The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baseline-pretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing...

This paper identifies sharp bounds on the mean treatment response and average treatment effect under the assumptions of both concave monotone treatment response (concave-MTR) and monotone treatment selection (MTS). We use our bounds and the US National Longitudinal Survey of Youth to estimate...

We propose a specification test for a wide range of parametric models for the conditional distribution function of an outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted estimate of the joint distribution function of the data,...

This paper uses the control function to develop a framework for testing for selection bias. The idea behind our framework is if the usual assumptions hold for matching or IV estimators, the control function identifies the presence and magnitude of potential selection bias. Averaging this...

The Local Average Treatment Effect (LATE) interpretation of the IV estimates of the returns to schooling is becoming increasingly popular. Typically, researchers reporting LATE estimates do not provide systematic evidence that there is substantial heterogeneity across different ability levels in...

In Canada, a policy aiming at helping single parents on social assistance become self-reliant was implemented on an experimental basis. The Self-Sufficiency Entry Effects Demonstration randomly selected a sample of 4,134 single parents who had applied for welfare between January 1994 and March...

This paper considers the problem of making inferences about the effects of a program on multiple outcomes when the assignment of treatment status is imperfectly randomized. By imperfect randomization we mean that treatment status is reassigned after an initial randomization on the basis of...

We provide a simple distribution regression estimator for treatment effects in the difference-in-differences (DiD) design. Our procedure is particularly useful when the treatment effect differs across the distribution of the outcome variable. Our proposed estimator easily incorporates covariates...

The informal sector plays an important role in the functioning of labor markets in emerging economies. To characterize better this highly heterogeneous sector, we conduct a distributional analysis of the earnings gap between informal and formal employment in Brazil, Mexico and South Africa,...