Consider a setting where a treatment that starts at some point during a spell (e.g. in unemployment) may impact on the hazard rate of the spell duration, and where the impact may be heterogeneous across subjects. We provide Monte Carlo evidence on the feasibility of estimating the distribution...

We develop a nonparametric instrumental variable approach for the estimation of average treatment effects on hazard rates and conditional survival probabilities, without model structure. We derive constructive identification proofs for average treatment effects under noncompliance and dynamic...

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...

Causal effects of a policy change on hazard rates of a duration outcome variable are not identified from a comparison of spells before and after the policy change, if there is unobserved heterogeneity in the effects and no model structure is imposed. We develop a discontinuity approach that...

We propose and implement a new method to estimate treatment effects in settings where individuals need to be in a certain state (e.g. unemployment) to be eligible for a treatment, treatments may commence at different points in time, and the outcome of interest is realized after the individual...