Statistical Inference in Random Coefficient Regression Models - Swamy, P. A. V. B.

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Sommaire:
I -- Introduction.- 1.1 Purpose and Outline of the Study.- 1.2 Review of the Literature on Regression Models with Random and Fixed Coefficients.- 1.3 Conclusions.- II -- Efficient Methods of Estimating a Regression Equation with Equicorrelated Disturbances.- 2.1 Introduction.- 2.2 Some Useful Lemmas.- 2.3 A Regression Model with Equicorrelated Disturbances.- 2.4 Analysis of Time Series of Cross-Sections.- 2.5 Estimation When the Variance-Covariance Matrix of Disturbances is Singular.- 2.6 Estimation When the Remaining Effects are Heteroskedastic.- 2.7 Conclusions.- III -- Efficient Methods of Estimating the Error Components Regression Models.- 3.1 Introduction.- 3.2 Some Matrix Results.- 3.3 Covariance Estimators.- 3.4 Estimation of Error Components Models.- 3.5 A Class of Asymptotically Efficient Estimators.- 3.6 Small Sample Properties of the Pooled Estimator.- 3.7 A Comparison of the Efficiencies of Pooled and OLS Estimators.- 3.8 A Comparison of the Efficiency of Pooled Estimator with Those of its Components.- 3.9 Alternative Estimators of Slope Coefficients and the Regression on Lagged Values of the Dependent Variables.- 3.10 Analysis of an Error Components Model Under Alternative Assumptions.- 3.11 Maximum Likelihood Method of Estimating Error Components Model.- 3.12 Departures from the Basic Assumptions Underlying the Error Components Model.- 3.13 Conclusions.- IV -- Statistical Inference in Random Coefficient Regression Models Using Panel Data.- 4.1 Introduction.- 4.2 Setting the Problem.- 4.3 Efficient Methods of Estimating the Parameters of RCR Models.- 4.4 Estimation of Parameters in RCR Models when Disturbances are Serially Correlated.- 4.5 Problems Associated with the Estimation of RCR Models Using Aggregate Data.- 4.6 Forecasting with RCR Models.- 4.7 Relaxation of Assumptions Underlying RCR Models.- 4.8 Similarities Between RCR and Bayesian Assumptions.- 4.9 Empirical CES Production Function Free of Management Bias.- 4.10 Analysis of Mixed Models.- 4.11 Conclusions.- V -- A Random Coefficient Investment Model.- 5.1 Introduction.- 5.2 Grunfeld's Hypothesis of Micro Investment Behavior.- 5.3 Estimation and Testing of Random Coefficient Investment Model.- 5.4 Aggregate Investment Function.- 5.5 Comparison of Random Coefficient Model with Fixed Coefficient Macro Model.- 5.6 Comparison of Random Coefficient Model with Fixed Coefficient Micro Model.- 5.7 Conclusions.- VI -- Aggregate Consumption Function with Coefficients Random Across Countries.- 6.1 Introduction.- 6.2 Aggregate Consumption Model.- 6.3 Source and Nature of Data.- 6.4 Fixed Coefficient Approach.- 6.5 Random Coefficient Approach.- 6.6 Conclusions.- VII -- Miscellaneous Topics.- 7.1 Introduction.- 7.2 Identification.- 7.3 Incorporation of Prior Information in the Estimation of RCR Models.- 7.4 Conclusions.