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SOLUTION MANUAL FOR INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 4TH EDITION BY JEFFREY M. WOOLDRIDGE| COMPLETE GUIDE

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SOLUTION MANUAL FOR INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 4TH EDITION BY JEFFREY M. WOOLDRIDGE| COMPLETE GUIDE SOLUTION MANUAL FOR INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 4TH EDITION BY JEFFREY M. WOOLDRIDGE| COMPLETE GUIDE

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INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 4TH
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INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 4TH

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STUDENT SOLUTIONS MANUALJEFFREY M. WOOLDRIDGEINTRODUCTORY
ECONOMETRICS: A MODERN APPROACH, 4E




SOLUTION MANUAL FOR INTRODUCTORY
ECONOMETRICS: A MODERN APPROACH, 4TH EDITION
BY JEFFREY M. WOOLDRIDGE| COMPLETE GUIDE


4th Edition




ii

,STUDENT SOLUTIONS MANUALJEFFREY M. WOOLDRIDGEINTRODUCTORY
ECONOMETRICS: A MODERN APPROACH, 4E
CONTENTS

Preface Iv

Chapter 1 Introduction 1

Chapter 2 The Simple Regression Model 3

Chapter 3 Multiple Regression Analysis: Estimation 9

Chapter 4 Multiple Regression Analysis: Inference 17

Chapter 5 Multiple Regression Analysis: OLS Asymptotics 24

Chapter 6 Multiple Regression Analysis: Further Issues 27

Chapter 7 Multiple Regression Analysis With Qualitative 34
Information: Binary (Or Dummy) Variables

Chapter 8 Heteroskedasticity 42

Chapter 9 More On Specification And Data Problems 47

Chapter 10 Basic Regression Analysis With Time Series Data 52

Chapter 11 Further Issues In Using OLS With Time Series Data 58

Chapter 12 Serial Correlation And Heteroskedasticity In 65
Time Series Regressions

Chapter 13 Pooling Cross Sections Across Time. Simple 71
Panel Data Methods

Chapter 14 Advanced Panel Data Methods 78

Chapter 15 Instrumental Variables Estimation And Two Stage 85
Least Squares

Chapter 16 Simultaneous Equations Models 92

Chapter 17 Limited Dependent Variable Models And Sample 99
Selection Corrections

Chapter 18 Advanced Time Series Topics 110




iii

,STUDENT SOLUTIONS MANUALJEFFREY M. WOOLDRIDGEINTRODUCTORY
ECONOMETRICS: A MODERN APPROACH, 4E
Appendix A Basic Mathematical Tools 117

Appendix B Fundamentals Of Probability 119

Appendix C Fundamentals Of Mathematical Statistics 120

Appendix D Summary Of Matrix Algebra 122

Appendix E The Linear Regression Model In Matrix Form 123




iv

, STUDENT SOLUTIONS MANUALJEFFREY M. WOOLDRIDGEINTRODUCTORY
ECONOMETRICS: A MODERN APPROACH, 4E

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,
Academic.Cengage.Com/Economics/Wooldridge. 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 .

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




v

, STUDENT SOLUTIONS MANUALJEFFREY M. WOOLDRIDGEINTRODUCTORY
ECONOMETRICS: A MODERN APPROACH, 4E

CHAPTER 1
SOLUTIONS TO PROBLEMS

1.1 (I) Ideally, We Could Randomly Assign Students To Classes Of Different Sizes. That Is,
Each Student Is Assigned A Different Class Size Without Regard To Any Student
Characteristics Such As Ability And Family Background. For Reasons We Will See In
Chapter 2, We Would Like Substantial Variation In Class Sizes (Subject, Of Course, To
Ethical Considerations And Resource Constraints).

(ii) A Negative Correlation Means That Larger Class Size Is Associated With Lower
Performance. We Might Find A Negative Correlation Because Larger Class Size Actually Hurts
Performance. However, With Observational Data, There Are Other Reasons We Might Find A
Negative Relationship. For Example, Children From More Affluent Families Might Be More
Likely To Attend Schools With Smaller Class Sizes, And Affluent Children Generally Score
Better On Standardized Tests. Another Possibility Is That, Within A School, A Principal Might
Assign The Better Students To Smaller Classes. Or, Some Parents Might Insist Their Children
Are In The Smaller Classes, And These Same Parents Tend To Be More Involved In Their
Children’s Education.

(iii) Given The Potential For Confounding Factors – Some Of Which Are Listed In (Ii) –
Finding A Negative Correlation Would Not Be Strong Evidence That Smaller Class Sizes
Actually Lead To Better Performance. Some Way Of Controlling For The Confounding Factors
Is Needed, And This Is The Subject Of Multiple Regression Analysis.

1.3 It Does Not Make Sense To Pose The Question In Terms Of Causality. Economists Would
Assume That Students Choose A Mix Of Studying And Working (And Other Activities, Such
As Attending Class, Leisure, And Sleeping) Based On Rational Behavior, Such As Maximizing
Utility Subject To The Constraint That There Are Only 168 Hours In A Week. We Can Then
Use Statistical Methods To Measure The Association Between Studying And Working,
Including Regression Analysis That We Cover Starting In Chapter 2. But We Would Not Be
Claiming That One Variable “Causes” The Other. They Are Both Choice Variables Of The
Student.

SOLUTIONS TO COMPUTER EXERCISES

C1.1 (I) The Average Of Educ Is About 12.6 Years. There Are Two People Reporting Zero
Years Of Education, And 19 People Reporting 18 Years Of Education.

(ii) The Average Of Wage Is About $5.90, Which Seems Low In The Year 2008.

(iii) Using Table B-60 In The 2004 Economic Report Of The President, The CPI Was
56.9 In 1976 And 184.0 In 2003.

(iv) To Convert 1976 Dollars Into 2003 Dollars, We Use The Ratio Of The Cpis,
Which Is .9  3.23 . Therefore, The Average Hourly Wage In 2003 Dollars Is
Roughly 3.23($5.90)  $19.06 , Which Is A Reasonable Figure.

1

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