The data set is for 366 student-athletes from a large university for fall and spring semesters. [A similar analysis is in Maloney and McCormick (1993), but here we use a true panel data set.] Because you have two terms of data for each student, an unobserved effects model is appropriate. The primary question of interest is this: Do athletes perform more poorly in school during the semester their sport is in season? i. Use pooled OLS to estimate a model with term GPA ( trmgpa ) as the dependent variable. The explanatory variables are spring , sat , hsperc , female , black , white , frstsem , tothrs , crsgpa , and season . Interpret the coefficient on season . Is it statis- tically significant?
ii. Most of the athletes who play their sport only in the fall are football players. Sup- pose the ability levels of football players differ systematically from those of other athletes. If ability is not adequately captured by SAT score and high school per- centile, explain why the pooled OLS estimators will be biased.
iii. Now, use the data differenced across the two terms. Which variables drop out? Now, test for an in-season effect.
iv. Can you think of one or more potentially important, time-varying variables that have been omitted from the analysis?