Econometric Analysis
International Edition
5th Edition
Published on 2. September 2002
Book
Paperback/Softback
1026 pages
978-0-13-110849-3 (ISBN)
Description
For a one-year graduate course in Econometrics.
This text has two objectives. The first is to introduce students to applied econometrics, including basic techniques in regression analysis and some of the rich variety of models that are used when the linear model proves inadequate or inappropriate. The second is to present students with sufficient theoretical background that they will recognize new variants of the models learned about here as merely natural extensions that fit within a common body of principles. The Fifth Edition features a complete update of techniques and developments, a reorganization of material for improved presentation, and new material and applications.
This text has two objectives. The first is to introduce students to applied econometrics, including basic techniques in regression analysis and some of the rich variety of models that are used when the linear model proves inadequate or inappropriate. The second is to present students with sufficient theoretical background that they will recognize new variants of the models learned about here as merely natural extensions that fit within a common body of principles. The Fifth Edition features a complete update of techniques and developments, a reorganization of material for improved presentation, and new material and applications.
More details
Edition
5th edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 189 mm
Thickness: 37 mm
Weight
1536 gr
ISBN-13
978-0-13-110849-3 (9780131108493)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
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William Greene | William H. Greene
Econometric Analysis, Global Edition
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01/2020
8th Edition
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09/1999
4th Edition
Pearson
€47.16
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Content
1. Introduction.
2. The Classical Multiple Linear Regression Model.
3. Least Squares.
4. Finite Sample Properties of the Least Squares Estimator.
5. Large Sample Properties of the Least Squares and Instrumental Variables Estimators.
6. Inference and Prediction.
7. Functional Form and Structural Change.
8. Specification Analysis and Model Selection.
9. Nonlinear Regression Models.
10. Nonspherical Disturbances-The Generalized Regression Model.
11. Heteroscedasticity.
12. Serial Correlation.
13. Models for Panel Data.
14. Systems of Regression Equations.
15. Simultaneous-Equations Models.
16. Estimation Frameworks in Econometrics.
17. Maximum Likelihood Estimation.
18. The Generalized Method of Moments.
19. Models with Lagged Variables.
20. Time-Series Models.
21. Models for Discrete Choice.
22. Limited Dependent Variable and Duration Models.
Appendix A: Matrix Algebra.
Appendix B: Probability and Distribution Theory.
Appendix C: Estimation and Inference.
Appendix D: Large Sample Distribution Theory.
Appendix E: Computation and Optimization.
Appendix F: Data Sets Used in Applications.
Appendix G. Statistical Tables.
References.
Author Index.
Subject Index.
2. The Classical Multiple Linear Regression Model.
3. Least Squares.
4. Finite Sample Properties of the Least Squares Estimator.
5. Large Sample Properties of the Least Squares and Instrumental Variables Estimators.
6. Inference and Prediction.
7. Functional Form and Structural Change.
8. Specification Analysis and Model Selection.
9. Nonlinear Regression Models.
10. Nonspherical Disturbances-The Generalized Regression Model.
11. Heteroscedasticity.
12. Serial Correlation.
13. Models for Panel Data.
14. Systems of Regression Equations.
15. Simultaneous-Equations Models.
16. Estimation Frameworks in Econometrics.
17. Maximum Likelihood Estimation.
18. The Generalized Method of Moments.
19. Models with Lagged Variables.
20. Time-Series Models.
21. Models for Discrete Choice.
22. Limited Dependent Variable and Duration Models.
Appendix A: Matrix Algebra.
Appendix B: Probability and Distribution Theory.
Appendix C: Estimation and Inference.
Appendix D: Large Sample Distribution Theory.
Appendix E: Computation and Optimization.
Appendix F: Data Sets Used in Applications.
Appendix G. Statistical Tables.
References.
Author Index.
Subject Index.