William H. Greene


The Stern School of Business


New York University


 

Part I The Linear Regression Model


Chapter 1 Econometrics


Chapter 2 T he Linear Regression Model


Chapter 3 L east Squares Regression


Chapter 4 Estimating the Regression Model by Least Squares


Chapter 5 H ypothesis Tests and Model Selection


Chapter 6 Functional Form, Difference in Differences, and Structural Change


Chapter 7 N onlinear, Semiparametric, and Nonparametric Regression


M odels


Chapter 8 Endogeneity and Instrumental Variable Estimation


Part II Generalized Regression Model and Equation Systems


Chapter 9 T he Generalized Regression Model and Heteroscedasticity


Chapter 10 S ystems of Regression Equations


Chapter 11 M odels 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 and Random Parameter


Models


Chapter 16 Bayesian Estimation and Inference


Part IV Cross Sections, Panel Data, and Microeconometrics


Chapter 17 Binary Outcomes and Discrete Choices


Chapter 18 M ultinomial Choices and Event Counts


Chapter 19 L imited Dependent Variables—Truncation, Censoring, and


Sample Selection


Part V Time Series and Macroeconometrics


Chapter 20 S erial Correlation 981


Chapter 21 Nonstationary Data


 

1) This text is intended for a one-year graduate course for social scientists.


2) It includes five chapters on estimation methods used in current research and five chapters on applications in micro- and macroeconometrics.


3) Appendix E and Chapter 15 contain a description of numerical methods that will


be useful to practicing econometricians.


4) The author has revised the presentation throughout the book to streamline the development of topics, in some cases , to improve the clarity of


the derivations.