1st Edition

An Introduction to Modern Econometrics Using Stata



ISBN 9781597180139
Published August 17, 2006 by Stata Press
341 Pages

USD $110.00

Prices & shipping based on shipping country


Preview

Book Description

Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata.

As an expert in Stata, the author successfully guides readers from the basic elements of Stata to the core econometric topics. He first describes the fundamental components needed to effectively use Stata. The book then covers the multiple linear regression model, linear and nonlinear Wald tests, constrained least-squares estimation, Lagrange multiplier tests, and hypothesis testing of nonnested models. Subsequent chapters center on the consequences of failures of the linear regression model's assumptions. The book also examines indicator variables, interaction effects, weak instruments, underidentification, and generalized method-of-moments estimation. The final chapters introduce panel-data analysis and discrete- and limited-dependent variables and the two appendices discuss how to import data into Stata and Stata programming.

Presenting many of the econometric theories used in modern empirical research, this introduction illustrates how to apply these concepts using Stata. The book serves both as a supplementary text for undergraduate and graduate students and as a clear guide for economists and financial analysts.

Table of Contents

PREFACE
NOTATION AND TYPOGRAPHY

INTRODUCTION
An Overview of Stata's Distinctive Features
Installing the Necessary Software
Installing the Support Materials

WORKING WITH ECONOMIC AND FINANCIAL DATA IN STATA
The Basics
Common Data Transformations

ORGANIZING AND HANDLING ECONOMIC DATA
Cross-Sectional Data and Identifier Variables
Time-Series Data
Pooled Cross-Sectional Time-Series Data
Panel Data
Tools for Manipulating Panel Data
Combining Cross-Sectional and Time-Series Datasets
Creating Long-Format Datasets with Append
The Reshape Command
Using Stata for Reproducible Research

LINEAR REGRESSION
Introduction
Computing Linear Regression Estimates
Interpreting Regression Estimates
Presenting Regression Estimates
Hypothesis Tests, Linear Restrictions, and Constrained Least Squares
Computing Residuals and Predicted Values
Computing Marginal Effects
Appendix A: Regression as a Least-Squares Estimator
Appendix B: The Large-Sample VCE for Linear Regression

SPECIFYING THE FUNCTIONAL FORM
Introduction
Specification Error
Endogeneity and Measurement Error

REGRESSION WITH NON-I.I.D. ERRORS
The Generalized Linear Regression Model
Heteroskedasticity in the Error Distribution
Serial Correlation in the Error Distribution

REGRESSION WITH INDICATOR VARIABLES
Testing for Significance of a Qualitative Factor
Regression with Qualitative and Quantitative Factors
Seasonal Adjustment with Indicator Variables
Testing for Structural Stability and Structural Change

INSTRUMENTAL-VARIABLES ESTIMATORS
Introduction
Endogeneity in Economic Relationships
2SLS
The ivreg Command
Identification and Tests of Overidentifying Restrictions
Computing IV Estimates
ivreg2 and GMM Estimation
Testing and Overidentifying Restrictions in GMM
Testing for Heteroskedasticity in the IV Context
Testing the Relevance of Instruments
Durbin-Wu-Hausman Tests for Endogeneity in IV Estimation
Appendix A: Omitted-Variables Bias
Appendix B: Measurement Error

PANEL-DATA MODELS
FE and RE Models
IV Models for Panel Data
Dynamic Panel-Data Models
Seemingly Unrelated Regression Models
Moving-Window Regression Estimates

MODELS OF DISCRETE AND LIMITED DEPENDENT VARIABLES
Binomial Logit and Probit Models
Ordered Logit and Probit Models
Truncated Regression and Tobit Models
Incidental Truncation and Sample-Selection Models
Bivariate Probit and Probit with Selection

APPENDIX A: GETTING THE DATA INTO STATA
Inputting Data from ASCII Text Files and Spreadsheets
Importing Data from Other Package Formats

APPENDIX B: THE BASICS OF STATA PROGRAMMING
Local and Global Macros
Scalars
Loop Constructs
Matrices
return and ereturn
The Program and Syntax Statements
Using Mata Functions in Stata Programs

REFERENCES
AUTHOR INDEX
SUBJECT INDEX

...
View More

Reviews

"This book provides an excellent resource for both teaching and learning modern microeconometric practice, using the most popular software package in this area. The coverage includes discrete choice models and models for panel data, as well as linear regression and instrumental variables methods. I particularly like the material on handling large datasets and developing efficient programs within Stata, which provide the reader with an invaluable introduction to good practice in empirical research."
-Steve Bond, Nuffield College, Oxford, UK, and Institute for Fiscal Studies (IFS), London, UK

"Baum provides students and researchers [with] a hands-on guide to modern econometric techniques by means of many well-documented examples in Stata. The examples are also useful templates for those who need to write Stata routines for their own work. Treatment and transformation of cross-section, time-series, and panel data are carefully explained. The coverage of the text is broad and up to date. … a valuable companion to undergraduate- and graduate-level econometric textbooks."
-Serena Ng, Department of Economics, University of Michigan, Ann Arbor, USA

"Christopher Baum's An Introduction to Modern Econometrics Using Stata is probably the only econometrics text published to date that pays serious attention to reproducibility of research and systematic data validation using Stata's data audit commands along with do-file and programming capabilities. Economic and financial consultants will find this text to be an invaluable guide to using Stata for creating reproducible, error-free data and econometric analysis, as well as quality graphic presentations. The book is comprehensive and easy to follow, with substantive coverage of econometric theory and applications using the full array of Stata's capabilities. This text should serve as an excellent learning and reference guide for every consultant."
-Zaur Rzakhanov, Ph.D., Analysis Group Inc., Boston, Massachusetts, USA

"This book is a wonderful complement to the Stata technical manuals. It provides a wealth of practical tips and sample applications that help the intermediate-level Stata user advance in making the most efficient use of Stata. It is thoughtfully organized along the lines of an econometrics textbook, allowing practitioners to find relevant and useful commands, procedures, and examples by topics that are familiar and immediate. It also includes a most helpful appendix for novice programmers that will expedite their development into proficient Stata programmers. This book is a must-have reference for any organization that needs to train practitioners of econometrics in the use of Stata."
-Peter Boberg, CRA International