TY - BOOK AU - Greene, William H. TI - Econometric Analysis SN - 9789353061074 U1 - 330.0151 23 PY - 2018/// CY - Noida PB - Pearson India KW - Econometrics, Linear Regression Model,Squares Regression,Least Squares,Semi-parametric N1 - Table of Contents; 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 N2 - 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 ER -