Overview

For first-¿year graduate courses in Econometrics for Social Scientists.   Bridging the gap between social science studies and econometric analysis Designed to bridge the gap between social science studies and field-econometrics, Econometric Analysis, 8th Edition presents this ever-growing area at an accessible level. The book first introduces readers to basic techniques, a rich variety of models, and underlying theory that is easy to put into practice. It then presents readers with a sufficient theoretical background to understand advanced techniques and to recognize new variants of established models. This focus, along with hundreds of worked numerical examples, ensures that readers can apply the theory to real-world application and are prepared to be successful economists in the field.

Full Product Details

Author:   William Greene
Publisher:   Pearson Education (US)
Imprint:   Pearson
Edition:   8th edition
Dimensions:   Width: 19.50cm , Height: 5.00cm , Length: 24.00cm
Weight:   1.982kg
ISBN:  

9780134461366

ISBN 10:   0134461363
Pages:   1176
Publication Date:   24 May 2017
Audience:   College/higher education ,  Tertiary & Higher Education
Replaced By:   9780134461632
Format:   Hardback
Publisher's Status:   Active
Availability:   Available To Order  
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Table of Contents

PART I. The Linear Regression Model 1.Econometrics 2. The Linear Regression Model 3. Least Squares 4. Estimating the Regression Model by Least Squares 5. Hypothesis Tests and Model Selection 6. Functional Form, Difference in Differences and Structural Change 7. Nonlinear, Semiparametric and Nonparametric Regression Models 8. Endogeneity and Instrumental Variable Estimation PART II. Generalized Regression Model and Systems of Equations 9. The Generalized Regression Model and Heteroscedasticity 10. Systems of Regression Equations 11. Models for Panel Data   PART III. Estimation Methodology 12. Estimation Frameworks in Econometrics 13. Minimum Distance Estimation and the Generalized Method of Moments 14. Maximum Likelihood Estimation 15. Simulation-Based Estimation and Inference and Random Parameter Models 16. Bayesian Estimation and Inference   PART IV. Cross Sections, Panel Data and Microeconometrics 17. Binary Outcomes and Discrete Choices 18. Multinomial Choices and Event Counts 19. Limited Dependent Variables, Truncation, Censoring and Sample Selection   PART V. Time Series and Macroeconometrics 20. Serial Correlation 21. Nonstationary Data   PART VI. Appendices 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

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