Beyhum, Jad, Florens, Jean-Pierre and Van Keilegom, Ingrid (2022) Nonparametric Instrumental Regression With Right Censored Duration Outcomes. Journal of Business and Economic Statistics, vol.40 (n°3). pp. 1034-1045.

Full text not available from this repository.
Identification Number : 10.1080/07350015.2021.1895814


This article analyzes the effect of a discrete treatment Z on a duration T. The treatment is not randomly assigned. The confounding issue is treated using a discrete instrumental variable explaining the treatment and independent of the error term of the model. Our framework is nonparametric and allows for random right censoring. This specification generates a nonlinear inverse problem and the average treatment effect is derived from its solution. We provide local and global identification properties that rely on a nonlinear system of equations. We propose an estimation procedure to solve this system and derive rates of convergence and conditions under which the estimator is asymptotically normal. When censoring makes identification fail, we develop partial identification results. Our estimators exhibit good finite sample properties in simulations. We also apply our methodology to the Illinois Reemployment Bonus Experiment.

Item Type: Article
Language: English
Date: 2022
Refereed: Yes
Place of Publication: Washington
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 23 Mar 2023 11:54
Last Modified: 23 Mar 2023 11:55
OAI Identifier:
View Item