A semi-nonparametric estimator of regression discontinuity design with discrete duration outcomes

We consider the regression discontinuity (RD) design with the duration outcome which has discrete support. The parameters of policy interest are treatment effects on unconditional (duration effect) and conditional (hazard effect) exiting probabilities for each discrete level. We propose a novel semi...

Full description

Saved in:
Bibliographic Details
Published in:Journal of econometrics 2018-09, Vol.206 (1), p.258-278
Main Author: Xu, Ke-Li
Format: Article
Language:English
Subjects:
Analysis
Business schools
Competing risks models
Discontinuity
Econometrics
Estimating techniques
Generalized wald test
Grouped duration data
Nonparametric statistics
Proportional hazard
Regression analysis
Regression discontinuity
Semi-nonparametric models
Series estimator
Treatment effects
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We consider the regression discontinuity (RD) design with the duration outcome which has discrete support. The parameters of policy interest are treatment effects on unconditional (duration effect) and conditional (hazard effect) exiting probabilities for each discrete level. We propose a novel semi-nonparametric estimator which exploits a flexible separability structure of the underlying continuous-time duration process. Simultaneous inference over discrete levels is nonstandard since the asymptotic variance matrix is singular with unknown rank. The peculiarity is delivered by the nature of the RD estimand, and we provide solutions. Random censoring and competing risks can also be allowed in our framework.
ISSN:0304-4076
1872-6895
DOI:10.1016/j.jeconom.2018.06.018