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
Original language | English |
---|---|
Pages (from-to) | 871-916 |
Number of pages | 46 |
Journal | Quantitative Economics |
Volume | 11 |
Issue number | 3 |
Early online date | 6 Feb 2020 |
DOIs | |
Publication status | Published - 17 Jul 2020 |
Bibliographical note
Publisher Copyright:Copyright © 2020 The Authors.
Keywords
- average treatment effect
- C14
- C25
- causality
- hazard rate
- identification
- J64
- job search assistance
- kernel hazard estimation
- local linear regression
- Policy evaluation
- regression discontinuity
- selectivity
- youth unemployment
Fingerprint
Dive into the research topics of 'Policy Discontinuity and Duration Outcomes'. Together they form a unique fingerprint.Profiles
-
Professor Gerard J van den Berg
- School of Economics - Honorary Professor
- Bristol Population Health Science Institute
Person: Member, Honorary and Visiting Academic