Specification Analysis in the Linear Model
Published on 5. March 2018
370 pages
978-1-351-14066-9 (ISBN)
Description
Originally published in 1987. This collection of original papers deals with various issues of specification in the context of the linear statistical model. The volume honours the early econometric work of Donald Cochrane, late Dean of Economics and Politics at Monash University in Australia. The chapters focus on problems associated with autocorrelation of the error term in the linear regression model and include appraisals of early work on this topic by Cochrane and Orcutt. The book includes an extensive survey of autocorrelation tests; some exact finite-sample tests; and some issues in preliminary test estimation. A wide range of other specification issues is discussed, including the implications of random regressors for Bayesian prediction; modelling with joint conditional probability functions; and results from duality theory. There is a major survey chapter dealing with specification tests for non-nested models, and some of the applications discussed by the contributors deal with the British National Accounts and with Australian financial and housing markets.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Product notice
Reflowable
File size
14,00 MB
ISBN-13
978-1-351-14066-9 (9781351140669)
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Schweitzer Classification
Other editions
Additional editions
Maxwell L. King | David E. A. Giles
Specification Analysis in the Linear Model
(In Honour of Donald Cochrane)
Book
06/2019
1st Edition
Routledge
€47.22
Shipment within 15-20 days
Maxwell L. King | David E. A. Giles
Specification Analysis in the Linear Model
(In Honour of Donald Cochrane)
Book
03/2018
1st Edition
Routledge
€119.03
Shipment within 15-20 days
Persons
Maxwell L. King, David E. A. Giles
Content
Preface 1. Introduction Maxwell L. King and David E. A. Giles Part 1: Linear Regression with Autocorrelated Errors 2. The Cochrane and Orcutt Papers E. J. Harman 3. Testing for Autocorrelation in Linear Regression Models Maxwell L. King 4. Linear regression with Correlated Errors: Bounds on Coefficient Estimates and t-values Grant H. Hillier and Maxwell L. King 5. Efficiency of Estimators in the Regression Model with First-order Autoregressive errors L. Magee, A. Ullah, and V. K. Srivastava 6. Autocorrelation Pre-test Estimation in Models with a Lagged Dependent Variable David E. A. Giles and Murray Beanie 7. Some Aspects of Mis-specification in the Linear Model Peter Praetz Part 2: General Model Specification Issues 8. Joint Conditional Probability Functions for Modeling National Economies Guy H. Orcutt 9. Specification Tests for Separate Models: A Survey Michael McAleer 10. Functional Forms in Intertemporal Duality Keith R. McLaren and Russel J. Cooper Part 3: Some Statistical Issues 11. Asymptotic Spectral Analysis of Cross-product Matrices G. S. Watson 12. Bayesian Prediction with Random Regressors Arnold Zellner and Soo-Bin Park Part 4: Applications 13. How Accurate are the British National Accounts? Richard Stone 14. The Pattern of Financial Asset Holdings in Australia Kenneth W. Clements and John C. Taylor 15. Dwelling Commencements in Australia: Lags and Autocorrelation Ross A. Williams. Appendix 1: Application of Least Squares Regression to Relationships Containing Auto-correlated Error Terms D. Cochrane and G. H. Orcutt. Appendix 2: A Sampling Study of the Merits of Autoregressive and Reduced Form Transformations in Regression Analysis Guy H. Orcutt and Donald Cochrane. Appendix 3: The Method of Iterative Maximization J. D. Sargan
