Hello, dear friend, you can consult us at any time if you have any questions, add WeChat: daixieit

Econometrics

Practice Midterm Exam

Part I - Multiple Choice (33 points in total – 3 points each)

Place your answers in these boxes:

1. You want to know if listening to music makes you solve puzzles quickly. What is the theoretically correct counterfactual comparison to make?

A. Compare the music listening habits of people who solve puzzles quickly with those who do not.

B. Compare the puzzle solving ability of those who listen to music with those who do not.

C. Compare the listening habits of the same people while they solve and do not solve puzzles

D. Compare the puzzle solving ability of the same people while they listen and do not listen to music

2. In a regression of quantity_sold on number_of_tv_ads, the coefficient on number_of_tv_ads is 1.3 and statistically insignificant.  What can one learn from this information?

A. It is unlikely that the true effect of the number_of_tv_ads is greater than zero.

B. It is likely that the true effect of the number_of_tv_ads is greater than zero.

C. It is likely that we’d see an effect this large, even if the true coefficient on the number_of_tv_ads is zero.

D. An increase in predicted sales of 1.3 is not a large number when it comes to quantity_sold.

3. You collect data on the number of children a person has, whether or not they have  graduate degrees (dummy) and their income (in thousands). You estimate the following SRF:

What is the predicted number of children for someone with a graduate degree earning $60,000?

A. 1.8

B. 2

C. -598

D. 2.9

4. Random sampling improves a study’s:

A. External validity

B. Internal validity

C. Precision

D. Omitted Variable Bias

5. You would like to understand how political leanings affect whether or not people vote.  You decide to specify a linear probability model.  What criticism may people raise:

A. You may get predicted probabilities that are greater than 0.

B. You may get predicted probabilities that are greater than 1.

C. It is hard to assess the magnitude of the relationship with a linear probability model.

D. It is hard to assess the significance of the relationship with a linear probability model.

6. Assume all coffee comes from Dunkin Donuts, Starbucks, or Peets. Which of the following regressions most easily allows you to test whether Starbucks coffee has significantly more caffeine than all other coffees?

A.

B.

C.

D.

7. Steve is exploring the relationship between the price of a house, its number of rooms, and its distance from the subway.  When Steve regresses house prices on the number of rooms, he finds a positive coefficient. Steve then regresses house prices on both the number of rooms and the distance to the subway. He gets a positive coefficient on both variables, though the coefficient on rooms is smaller than before. What does he know about the correlation of rooms and distance?

A.  They are positively correlated

B.  They are negatively correlated

C.  We cannot infer the direction of their correlation

D. They are not correlated

8. A researcher, using a sample of lottery players, regresses life expectancy on a dummy variable for randomly winning a jackpot in the lottery. The researcher considers adding education as another explanatory variable. What is likely to be true?

A. The coefficient on winning a jackpot will change because education affects life expectancy.

B. The coefficient on winning a jackpot will not change because education does not affect life expectancy.

C. The coefficient on winning a jackpot will not change because education and winning a jackpot are not correlated.

D. The coefficient on winning a jackpot will not change because education and life expectancy are not correlated.

9. You run a linear probability model of admission to college on SAT scores.  You find a coefficient of 0.004 on SAT score, with a p-value of 0.02. You can conclude that:

A. Taking the SATs is associated with a 0.4% increase in admission that is significant at the 5% level.

B. There is an increase in the probability of admission that is significant, but you cannot interpret the magnitude.

C. A one point increase in SAT scores raises the predicted probability of admission by 0.4%.

D. A one point increase in SAT scores raises the predicted probability of admission by 0.4 percentage points.

10. You want to know whether a new juice diet introduced this year helps people sleep well. You have observational data on sleep and eating habits and other personal characteristics. What regression has the greatest internal validity?

A.

B.

C.

D.

11. Which of the following is NOT true for a probit model?

A. The outcome variable Y must be a dummy variable.

B. The independent variable X must be a dummy variable.

C. The probit results tell you whether the relationship between Y and X is statistically significant.

D. The probit results tell you the sign of the relationship between Y and X

PART II – SHORT ANSWER

National Basketball League Salaries and Team Performance

You have been hired by the owner of the Boston Celtics to determine whether his team can win more games by spending more money on players’ salaries to recruit better players. He provides you with data on every team’s wins and payrolls for two years, 2000 and 2013. The average team payroll in 2000 was $46 million and $67 million in 2013.

You run the following regressions:

Table 1: Description of Variables

Variable	Description
Wins	Numbers of games won in the season. Each team plays 82 games per season.
Salary	Total Annual Salary of Boston Celtics in Millions of Dollars
Other Teams Salary	Total Annual Salary of the Other 29 Teams in Millions of Dollars

Table 2:  Regressions from NBA Data

1. (4 points) Interpret the coefficient on salary in regression (1). [max 1 sentence]

2. (4 points) Is the coefficient on salary in regression (1) statistically significant at the 5% level? State the null hypothesis, show your work, and explain your conclusion. [max 3 sentences]

3.  (3 points)  What is the predicted number of total wins in regression (1) for a team spending $50 million in salary? [max one sentence]

4. (3 points) Interpret the coefficient on Other Teams Salary in regression (2) (max one sentence)

5. (5 points) Regression (2) demonstrates that the coefficient in regression (1) suffered from omitted variable bias from omitting other team’s salary. Using the omitted variable bias formula, state whether the bias is positive or negative and explain why.     [max 3 sentences]

6. (3 points) Were the results in Regression (1) over or understated?  Explain. [max 1 sentences]

7. (5 points) The owner criticizes your study, claiming the color of the team bus must also factor into the regression formula.  Do you think that not including this variable will generate omitted variable bias?  Explain why or why not?

8. (5 points) The owner of the Celtics objects to your findings. “I spent almost $26 million more in 2013 than I did in 2000, and my team’s record only improved by 6 wins. Doesn’t Regression 2 say it should have improved by 17.4 wins? ” Explain an error in his reasoning.

For course staff only: