Downloads
wp201327.pdf
PDF | 300.94 KB
A comparison of hazard rates of duration outcomes before and after policy changes is hampered by non-identification if there is unobserved heteogeneity in the effects and no model structure is imposed. We develop a discontinuity approach that overcomes this by exploiting variation in the moment at which different cohorts are exposed to the policy change, i.e. by considering spells crossing the policy change. We prove identification of average treatment effect on hazard rates without model structure. We estimate these effects by local linear kernel hazard regression. We use the introduction of the NDYP programme for young unemployed individuals to estimate average programme participation effects on the exit rate to work.
Authors
Deputy Research Director
Monica is a Deputy Research Director and Professor of Economics at the University of Bristol, with an interest in Labour, Family and Public Economics.
Gerard Van Den Berg
Research Fellow Paris School of Economics
Antoine is a Research Fellow, an Associate Professor at the EHESS, and Director of the Institut des Politiques Publiques (IPP) in Paris.
Working Paper details
- DOI
- 10.1920/wp.ifs.2013.1327
- Publisher
- Institute for Fiscal Studies
Suggested citation
A, Bozio and M, Costa Dias and G, Van Den Berg. (2013). Policy discontinuity and duration outcomes. London: Institute for Fiscal Studies. Available at: https://ifs.org.uk/publications/policy-discontinuity-and-duration-outcomes-0 (accessed: 19 April 2024).
More from IFS
Understand this issue
Gender norms, violence and adolescent girls’ trajectories: Evidence from India
24 October 2022
Raising revenue from closing inheritance tax loopholes
18 April 2024
Sure Start achieved its aims, then we threw it away
15 April 2024
Policy analysis
IFS Deputy Director Carl Emmerson appointed to the UK Statistics Authority Methodological Assurance Review Panel
14 April 2023
ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models
We develop novel methods for estimation and filtering of continuous-time models with stochastic volatility and jumps using so-called Approximate Bayesian Compu- tation which build likelihoods based on limited information.
12 August 2014
Is there really an NHS productivity crisis?
17 November 2023
Academic research
Sample composition and representativeness on Understanding Society
2 February 2024
Understanding Society: minimising selection biases in data collection using mobile apps
2 February 2024
Robust analysis of short panels
8 January 2024