Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/253557 
Year of Publication: 
2020
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 11 [Issue:] 3 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2020 [Pages:] 871-916
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
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.
Subjects: 
Policy evaluation
hazard rate
identification
causality
regression discontinuity
selectivity
kernel hazard estimation
local linear regression
average treatment effect
job search assistance
youth unemployment
JEL: 
C14
C25
J64
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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