Econometric Analysis/
Greene, William H.
Econometric Analysis/ William H. Greene. - 8th Ed. - Noida : Pearson India, 2018. - xl, 1126p. : ill. ;
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
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.
9789353061074
Econometrics, Linear Regression Model,Squares Regression,Least Squares,Semi-parametric
330.0151 / GRE
Econometric Analysis/ William H. Greene. - 8th Ed. - Noida : Pearson India, 2018. - xl, 1126p. : ill. ;
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
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.
9789353061074
Econometrics, Linear Regression Model,Squares Regression,Least Squares,Semi-parametric
330.0151 / GRE