Applied Econometrics Using the SAS System

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The first cutting-edge guide to using the SAS® system for the analysis of econometric data Applied Econometrics Using the SAS® System is the first book of its kind to treat the analysis of basic econometric data using SAS®, one of the most commonly used software tools among today’s statisticians in business and industry. This book thoroughly examines econometric methods and discusses how data collected in economic studies can easily be analyzed using the SAS® system. In addition to addressing the computational aspects of econometric data analysis, the author provides a statistical foundation by introducing the underlying theory behind each method before delving into the related SAS® routines. The book begins with a basic introduction to econometrics and the relationship between classical regression analysis models and econometric models. Subsequent chapters balance essential concepts with SAS® tools and cover key topics such as: Regression analysis using Proc IML and Proc Reg Hypothesis testing Instrumental variables analysis, with a discussion of measurement errors, the assumptions incorporated into the analysis, and specification tests Heteroscedasticity, including GLS and FGLS estimation, group-wise heteroscedasticity, and GARCH models Panel data analysis Discrete choice models, along with coverage of binary choice models and Poisson regression Duration analysis models Assuming only a working knowledge of SAS®, this book is a one-stop reference for using the software to analyze econometric data. Additional features include complete SAS® code, Proc IML routines plus a tutorial on Proc IML, and an appendix with additional programs and data sets. Applied Econometrics Using the SAS® System serves as a relevant and valuable reference for practitioners in the fields of business, economics, and finance. In addition, most students of econometrics are taught using GAUSS and STATA, yet SAS® is the standard in the working world; therefore, this book is an ideal supplement for upper-undergraduate and graduate courses in statistics, economics, and other social sciences since it prepares readers for real-world careers.

Table of contents

Cover
Title page
Copyright page
Dedication
Preface
Acknowledgments
1: Introduction to Regression Analysis
2: Regression Analysis Using Proc IML and Proc Reg
3: Hypothesis Testing
4: Instrumental Variables
5: Nonspherical Disturbances and Heteroscedasticity
6: Autocorrelation
7: Panel Data Analysis
8: Systems of Regression Equations
9: Simultaneous Equations
10: Discrete Choice Models
11: Duration Analysis
12: Special Topics
Appendix A: Basic Matrix Algebra for Econometrics
Appendix B: Basic Matrix Operations in Proc IML
Appendix C: Simulating the Large Sample Properties of the OLS Estimators
Appendix D: Introduction to Bootstrap Estimation
Appendix E: Complete Programs and Proc IML Routines
References
Index


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