Estimation of Simultaneous Equation Models with Error Components Structure

Jayalakshmi Krishnakumar

ISBN 10: 3540500316 / ISBN 13: 9783540500315

Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 1988, 1988

Beschreibung

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 376 pp. Englisch.

Bestandsnummer des Verkäufers 9783540500315

Bibliografische Details

• Titel: Estimation of Simultaneous Equation Models with Error Components Structure
• Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 1988
• Erscheinungsjahr: 1988
• Sprache: Englisch
• ISBN-10: 3540500316
• ISBN-13: 9783540500315
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

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.