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...

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,...

University fees have recently trebled in England, prompting fears that young people may be put off from participating in higher education. We investigate students' knowledge and their receptiveness to information campaigns about the costs and benefits of staying on in education. We compare the...

The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption or on the availability of an instrument. When available, instruments may also be used to test for the unconfoundedness assumption (exogeneity of the...