Estimation of Simultaneous Linear Equation Models with Error Components Structure PDF Download

Author: Jayalakshmi Varadharajan
Publisher:
ISBN:
Category :
Languages : en
Pages : 64

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Author: Jayalakshmi Krishnakumar
Publisher: Springer Science & Business Media
ISBN: 3642456472
Category : Business & Economics
Languages : en
Pages : 371

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Economists can rarely perform controlled experiments to generate data. Existing information in the form of real-life observations simply has to be utilized in the best possible way. Given this, it is advantageous to make use of the increasing availability and accessibility of combinations of time-series and cross-sectional data in the estimation of economic models. But such data call for a new methodology of estimation and hence for the development of new econometric models. This book proposes one such new model which introduces error components in a system of simultaneous equations to take into account the temporal and cross-sectional heterogeneity of panel data. After a substantial survey of panel data models, the newly proposed model is presented in detail and indirect estimations, full information and limited information estimations, and estimations with and without the assumption of normal distribution errors. These estimation methods are then applied using a computer to estimate a model of residential electricity demand using data on American households. The results are analysed both from an economic and from a statistical point of view.

Author: James McConnell Brundy
Publisher:
ISBN:
Category :
Languages : en
Pages : 298

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Author: Karl G. Jöreskog
Publisher: Springer
ISBN: 3319331531
Category : Mathematics
Languages : en
Pages : 561

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This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis.

Author: Vincent J. Geraci
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 342

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Author: Charles Stockton Roehrig
Publisher: Routledge
ISBN: 1351140515
Category : Business & Economics
Languages : en
Pages : 146

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Originally published in 1984. This book brings together a reasonably complete set of results regarding the use of Constraint Item estimation procedures under the assumption of accurate specification. The analysis covers the case of all explanatory variables being non-stochastic as well as the case of identified simultaneous equations, with error terms known and unknown. Particular emphasis is given to the derivation of criteria for choosing the Constraint Item. Part 1 looks at the best CI estimators and Part 2 examines equation by equation estimation, considering forecasting accuracy.

Author: Phoebus J. Dhrymes
Publisher: Springer Science & Business Media
ISBN: 1461243025
Category : Business & Economics
Languages : en
Pages : 411

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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.

Author: Donald J. Wyhowski
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 354

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Author: Y. P. Gupta
Publisher: Gower Publishing Company, Limited
ISBN:
Category : Econometrics
Languages : en
Pages : 130

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Author: Terrence Kinal
Publisher:
ISBN:
Category :
Languages : en
Pages :

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