Solution Manual For Introductory
Econometrics A Modern Approach 7th
By Wooldridge
3
, CHAPTER 1
TEACHING NOTES
You Have Substantial Latitude About What To Emphasize In Chapter 1. I Find It Useful To Talk
About The Economics Of Crime Example (Example 1.1) And The Wage Example (Example 1.2)
So That Students See, At The Outset, That Econometrics Is Linked To Economic Reasoning, If
Not Economic Theory.
I Like To Familiarize Students With The Important Data Structures That Empirical
Economists Use, Focusing Primarily On Cross-Sectional And Time Series Data Sets, As These
Are What I Cover In A First-Semester Course. It Is Probably A Good Idea To Mention The
Growing Importance Of Data Sets That Have Both A Cross-Sectional And Time Dimension.
I Spend Almost An Entire Lecture Talking About The Problems Inherent In Drawing Causal
Inferences In The Social Sciences. I Do This Mostly Through The Agricultural Yield, Return To
Education, And Crime Examples. These Examples Also Contrast Experimental And
Nonexperimental Data. Students Studying Business And Finance Tend To Find The Term
Structure Of Interest Rates Example More Relevant, Although The Issue There Is Testing The
Implication Of A Simple Theory, As Opposed To Inferring Causality. I Have Found That
Spending Time Talking About These Examples, In Place Of A Formal Review Of Probability
And Statistics, Is More Successful (And More Enjoyable For The Students And Me).
CHAPTER 1
CORRECT ANSWER TO PROBLEMS1.1
(i) Ideally, We Could Randomly Assign Students To Classes Of Different Sizes. That Is, Eachstudent Is
Assigned A Different Class Size Without Regard To Any Student Characteristics Such Asability And Family
Background. For Reasons We Will See In Chapter 2, We Would Like Substantialvariation 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 Withsmaller 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
Parentstend To Be More Involved In Their Children’s Education.(Iii) Given The Potential For Confounding
Factors – Some Of Which Are Listed In (Ii) – Finding Anegative 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
Thesubject Of Multiple Regression Analysis.
1.3
It Does Not Make Sense To Pose The Question In Terms Of Causality. Economists Would Assumethat
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 Theconstraint That There Are
Only 168 Hours In A Week. We Can Then Use Statistical Methods Tomeasure The Association Between
Studying And Working, Including Regression Analysis That Wecover Starting In Chapter 2. But We Would Not
Be Claiming That One Variable “Causes” The Other.They Are Both Choice Variables Of The Student.
CORRECT ANSWER TO COMPUTER EXERCISESC1.1
(i) The Average
4
,Of Educ
Is About 12.6 Years. There Are Two People Reporting Zero Years Ofeducation, And 19 People Reporting 18
Years
5
, 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
Den
t
, The CPI Was 56.9 In1976 And 184.0 In 2003.(Iv) To Convert 1976 Dollars Into 2003 Dollars, We Use The
Ratio Of The Cpis, Which Is. Therefore, The Average Hourly Wage In 2003 Dollars Is Roughly, Which Is A
Reasonable Figure.184/56.93.23
≈
3.23($5.90)
≈
$19.06 1
2 (V) The Sample Contains 252 Women (The Number Of Observations With
Female
= 1) And 274men.
C1.3
(I) The Largest Is 100, The Smallest Is 0.(Ii) 38 Out Of 1,823, Or About 2.1 Percent Of The Sample.(Iii)
17(Iv) The Average Of
Math4
Is About 71.9 And The Average Of
Read4
Is About 60.1. So, At Leastin 2001, The Reading Test Was Harder To Pass.(V) The Sample Correlation Between
Math
4 And
Read4
Is About .843, Which Is A Very Highdegree Of (Linear) Association. Not Surprisingly, Schools That Have
High Pass Rates On One Testhave A Strong Tendency To Have High Pass Rates On The Other Test.(Vi) The
Average Of
Exppp
Is About $5,194.87. The Standard Deviation Is $1,091.89, Whichshows Rather Wide Variation In Spending
Per Pupil. [The Minimum Is $1,206.88 And Themaximum Is $11,957.64.
6
Econometrics A Modern Approach 7th
By Wooldridge
3
, CHAPTER 1
TEACHING NOTES
You Have Substantial Latitude About What To Emphasize In Chapter 1. I Find It Useful To Talk
About The Economics Of Crime Example (Example 1.1) And The Wage Example (Example 1.2)
So That Students See, At The Outset, That Econometrics Is Linked To Economic Reasoning, If
Not Economic Theory.
I Like To Familiarize Students With The Important Data Structures That Empirical
Economists Use, Focusing Primarily On Cross-Sectional And Time Series Data Sets, As These
Are What I Cover In A First-Semester Course. It Is Probably A Good Idea To Mention The
Growing Importance Of Data Sets That Have Both A Cross-Sectional And Time Dimension.
I Spend Almost An Entire Lecture Talking About The Problems Inherent In Drawing Causal
Inferences In The Social Sciences. I Do This Mostly Through The Agricultural Yield, Return To
Education, And Crime Examples. These Examples Also Contrast Experimental And
Nonexperimental Data. Students Studying Business And Finance Tend To Find The Term
Structure Of Interest Rates Example More Relevant, Although The Issue There Is Testing The
Implication Of A Simple Theory, As Opposed To Inferring Causality. I Have Found That
Spending Time Talking About These Examples, In Place Of A Formal Review Of Probability
And Statistics, Is More Successful (And More Enjoyable For The Students And Me).
CHAPTER 1
CORRECT ANSWER TO PROBLEMS1.1
(i) Ideally, We Could Randomly Assign Students To Classes Of Different Sizes. That Is, Eachstudent Is
Assigned A Different Class Size Without Regard To Any Student Characteristics Such Asability And Family
Background. For Reasons We Will See In Chapter 2, We Would Like Substantialvariation 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 Withsmaller 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
Parentstend To Be More Involved In Their Children’s Education.(Iii) Given The Potential For Confounding
Factors – Some Of Which Are Listed In (Ii) – Finding Anegative 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
Thesubject Of Multiple Regression Analysis.
1.3
It Does Not Make Sense To Pose The Question In Terms Of Causality. Economists Would Assumethat
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 Theconstraint That There Are
Only 168 Hours In A Week. We Can Then Use Statistical Methods Tomeasure The Association Between
Studying And Working, Including Regression Analysis That Wecover Starting In Chapter 2. But We Would Not
Be Claiming That One Variable “Causes” The Other.They Are Both Choice Variables Of The Student.
CORRECT ANSWER TO COMPUTER EXERCISESC1.1
(i) The Average
4
,Of Educ
Is About 12.6 Years. There Are Two People Reporting Zero Years Ofeducation, And 19 People Reporting 18
Years
5
, 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
Den
t
, The CPI Was 56.9 In1976 And 184.0 In 2003.(Iv) To Convert 1976 Dollars Into 2003 Dollars, We Use The
Ratio Of The Cpis, Which Is. Therefore, The Average Hourly Wage In 2003 Dollars Is Roughly, Which Is A
Reasonable Figure.184/56.93.23
≈
3.23($5.90)
≈
$19.06 1
2 (V) The Sample Contains 252 Women (The Number Of Observations With
Female
= 1) And 274men.
C1.3
(I) The Largest Is 100, The Smallest Is 0.(Ii) 38 Out Of 1,823, Or About 2.1 Percent Of The Sample.(Iii)
17(Iv) The Average Of
Math4
Is About 71.9 And The Average Of
Read4
Is About 60.1. So, At Leastin 2001, The Reading Test Was Harder To Pass.(V) The Sample Correlation Between
Math
4 And
Read4
Is About .843, Which Is A Very Highdegree Of (Linear) Association. Not Surprisingly, Schools That Have
High Pass Rates On One Testhave A Strong Tendency To Have High Pass Rates On The Other Test.(Vi) The
Average Of
Exppp
Is About $5,194.87. The Standard Deviation Is $1,091.89, Whichshows Rather Wide Variation In Spending
Per Pupil. [The Minimum Is $1,206.88 And Themaximum Is $11,957.64.
6
