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Statistical Inference in Random Coefficient Regression Models

Author: P A V B Swamy
Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1971.
Series: Lecture Notes in Operations Research and Mathematical Systems, Economics, Computer Science, Information and Control, 55; Lecture Notes in Operations Research and Mathematical Systems, Economics, Computer Science, Information and Control, 55.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: P A V B Swamy
ISBN: 9783642806537 3642806538 9783540056034 3540056033
OCLC Number: 858930804
Description: 1 online resource.
Contents: 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.
Series Title: Lecture Notes in Operations Research and Mathematical Systems, Economics, Computer Science, Information and Control, 55; Lecture Notes in Operations Research and Mathematical Systems, Economics, Computer Science, Information and Control, 55.
Responsibility: by P.A.V.B. Swamy.

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