3 Choice of an Optimal NL2SLS Estimator.- 6.3 Nonlinear 3SLS.- 6.3.1 Identification and Consistency of NL3SLS.- 6.3.2 Asymptotic Normality of NL3SLS.- 6.3.3 Optimum NL3SLS and Computational Aspects.- 6.4 GMM.- 6.4.1 Reformulation of GMM as NL2SLS and NL3SLS.- 6.4.2 Identification and Consistency.- 6.4.3 Asymptotic Normality.- 6.4.4 Tests of Restrictions.- 6.5 Causality and Related Issues.- 6.5.1 Introduction.- 6.5.2 Basic Concepts.- Questions and Problems.

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