We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...

This study is an empirical assessment of the impact of the drug decriminalization policy followed by Portugal in July, 2001. We investigate especially the impact of the policy change on the price of illicit drugs. The analysis is performed using a difference-in-differences approach and a...

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that, without additional assumptions, it is not possible to estimate the average treatment effect and treatment on the treated. It is, however,...

Randomized control trials (RCTs) have become increasingly important as an evidence-based method to evaluate interventions such as government programs and policy initiatives. Frequently, however, RCTs are characterized by "imperfect compliance," in that not all the subjects who are randomly...

A key assumption in regression discontinuity analysis is that units cannot manipulate the value of their running variable in a way that guarantees or avoids assignment to the treatment. Standard identification arguments break down if this condition is violated. This paper shows that treatment...

Our research investigates the magnitude of the effect of residential energy efficiency audit programs on later household electricity consumption. These programs are designed to increase awareness of household energy consumption with personalized feedback that will eventually lead to behavioral...