Introductory Econometrics

Jeffrey M. Wooldridge

Chapter 1

The Nature of Econometrics and Economic Data - all with Video Answers

Educators

Chapter Questions

Problem 1

Use the data in WAGE1 for this exercise.
(i) Find the average education level in the sample. What are the lowest and highest years of education?
(ii) Find the average hourly wage in the sample. Does it seem high or low?
(iii) The wage data are reported in 1976 dollars. Using the Internet or a printed source, find the
Consumer Price Index (CPI) for the years 1976 and 2013.
(iv) Use the CPI values from part (iii) to find the average hourly wage in 2013 dollars. Now does
the average hourly wage seem reasonable?
(v) How many women are in the sample? How many men?

Alex Loukas

Alex Loukas

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Problem 2

Use the data in BWGHT to answer this question.
(i) How many women are in the sample, and how many report smoking during pregnancy?
(ii) What is the average number of cigarettes smoked per day? Is the average a good measure of the
"typical" woman in this case? Explain.
(iii) Among women who smoked during pregnancy, what is the average number of cigarettes
smoked per day? How does this compare with your answer from part (ii), and why?
(iv) Find the average of fatheduc in the sample. Why are only 1,192 observations used to compute
this average?
(v) Report the average family income and its standard deviation in dollars.

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Problem 3

The data in MEAPOl are for the state of Michigan in the year $2001 .$ Use these data to answer the following questions.
(i) Find the largest and smallest values of math. Does the range make sense? Explain.
(ii) How many schools have a perfect pass rate on the math test? What percentage is the total
sample?
(iii) How many schools have math pass rates of exactly 50$\% ?$
(iv) Compare the average pass rates for the math and reading scores. Which test is harder to pass?
(v) Find the correlation between $m a t h 4$ and read $4 .$ What do you conclude?
(vi) The variable expenditure per pupil. Find the average of exppp along with its standard
deviation. Would you say there is wide variation in per pupil spending?
(vii) Suppose School A spends $\$ 6,000$ per student and School $B$ spends $\$ 5,500$ per student. By what percentage does School A's spending exceed School $\mathrm{B}$ 's? Compare this to 100$\cdot[\log (6,000)-$
$\log (5,500) ],$ which is the approximation percentage difference based on the difference in the
natural logs. (See Section A.4 in Appendix A.)

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Problem 4

The data in JTRAIN2 come from a job training experiment conducted for low-income men during
$1976-1977 ;$ see Lalonde $(1986) .$
(i) Use the indicator variable train to determine the fraction of men receiving job training.
(ii) The variable $r e 78$ is earnings from 1978 , measured in thousands of 1982 dollars. Find the
averages of $r e 78$ for the sample of men receiving job training and the sample not receiving job
training. Is the difference economically large?
(iii) The variable unem 78 is an indicator of whether a man is unemployed or not in $1978 .$ What
fraction of the men who received job training are unemployed? What about for men who did
not receive job training? Comment on the difference.
(iv) From parts (ii) and (iii), does it appear that the job training program was effective? What would
make our conclusions more convincing?

Alex Loukas

Numerade Educator

Problem 5

The data in FERTIL2 were collected on women living in the Republic of Botswana in $1988 .$ The variable children refers to the number of living children. The variable electric is a binary indicator equal to one if the woman's home has electricity, and zero if not.
(i) Find the smallest and largest values of children in the sample. What is the average of children?
(ii) What percentage of women have electricity in the home?
(iii) Compute the average of children for those without electricity and do the same for those with
electricity. Comment on what you find.
From part (iii), can you infer that having electricity "causes" women to have fewer children?
Explain.

Alex Loukas

Numerade Educator

Problem 6

Use the data in COUNTYMURDERS to answer this question. Use only the year $1996 .$ The variable murders is the number of murders reported in the county. The variable execs is the number of executions that took place of people sentenced to death in the given county. Most states in the United States have the death penalty, but several do not.
(i) How many counties are there in the data set? Of these, how many have zero murders? What
percentage of counties have zero executions? (Remember, use only the 1996 data.)
(ii) What is the largest number of murders? What is the largest number of executions? Why is the
average number of executions so small?
(iii) Compute the correlation coefficient between murders and execs and describe what you find.
(iv) You should have computed a positive correlation in part (ii). Do you think that more executions
cause more murders to occur? What might explain the positive correlation?

Alex Loukas

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Problem 7

The data set in ALCOHOL contains information on a sample of men in the United States. Two key.
variables are self-reported employment status and alcohol abuse (along with many other variables).
The variables employ and abuse are both bindicator, variables: they take on only the values)
zero and one.
(i) What is percentage of the men in the sample report abusing alcohol? What is the employment rate?
(ii) Consider the group of men who abuse alcohol. What is the employment rate?
(iii) What is the employment rate for the group of men who do not abuse alcohol?
(iv) Discuss the difference in your answers to parts (ii) and (iii). Does this allow you to conclude
that alcohol abuse causes unemployment?

Alex Loukas

Numerade Educator