Noah Deitrick and Adam Streff provided excellent research assistance. All errors that remain are ours. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Noah Deitrick and Adam Streff provided excellent research assistance. All errors that remain are ours. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

While instructional time is viewed as crucial to learning, little is known about the effectiveness of reducing absences relative to increasing the number of school days. In this regard, this paper jointly estimates the effect of absences and length of the school calendar on test score performance. Using administrative data from North Carolina public schools, we exploit a state policy that provides variation in the number of days prior to standardized testing and find substantial differences between these effects. Extending the school calendar by ten days increases math and reading test scores by only 0.8% and 0.2% of a standard deviation, respectively; a similar reduction in absences would lead to gains of 5.8% and 3% in math and reading. We perform a number of robustness checks including utilizing u data to instrument for absences, family-year fixed effects, separating excused and unexcused absences, and controlling for a contemporaneous measure of student disengagement. Our results are robust to these alternative specifications. In addition, our findings indicate considerable heterogeneity across student ability, suggesting that targeting absenteeism among low performing students could aid in narrowing current gaps in performance.

At the private university we analyze, the gap between white and black grade point averages falls by half between the students' freshmen and senior year. This outcome could suggest that affirmative action policies are playing a key role to reduce racial differences. However, this convergence masks two effects. First, the variance of grades given falls across time. Hence, shrinkage in the level of the gap may not imply shrinkage in the class rank gap. Second, grading standards differ across courses in different majors. We show that controlling for these two features virtually eliminates any convergence of black/white grades. In fact, black/white gpa convergence is symptomatic of dramatic shifts by blacks from initial interest in the natural sciences, engineering, and economics to majors in the humanities and social sciences. We show that natural science, engineering, and economics courses are more difficult, associated with higher study times, and have harsher grading standards; all of which translate into students with weaker academic backgrounds being less likely to choose these majors. Indeed, we show that accounting for academic background can fully account for average differences in switching behavior between blacks and whites.

We examine differences in minority science graduation rates among University of California campuses when racial preferences were in place. Less prepared minorities at higher ranked campuses had lower persistence rates in science and took longer to graduate. We estimate a model of students' college major choice where net returns of a science major differ across campuses and student preparation. We find less prepared minority students at top ranked campuses would have higher science graduation rates had they attended lower ranked campuses. Better matching of science students to universities by preparation and providing information about students' prospects in different major-university combinations could increase minority science graduation. (JEL D14, E23, E32, E43, E52, E61, E62)

This paper investigates the role played by informational frictions in college and the workplace. We estimate a dynamic structural model of schooling and work decisions, where individuals have imperfect information about their schooling ability and labor market productivity. We take into account the heterogeneity in schooling investments by distinguishing between two-and four-year colleges, graduate school, as well as science and non-science majors for four-year colleges. Individuals may also choose whether to work full-time, part-time, or not at all. A key feature of our approach is to account for correlated learning through college grades and wages, whereby individuals may leave or re-enter college as a result of the arrival of new information on their ability and productivity. Our findings indicate that the elimination of informational frictions would increase the college graduation rate by 9 percentage points, and would increase the college wage premium by 32.7 percentage points through increased sorting on ability.

Partial funding for Arcidiacono came from the Searle Freedom Trust. We thank seminar participants at NYU, Oxford, and the 2012 Brookings conference on The Effects of Racial Preferences on Student Outcomes for helpful comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We argue that once we take into account the students' rational enrollment decisions, mismatch in the sense that the intended beneficiary of affirmative action admission policies are made worse off could occur only if selective universities possess private information about students' post-enrollment treatment effects. This necessary condition for mismatch provides the basis for a new test. We propose an empirical methodology to test for private information in such a setting. The test is implemented using data from Campus Life and Learning Project (CLL) at Duke. Evidence shows that Duke does possess private information that is a statistically significant predictor of the students' post-enrollment academic performance. We also propose strategies to evaluate more conclusively whether the evidence of Duke private information has generated mismatch.