Microeconometrics Using Stata
Stata Press
1st Edition
Published on 15. December 2008
Book
Paperback/Softback
978-1-59718-016-0 (ISBN)
Description
Covering important topics omitted from basic introductions to Stata, Microeconometrics Using Stata shows how to do microeconometric research using Stata. It provides the most complete and up-to-date survey of microeconometric methods available in Stata.
After a brief introduction to Stata, the authors present linear regression, simulation, and generalized least squares methods. The section on cross-sectional techniques is complete with up-to-date treatments of instrumental-variables methods for linear models as well as quantile regression methods. The next section covers estimators for the parameters of linear panel-data models. The book explores standard random-effects and fixed-effects methods, along with mixed linear models used in many areas outside of econometrics. After introducing methods for nonlinear regression models, the authors discuss how to code new, nonlinear estimators in Stata. They show how to easily implement new nonlinear estimators. The authors also cover inference using analytical and bootstrap approximations to the distribution of test statistics. The book then contains a section on methods for different nonlinear models, including multinomial, selection, count-data, and nonlinear panel-data models.
By combining intuitive introductions and detailed discussions of Stata examples, this book provides an invaluable hands-on introduction to microeconometrics.
After a brief introduction to Stata, the authors present linear regression, simulation, and generalized least squares methods. The section on cross-sectional techniques is complete with up-to-date treatments of instrumental-variables methods for linear models as well as quantile regression methods. The next section covers estimators for the parameters of linear panel-data models. The book explores standard random-effects and fixed-effects methods, along with mixed linear models used in many areas outside of econometrics. After introducing methods for nonlinear regression models, the authors discuss how to code new, nonlinear estimators in Stata. They show how to easily implement new nonlinear estimators. The authors also cover inference using analytical and bootstrap approximations to the distribution of test statistics. The book then contains a section on methods for different nonlinear models, including multinomial, selection, count-data, and nonlinear panel-data models.
By combining intuitive introductions and detailed discussions of Stata examples, this book provides an invaluable hands-on introduction to microeconometrics.
More details
Language
English
Place of publication
College Station
United States
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 280 mm
Width: 210 mm
ISBN-13
978-1-59718-016-0 (9781597180160)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
University of California, California, USA COLLEGE STATION Indiana University, Bloomington, Indiana, USA COLLEGE STATION
University of California, California, USA COLLEGE STATION Indiana University, Bloomington, Indiana, USA COLLEGE STATION
University of California, California, USA COLLEGE STATION Indiana University, Bloomington, Indiana, USA COLLEGE STATION
Author
University of California, Davis, California, USA
University of Aarhus, Denmark
Content
Preface
Stata Basics
Data Management and Graphics
Linear Regression Basics
Simulation
GLS Regression
Linear Instrumental-Variables Regression
Quantile Regression
Linear Panel Models: Basics
Linear Panel Models: Extensions
Nonlinear Regression Methods
Nonlinear Optimization Methods
Testing Methods
Bootstrap Methods
Binary Outcome Models
Multinomial Models
Tobit and Selection Models
Count-Data models
Nonlinear Panel Models
Appendix A: Programming in Stata
Appendix B: Mata
References
Stata Basics
Data Management and Graphics
Linear Regression Basics
Simulation
GLS Regression
Linear Instrumental-Variables Regression
Quantile Regression
Linear Panel Models: Basics
Linear Panel Models: Extensions
Nonlinear Regression Methods
Nonlinear Optimization Methods
Testing Methods
Bootstrap Methods
Binary Outcome Models
Multinomial Models
Tobit and Selection Models
Count-Data models
Nonlinear Panel Models
Appendix A: Programming in Stata
Appendix B: Mata
References