# Introductory Econometrics Solutions

Topics: Regression analysis, Econometrics, Linear regression Pages: 144 (46739 words) Published: September 12, 2012
STUDENT SOLUTIONS MANUAL
Jeffrey M. Wooldridge

Introductory Econometrics: A Modern Approach, 4e

CONTENTS
Preface Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Introduction The Simple Regression Model Multiple Regression Analysis: Estimation Multiple Regression Analysis: Inference Multiple Regression Analysis: OLS Asymptotics Multiple Regression Analysis: Further Issues Multiple Regression Analysis With Qualitative Information: Binary (or Dummy) Variables Heteroskedasticity More on Specification and Data Problems Basic Regression Analysis With Time Series Data Further Issues in Using OLS With Time Series Data Serial Correlation and Heteroskedasticity in Time Series Regressions Pooling Cross Sections Across Time. Simple Panel Data Methods Advanced Panel Data Methods Instrumental Variables Estimation and Two Stage Least Squares Simultaneous Equations Models Limited Dependent Variable Models and Sample Selection Corrections Advanced Time Series Topics ii This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied, or distributed without the prior consent of the publisher.

iv 1 3 9 17 24 27 34

Chapter 8 Chapter 9 Chapter 10 Chapter 11 Chapter 12

42 47 52 58 65

Chapter 13

71

Chapter 14 Chapter 15

78 85

Chapter 16 Chapter 17

92 99

Chapter 18

110

Appendix A Appendix B Appendix C Appendix D Appendix E

Basic Mathematical Tools Fundamentals of Probability Fundamentals of Mathematical Statistics Summary of Matrix Algebra The Linear Regression Model in Matrix Form

117 119 120 122 123

iii
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied, or distributed without the prior consent of the publisher.

PREFACE
This manual contains solutions to the odd-numbered problems and computer exercises in Introductory Econometrics: A Modern Approach, 4e. Hopefully, you will find that the solutions are detailed enough to act as a study supplement to the text. Rather than just presenting the final answer, I usually provide detailed steps, emphasizing where the chapter material is used in solving the problems. Some of the answers given here are subjective, and you or your instructor may have perfectly acceptable alternative answers or opinions. I obtained the solutions to the computer exercises using Stata, starting with version 4.0 and ending with version 9.0. Nevertheless, almost all of the estimation methods covered in the text have been standardized, and different econometrics or statistical packages should give the same answers to the reported degree of accuracy. There can be differences when applying more advanced techniques, as conventions sometimes differ on how to choose or estimate auxiliary parameters. (Examples include heteroskedasticity-robust standard errors, estimates of a random effects model, and corrections for sample selection bias.) Any differences in estimates or test statistics should be practically unimportant, provided you are using a reasonably large sample size. While I have endeavored to make the solutions free of mistakes, some errors may have crept in. I would appreciate hearing from students who find mistakes. I will keep a list of any notable errors on the Web site for the book, www.international.cengage.com. I would also like to hear from students who have suggestions for improving either the solutions or the problems themselves. I can be reached via e-mail at wooldri1@.msu.edu. I hope that you find this solutions manual helpful when used in conjunction with the text. I look forward to hearing from you. Jeffrey M. Wooldridge Department of Economics Michigan State University 110 Marshall-Adams Hall East Lansing, MI 48824-1038

iv
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not...