Book description
The first cuttingedge 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, groupwise 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 onestop 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 upperundergraduate and graduate courses in statistics, economics, and other social sciences since it prepares readers for realworld 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
 2.1 Introduction
 2.2 Regression Analysis Using Proc IML
 2.3 Analyzing the Data Using Proc Reg
 2.4 Extending the Investment Equation Model to the Complete Data Set
 2.5 Plotting the Data
 2.6 Correlation Between Variables
 2.7 Predictions of the Dependent Variable
 2.8 Residual Analysis
 2.9 Multicollinearity
 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
 12.1 Iterative FGLS Estimation Under Heteroscedasticity
 12.2 Maximum Likelihood Estimation Under Heteroscedasticity
 12.3 Harvey’s Multiplicative Heteroscedasticity
 12.4 Groupwise Heteroscedasticity
 12.5 Hausman–Taylor Estimator for the Random Effects Model
 12.6 Robust Estimation of Covariance Matrices in Panel Data
 12.7 Dynamic Panel Data Models
 12.8 Heterogeneity and Autocorrelation in Panel Data Models
 12.9 Autocorrelation in Panel Data

Appendix A: Basic Matrix Algebra for Econometrics
 A.1 Matrix Definitions
 A.2 Matrix Operations
 A.3 Basic Laws of Matrix Algebra
 A.4 Identity Matrix
 A.5 Transpose of a Matrix
 A.6 Determinants
 A.7 Trace of a Matrix
 A.8 Matrix Inverses
 A.9 Idempotent Matrices
 A.10 Kronecker Products
 A.11 Some Common Matrix Notations
 A.12 Linear Dependence and Rank
 A.13 Differential Calculus in Matrix Algebra
 A.14 Solving a System of Linear Equations in Proc IML

Appendix B: Basic Matrix Operations in Proc IML
 B.1 Assigning Scalars
 B.2 Creating Matrices and Vectors
 B.3 Elementary Matrix Operations
 B.4 Comparison Operators
 B.5 MatrixGenerating Functions
 B.6 Subset of Matrices
 B.7 Subscript Reduction Operators
 B.8 The Diag and VecDiag Commands
 B.9 Concatenation of Matrices
 B.10 Control Statements
 B.11 Calculating Summary Statistics 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
Product information
 Title: Applied Econometrics Using the SAS® System
 Author(s):
 Release date: June 2009
 Publisher(s): WileyInterscience
 ISBN: 9780470129494
You might also like
video
Python Fundamentals
51+ hours of video instruction. Overview The professional programmer’s Deitel® video guide to Python development with …
book
Kafka: The Definitive Guide, 2nd Edition
Every enterprise application creates data, whether it consists of log messages, metrics, user activity, outgoing messages, …
book
Machine Learning with TensorFlow
Summary Machine Learning with TensorFlow gives readers a solid foundation in machinelearning concepts plus handson experience …
book
Programming Rust, 2nd Edition
The Rust programming language offers the rare and valuable combination of statically verified memory safety and …