In difference-in-differences applications, identification of the key parameter often arises from changes in policy by a small number of groups. In contrast, typical inference assumes that the number of groups changing policy is large. We present an alternative inference approach for a small (finite) number of policy changers, using information from a large sample of nonchanging groups. Treatment effect point estimators are not consistent, but we can consistently estimate their asymptotic distribution under any point null hypothesis about the treatment. Thus, treatment point estimators can be used as test statistics, and confidence intervals can be constructed using test statistic inversion.

This paper explores issues that arise in the evaluation of social programs using experimental data in the frequently encountered case where some of the experimental treatment group members drop out of the program prior to receiving treatment. We begin with the standard estimator for this case and the identifying assumption upon which it rests. We then examine the behavior of the estimator when the dropouts receive a partial “dose” of the program treatment prior to dropping out of the program. In the case of partial treatment, the identifying assumption is typically violated, thereby making the estimator inconsistent for the conventional parameter of interest: the impact of full treatment on the fully treated. We develop a test of the identifying assumption underlying the standard estimator and consider whether exclusion restrictions produce identification of the mean impact of the program when this assumption fails to hold. Finally, we discuss alternative parameters of interest in the presence of partial treatment among the dropouts and argue that the conventional parameter is not always the economically interesting one. We apply our methods to data from a recent experimental evaluation of the Job Training Partnership Act (JTPA) program.

Using Selection on Observed Variables to Assess Bias from Unobservables When Evaluating Swan-Ganz Catheterization by Joseph G. Altonji, Todd E. Elder and Christopher R. Taber. Published in volume 98, issue 2, pages 345-50 of American Economic Review, May 2008

In this paper we measure the effect of Catholic high school attendance on educational attainment and test scores. Because we do not have a good instrumental variable for Catholic school attendance, we develop new estimation methods based on the idea that the amount of selection on the observed explanatory variables in a model provides a guide to the amount of selection on the unobservables. We also propose an informal way to assess selectivity bias based on measuring the ratio of selection on unobservables to selection on observables that would be required if one is to attribute the entire effect of Catholic school attendance to selection bias. We use our methods to estimate the effect of attending a Catholic high school on a variety of outcomes. Our main conclusion is that Catholic high schools substantially increase the probability of graduating from high school and, more tentatively, attending college. We find little evidence of an effect on test scores.

Joseph Altonji is one of the pioneers of modern labor economics. To mark Joe’s sixty-fifth birthday and honor his illustrious career, a conference was held at his alma mater and employer, Yale University, on September 7–8, 2018. This special issue contains seven of the papers presented by former students, coauthors, and colleagues. Joe has been central to the empirical revolution that has brought vast amounts of individual-level data to some of the most important questions ofbothmicroandmacroeconomics.His seminal breakthroughshave changed thewaywe think aboutnumerous topics, including the studyof consumption behavior and labor supply over time, intrafamily insurance, discrimination, wage determination and learning, school choice and school quality, returns to higher education, and the stochastic process of income. The hallmark of all thiswork is a thoughtful combination of theory anddata, the development ofnewempiricalmethods, thediscoveryofnovel identificationstrategies, and extreme care with extensive robustness checks and attention to data details. Early on in his career Joe was one of the first to develop our understanding of the relationship between intratemporal and intertemporal allocations and the implication this distinction has on estimating elasticities. These

This paper defines and estimates general equilibrium treatment effects. The conventional approach in the literature on treatment effects ignores interactions among individuals induced by the policy interventions being studied. Focusing on the impact of tuition policy, and using estimates from our dynamic overlapping generations general equilibrium model of capital and human capital formation, we find that general equilibrium impacts of tuition on college enrollment are an order of magnitude smaller than those reported in the literature on microeconomic treatment effects. The assumptions used to justify the LATE parameter in a partial equilibrium setting do not hold in a general equilibrium setting. Policy changes induce two way flows. We extend the LATE concept to a general equilibrium setting. We present a more comprehensive evaluation to program evaluation by considering both the tax and benefit consequences of the program being evaluated and placing the analysis in a market setting.

Missing from recent discussions of tax reform is any systematic analysis of the effects of various tax proposals on skill formation. This gap in the literature in empirical public finance is due to the absence of any empirically based general equilibrium models with both human capital formation and physical capital formation that are consistent with observations on modern labor markets. This paper is a progress report on our ongoing research on formulating and estimating dynamic general equilibrium models with endogenous heterogeneous human capital accumulation. Our model explains many features of rising wage inequality in the U.S. economy (James Heckman, Lance Lochner and Christopher Taber, 1998). In this paper, we use our model to study the impacts on skill formation of proposals to switch from progressive taxes to flat income and consumption taxes. For the sake of brevity, we focus on steady states in this paper, although we study both transitions and steady states in our research.

We derive a formula to determine the degree to which a school choice program may harm public school stayers by luring the best students to other schools. The “cream skimming” effect is increasing in the degree of heterogeneity within schools, the school choice take-up rate of strong students relative to weak students, and the dependence of school outcomes on student body quality. We use the formula to investigate the cream skimming effect of hypothetical voucher programs on the high school graduation rate and other outcomes of the students who would remain in public school. We find small effects across a wide variety of model specifications and types of modest voucher programs.