Estimation of Heterogeneous Treatment Effects on Hazard Rates

Simen Gaure, Knut Røed (), Gerard van den Berg and Tao Zhang ()
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Tao Zhang: Ragnar Frisch Centre for Economic Research

No 4794, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Consider a setting where a treatment that starts at some point during a spell (e.g. in unemployment) may impact on the hazard rate of the spell duration, and where the impact may be heterogeneous across subjects. We provide Monte Carlo evidence on the feasibility of estimating the distribution of treatment effects from duration data with selectivity, by means of a nonparametric maximum likelihood estimator with unrestricted numbers of mass points for the heterogeneity distribution. We find that specifying the treatment effect as homogenous may yield misleading average results if the true effects are heterogeneous, even when the sorting into treatment is appropriately accounted for. Specifying the treatment effect as a random coefficient allows for precise estimation of informative average treatment effects including the program’s overall impact on the mean duration.

Keywords: duration analysis; unobserved heterogeneity; program evaluation; nonparametric estimation; Monte Carlo simulation; timing of events; random effects (search for similar items in EconPapers)
JEL-codes: C31 C41 C63 J64 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2010-02
New Economics Papers: this item is included in nep-ecm and nep-lab
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Citations: View citations in EconPapers (1)

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