Beyhum, Jad, Florens, Jean-Pierre and Van Keilegom, Ingrid (2020) Nonparametric Instrumental Regression with Right Censored Duration Outcomes. TSE Working Paper, n. 20-1164, Toulouse

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This paper analyzes the effect of a discrete treatment Z on a duration T. The
treatment is not randomly assigned. The confoundingness 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: Monograph (Working Paper)
Language: English
Date: November 2020
Place of Publication: Toulouse
Uncontrolled Keywords: Duration Models, Endogeneity, Instrumental variable, Nonseparability, Partial identification
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 08 Dec 2020 14:35
Last Modified: 27 Oct 2021 13:38
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