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 overcomes this by considering spells that include the moment of the policy change and by exploiting variation in the moment at which different cohorts are exposed to the policy change. We prove identification of average treatment effects on hazard rates without model structure. We estimate these effects by kernel hazard regression. We use the introduction of the NDYP program for young unemployed individuals in the UK to estimate average program participation effects on the exit rate to work as well as anticipation effects.

Policy evaluation hazard rate identification causality regression discontinuity selectivity kernel hazard estimation local linear regression average treatment effect job search assistance youth unemployment C14 C25 J64