Suppose you want to test whether girls who attend a girls' high school do better in math than girls who attend co-ed (mixed-gender) schools. You have a random sample of senior high school girls from a state in the United States. Let score be the score on a standardized math test. Let girlhs be a dummy variable indicating whether a student attends a girls' high school. 1. What other factors would you control for in the equation? (You should be able to reasonably collect data on the factors you mention.) 2. Write an equation relating score to girlhs and the other factors you listed in part (1). 3. Suppose that parental moral support and motivation are unmeasured factors in the error term in part (2). Are these likely to be correlated with girlhs? Explain what are the problems that this creates in your model. 4. Discuss the assumptions needed for the number of girls' high schools within a 20-mile radius of a girl's home to be a valid IV for girlhs. 5. Suppose that, when you estimate the reduced form for girlshs, you find that the coefficient on numghs (the number of girls' high schools within a 20-mile radius) is negative and statistically significant. Would you feel comfortable proceeding with IV estimation where numghs is used as an IV for girlshs? Explain.
Suppose you want to test whether girls who attend a girls' high school do better in math than girls who attend co-ed (mixed-gender) schools. You have a random sample of senior high school girls from a state in the United States. Let score be the score on a standardized math test. Let girlhs be a dummy variable indicating whether a student attends a girls' high school. 1. What other factors would you control for in the equation? (You should be able to reasonably collect data on the factors you mention.) 2. Write an equation relating score to girlhs and the other factors you listed in part (1). 3. Suppose that parental moral support and motivation are unmeasured factors in the error term in part (2). Are these likely to be correlated with girlhs? Explain what are the problems that this creates in your model. 4. Discuss the assumptions needed for the number of girls' high schools within a 20-mile radius of a girl's home to be a valid IV for girlhs. 5. Suppose that, when you estimate the reduced form for girlshs, you find that the coefficient on numghs (the number of girls' high schools within a 20-mile radius) is negative and statistically significant. Would you feel comfortable proceeding with IV estimation where numghs is used as an IV for girlshs? Explain.
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
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Transcribed Image Text:Problem 3 (Wooldridge 15.8):
Suppose you want to test whether girls who attend a girls' high school do better in math than girls
who attend co-ed (mixed-gender) schools. You have a random sample of senior high school girls
from a state in the United States. Let score be the score on a standardized math test. Let girlhs
be a dummy variable indicating whether a student attends a girls' high school.
1. What other factors would you control for in the equation? (You should be able to reasonably
collect data on the factors you mention.)
2. Write an equation relating score to girlhs and the other factors you listed in part (1).
3. Suppose that parental moral support and motivation are unmeasured factors in the error term
in part (2). Are these likely to be correlated with girlhs? Explain what are the problems that
this creates in your model.
4. Discuss the assumptions needed for the number of girls' high schools within a 20-mile radius
of a girl's home to be a valid IV for girlhs.
5. Suppose that, when you estimate the reduced form for girlshs, you find that the coefficient on
numghs (the number of girls' high schools within a 20-mile radius) is negative and statistically
significant. Would you feel comfortable proceeding with IV estimation where numghs is used
as an IV for girlshs? Explain.
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