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Estimation of Simultaneous Equation Models with Error Components Structure

  • Book
  • © 1988

Overview

Authors:
  1. Jayalakshmi Krishnakumar

    1. Dept. of Econometrics, University of Geneva, Geneva 4, Switzerland

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Part of the book series: Lecture Notes in Economics and Mathematical Systems (LNE, volume 312)

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Table of contents (9 chapters)

  1. Front Matter

    Pages N2-X
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  2. Introduction

    • Jayalakshmi Krishnakumar
    Pages 1-5

  3. A Survey of Panel Data Models

    • Jayalakshmi Krishnakumar
    Pages 6-46

  4. Presentation of Simultaneous Equations Model with Error Components Structure and Estimation of the Reduced Form

    • Jayalakshmi Krishnakumar
    Pages 47-119

  5. Estimation of the Structural Form — Part 1

    • Jayalakshmi Krishnakumar
    Pages 120-169

  6. Estimation of the Structural Form — Part 2

    • Jayalakshmi Krishnakumar
    Pages 170-204

  7. The Just-Identified Case and Indirect Estimation of Structural Parameters

    • Jayalakshmi Krishnakumar
    Pages 205-226

  8. Bias of the Feasible Estimators of Reduced Form and Structural Variance Components and Coefficients

    • Jayalakshmi Krishnakumar
    Pages 227-306

  9. Application to a Model of Residential Electricity Demand

    • Jayalakshmi Krishnakumar
    Pages 307-345

  10. Conclusions

    • Jayalakshmi Krishnakumar
    Pages 346-352

  11. Back Matter

    Pages 353-363
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Keywords

About this book

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.

Authors and Affiliations

  • Dept. of Econometrics, University of Geneva, Geneva 4, Switzerland

    Jayalakshmi Krishnakumar

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