Econometric Analysis, Global Edition

8th Auflage
ISBN: 978-1-292-23113-6
Verlag: Pearson

Buch, Englisch, 1166 Seiten, Format (B × H): 187 mm x 232 mm, Gewicht: 1644 g

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, Global Edition, presents this ever-growing area at an accessible graduate level. The book first introduces students to basic techniques, a rich variety of models, and underlying theory that is easy to put into practice. It then presents students with a sufficient theoretical background to understand advanced techniques and to recognise new variants of established models. This focus, along with hundreds of worked numerical examples, ensures that students can apply the theory to real-world application and are prepared to be successful economists in the field.

Autoren/Hrsg.

Greene, William H.

Greene, William

Inhaltsverzeichnis

PART I. The Linear Regression Model1.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 Equations9. The Generalized Regression Model and Heteroscedasticity 10. Systems of Regression Equations 11. Models for Panel Data PART III. Estimation Methodology12. 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 Microeconometrics17. 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 Macroeconometrics20. Serial Correlation 21. Nonstationary Data PART VI. AppendicesAppendix 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