Class Size and Student Achievement: Experimental Estimates of Who Benefits and Who Loses from Reductions

Class size proponents 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 economic disadvantaged students receive the largest benefits. To explore and truly understand the heterogeneous impacts of class size and student achievement requires more flexible estimation approaches. We consider several semi and nonparametric strategies and find strong evidence that i) higher ability students gain the most from class size reductions while many low ability students do not benefit from these reductions, ii) there are no significant benefits in reducing class size from 22 to 15 students in any subject area, iii) no additional benefits from class size reductions for minority or disadvantaged students, iv) significant heterogeneity in the effectiveness of class size reductions across schools and in parental and school behavioural responses.Class size, Academic performance, Project STAR, Economic disadvantaged students, Minority students

Estimating Dynamic Treatment Effects from Project STAR

This paper considers the analysis of data from randomized trials which offer a sequence of interventions and suffer from a variety of problems in implementation. In experiments that provide treatment in multiple periods (T>1), subjects have up to 2^{T}-1 counterfactual outcomes to be estimated to determine the full sequence of causal effects from the study. Traditional program evaluation and non-experimental estimators are unable to recover parameters of interest to policy makers in this setting, particularly if there is non-ignorable attrition. We examine these issues in the context of Tennessee's highly influential randomized class size study, Project STAR. We demonstrate how a researcher can estimate the full sequence of dynamic treatment effects using a sequential difference in difference strategy that accounts for attrition due to observables using inverse probability weighting M-estimators. These estimates allow us to recover the structural parameters of the small class effects in the underlying education production function and construct dynamic average treatment effects. We present a complete and different picture of the effectiveness of reduced class size and find that accounting for both attrition due to observables and selection due to unobservables is crucial and necessary with data from Project STAREducation, Attrition, Non-Compliance, Sequential Difference in Difference, Class Size reduction

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 is among the first to firmly establish the 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.Peer Effects, Ability Grouping, Selection on observables, China, Academic performance, Teacher quality

Matching using Semiparametric Propensity Scores

Propensity score matching is becoming increasingly common in clinical medicine, demographic and economic research for the evaluation of the magnitude of treatment effects. Existing studies generally use parametric estimators of binary response models such as the probit and logit to estimate the propensity score, which imposes strong distributional assumptions on the error term that are often violated with the underlying data. This paper considers matching using semiparametrically estimated propensity scores. Our approach allows for heterogeneity in response across observed covariates along the conditional willingness to participate in the treatment intervention distribution. Data from the NSW experiment, CPS and PSID are used to evaluate the performance of alternative matching estimators. Preliminary estimates indicate mean absolute bias error reductions between 6.2% and 706% of the experimental treatment impact with stratification matching using semiparametric propensity score estimates relative to matching algorithms that employ parametric propensity scoresPropensity Score matching, program evaluation, Binary quantile regression and heterogeneity

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.

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

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

Worker Sorting, Health Insurance and Wages: Further Evidence from Displaced Workers in the United States

The United States has the distinction of being the only industrialized nation without universal health insurance. Health insurance may have impacts on the US labor market. We use data on displaced workers over a 25 year period to document how the role of health insurance on wages and worker sorting has evolved. We find that the provision of health insurance increasingly influences wage inequality. Our results indicate that the portion of the unadjusted wage gap due only to selection bias from unobserved (to the analyst) characteristics, such as ability or innate health status has grown rapidly since 2000. Further, while there have been substantial changes in how displaced workers sort to firms that offer health insurance benefits over the last 25 years, many of the patterns have reversed directions over the past six years. Finally, we discuss the policy implications of our results.Health insurance; Worker sorting; Displacement; Comparative advantage; Non-linear instrumental variables

Bargaining in Legislatures: An Experimental Investigation of Open versus Closed Amendment Rules

We investigate the Baron and Ferejohn (1989) noncooperative game theoretic bargaining model of legislative equilibrium. Legislative outcomes are sensitive to formal rules specifying who may make proposals and how they will be voted on. With a random proposal recognition rule and a closed amendment rule (proposals are voted up or down with no room for amendments) the model predicts no delays in benefit allocation, that benefits will be allocated to a minimal winning coalition, and that benefits within the coalition will be strongly skewed in favor of the proposer. In contrast, with a random proposal recognition rule and an open amendment rule (proposals may be amended before they are voted on) the model predicts delays in benefit allocation, that benefits will be more evenly spread among winning coalition members, and that coalitions need not be restricted to a minimal majority. With experience we find strong qualitative support for the model's predictions: All proposals are passed without delay with the closed rule versus 81% of all proposals with the open rule. Minimal winning coalitions are effectively proposed in 67% of all cases with the closed rule versus 4% with the open rule, and benefits are more evenly distributed with open rule. Quantitative predictions of the model fail however: Most importantly, proposers consistently fail to allocate themselves anything close to what the theory predicts. Further, the probability of immediate acceptance is much higher than predicted in the open rule as proposers consistently expand the winning coalition beyond the model's prediction in attempts to limit amendments. The evolution of play over time is reported (outcomes under both treatments are much more similar early on then later). Tests show that subjects' votes in favor of a proposed allocation are significantly affected by their own share (in the expected direction) but that the distribution of shares across all voters has no significant effect.