Experimental Estimates of the Impacts of Class Size on Test Scores: Robustness and Heterogeneity

Proponents of class size reductions draw heavily on the results from Project STAR to support their initiatives. Adding to the political appeal of these initiative are reports that minority and economically disadvantaged students received the largest benefits from smaller classes. We extend this research in two directions. First, to address correlated outcomes from the same class size treatment, we account for the over-rejection of the Null hypotheses by using multiple inference procedures. Second, we conduct a more detailed examination of the heterogeneous impacts of class size reductions on measures of cognitive and noncognitive achievement using more flexible models. We find that students with higher test scores received greater benefits from class size reductions. Furthermore, we present evidence that the main effects of the small class treatment are robust to corrections for the multiple hypotheses being tested. However, these same corrections lead the differential impacts of smaller classes by race and freelunch status to become statistically insignificant.class size; multiple inference; unconditional quantile regression; treatment effect heterogeneity; test score gaps; and education experiment

Do Peers Affect Student Achievement in China's Secondary Schools?

Peer effects have figured prominently in debates on school vouchers, desegregation, ability tracking and anti-poverty programs. Compelling evidence of their existence remains scarce for plaguing endogeneity issues such as selection bias and the reflection problem. This paper firmly establishes a link between peer performance and student achievement, using a unique dataset 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 semi-parametric estimates clarify the tradeoffs facing policymakers in exploiting positive peers effects to increase future achievement.

Worker Sorting, Compensating Differentials and Health Insurance: Evidence from Displaced Workers

This article introduces an empirical strategy to the compensating differentials literature that i) allows both individual observed and unobserved characteristics to be rewarded differently in firms based on health insurance provision, and ii) selection to jobs that provide benefits to operate on both sides of the labor market. Estimates of this model are used to directly test empirical assumptions that are made with popular econometric strategies in the health economics literature. Our estimates reject the assumptions underlying numerous cross sectional and longitudinal estimators. We find that the provision of health insurance has influenced wage inequality. Finally, our results suggest there have been substantial changes in how displaced workers sort to firms that offer health insurance benefits over the past two decades. We discuss the implications of our findings for the compensating differentials literature.

The Effect of Adolescent Health on Educational Outcomes: Causal Evidence using ‘Genetic Lotteries’ between Siblings

There has been growing interest in using specific genetic markers as instrumental variables in attempts to assess causal relationships between health status and socioeconomic outcomes, including human capital accumulation. In this paper we use a combination of family fixed effects and genetic marker instruments to show strong evidence that inattentive symptoms of ADHD in childhood and depressive symptoms as an adolescent are linked with years of completed schooling. Our estimates suggest that controlling for family fixed effects is important but these strategies cannot fully account for the endogeneity of poor mental heath. Finally, our results demonstrate that the presence of comorbid conditions present immense challenges for empirical studies that aim to estimate the impact of specific health conditions.Education Outcomes, Depression, Genetic Markers, ADHD, Obesity, Family Fixed Effects, and Instrumental Variables

Randomization, Endogeneity and Laboratory Experiments

In conducting experiments with multiple trials, outcomes from previous trials can impact on current behavior. One of the most obvious cases in which this can happen, and the case considered in this paper, is in an auction market experiment, where earnings from previous auction trials alter cash balances which, in turn, can affect bidding behavior. (The most obvious mechanism for such a result, within standard theory, is if bidders are risk averse and do not have constant absolute risk aversion. One can imagine a number of non-standard reasons for such effects as well.) Use of OLS regressions with cash balances included as a right hand side variable are likely to lead to a biased estimate of the cash balance effect since the variation in cash balances is largely related to differences in bidding strategies across individuals. Fixed effect regressions can commonly control for these endogeniety problems at the potential cost of obtaining inefficient estimates, since this estimator does not exploit between-individual variation. This paper addresses this problem in two ways. First we consider an experimental design that reduces the potential bias of OLS estimates while increasing the precision of fixed effect estimates. Second, we consider instrumental variables estimation of the cash balance effect where the instruments are produced by the experimental design. To the best of our knowledge, neither of these approaches has been explored in the experimental literature.

Estimating Treatment Effects from Contaminated Multi-Period Education Experiments: The Dynamic Impacts of Class Size Reductions

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 class in all cognitive subject areas in kindergarten and the first grade. We do not find any statistically significant dynamic benefits from continuous treatment versus never attending small classes following grade one. Finally, statistical tests support accounting for both selective attrition and noncompliance with treatment assignment.

The Impact of Poor Health on Education: New Evidence Using Genetic Markers

This paper examines the influence of health conditions on academic performance during adolescence. To account for the endogeneity of health outcomes and their interactions with risky behaviors we exploit natural variation within a set of genetic markers across individuals. We present strong evidence that these genetic markers serve as valid instruments with good statistical properties for ADHD, depression and obesity. They help to reveal a new dynamism from poor health to lower academic achievement with substantial heterogeneity in their impacts across genders. Our investigation further exposes the considerable challenges in identifying health impacts due to the prevalence of comorbid health conditions and endogenous health behaviors.

Using Genetic Lotteries within Families to Examine the Causal Impact of Poor Health on Academic Achievement

While there is a well-established, large positive correlation between mental and physical health and education outcomes, establishing a causal link remains a substantial challenge. Building on findings from the biomedical literature, we exploit specific differences in the genetic code between siblings within the same family to estimate the causal impact of several poor health conditions on academic outcomes. We present evidence of large impacts of poor mental health on academic achievement. Further, our estimates suggest that family fixed effects estimators by themselves cannot fully account for the endogeneity of poor health. Finally, our sensitivity analysis suggests that these differences in specific portions of the genetic code have good statistical properties and that our results are robust to reasonable violations of the exclusion restriction assumption.

Reinvestigating How Welfare Reform Influences Labor Supply: A Multiple Testing Approach *

Abstract Economic theory suggests that individual responses to welfare reform depend on pretreatment labor supply and other characteristics. Resulting changes in earnings may be positive or negative, leading to heterogenous treatment effects. In this paper, we extend the literature on treatment effect heterogeneity by introducing six nonparametric tests that are implemented using bootstrap testing of functional inequalities. The proposed tests view treatment effect heterogeneity as a multiple testing problem and make corrections for the family-wise error rate. To facilitate comparisons to the existing literature we re-examine the extent of heterogeneity in labor supply responses to the Jobs First welfare experiment across both quantiles of the earnings distribution and individual subgroups. Our results shed new light on who truly benefits from welfare reform and demonstrate the importance of correcting for multiple testing. Keywords: multiple testing, bootstrap tests, quantile treatment effects, welfare reform, labor supply JEL classification: C12, C21, I38, J22 * We wish to thank participants at the 2014 CLSRN annual conference for helpful comments and suggestions. Jacob Schwartz provided excellent research assistance. Lehrer and Song respectively wish to thank SSHRC for research support. The usual caveat applies