Using the Youth in Transition Survey, we estimate a Roy model with a three-dimensional latent factor structure to consider how parental valuation of education, cognitive skills, and noncognitive skills influence endogenous schooling decisions and subsequent labor market outcomes. We find that the effect of cognitive skills on adult incomes arises by increasing the likelihood of obtaining further education. Furthermore, we find that both noncognitive skills and parental valuation for education play a larger role in determining income at age 25 than cognitive skills. Last, our analysis uncovers striking differences between men and women in several of the estimated relationships.

We provide evidence on the distributional effects of Quebec’s universal child care policy. Our analysis uncovers substantial policy relevant heterogeneity in the estimated effect of access to subsidized child care across two developmental score distributions for children from two-parent families. Whereas past research reported findings of negative effects on mothers and children from these families, igniting controversy, our estimates reveal a more nuanced image that formal child care can indeed boost developmental outcomes for children from some households: particularly disadvantaged single-parent households. We present suggestive evidence that the heterogeneity in policy effects is consistent with differences in home learning environments.

Business decision makers are increasingly using predictive social media analytic tools in forecasting exercises but ignoring potential model uncertainty. Using data on the universe of Twitter messages, we calculate the sentiment regarding each film to understand whether these opinions affect box office opening and DVD retail sales. Our results contrasting eleven different econometric strategies including penalization methods indicate that accounting for model uncertainty can lead to large gains in forecast accuracy. While penalization methods do not outperform model averaging on forecast accuracy, evidence indicates they perform equivalently at the variable selection stage. Finally, incorporating social media data greatly improves forecast accuracy.

This paper introduces an empirical strategy to estimate dynamic treatment effects in randomized trials that provide treatment in multiple stages and in which various noncompliance problems arise, such as attrition and selective transitions between treatment and control groups. Our approach is applied to the highly influential four-year randomized class size study, Project STAR. We find benefits from attending small classes in all cognitive subject areas in kindergarten and first grade. We do not find any statistically significant dynamic benefits from continuous treatment versus never attending small classes following grade 1. Finally, statistical tests support accounting for both selective attrition and noncompliance with treatment assignment.

Peer effects have figured prominently in debates on school vouchers, desegregation, ability tracking, and antipoverty programs. Compelling evidence of their existence remains scarce for plaguing endogeneity issues such as selection bias and the reflection problem. This paper is among the first to firmly establish the link between peer performance and student achievement, using a unique data set from China. We find strong evidence that peer effects exist and operate in a positive and nonlinear manner; reducing the variation of peer performance increases achievement; and our semiparametric estimates clarify the trade-offs facing policymakers in exploiting positive peer effects to increase future achievement.