Econometric Analysis 7e PIE - Greene, William H.

Econometric Analysis 7e PIE

William H. Greene

Yayınevi: Pearson Education

Yayın tarihi: 05/2011

ISBN: 9780273753568

İngilizce | 1248 Sayfa | Büyük boy  |  18,59x23,01x4,19 cm.

Tür: Ekonomi

  • 166,00 TL

For first-year graduate courses in Econometrics for Social Scientists. This title is a Pearson Global Edition. The Editorial team at Pearson has worked closely with educators around the world to include content which is especially relevant to students outside the United States. This text serves as a bridge between an introduction to the field of econometrics and the professional literature for graduate students in the social sciences, focusing on applied econometrics and theoretical concepts.


Table of Contents Part I: The Linear Regression Model Chapter 1: Econometrics Chapter 2: The Linear Regression Model Chapter 3: Least Squares Chapter 4: The Least Squares Estimator Chapter 5: Hypothesis Tests and Model Selection Chapter 6: Functional Form and Structural Change Chapter 7: Nonlinear, Semiparametric, and Nonparametric Regression Models Chapter 8: Endogeneity and Instrumental Variable Estimation Part II: Generalized Regression Model and Equation Systems Chapter 9: The Generalized Regression Model and Heteroscedasticity Chapter 10: Systems of Equations Chapter 11: Models for Panel Data Part III: Estimation Methodology Chapter 12: Estimation Frameworks in Econometrics Chapter 13: Minimum Distance Estimation and the Generalized Method of Moments Chapter 14: Maximum Likelihood Estimation Chapter 15: Simulation-Based Estimation and Inference Chapter 16: Bayesian Estimation and Inference Part IV: Cross Sections, Panel Data, and Microeconometrics Chapter 17: Discrete Choice Chapter 18: Discrete Choices and Event Counts Chapter 19: Limited Dependent Variables - Truncation, Censoring, and Sample Selection Part V: Time Series and Macroeconometrics Chapter 20: Serial Correlation Chapter 21: Models with Lagged Variables Chapter 22: Time-Series Models Chapter 23: 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 Appendix G: Statistical Tables

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