Counterfactual Duration Analysis

Miguel A. Delgado () and Andrés García-Suaza
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Miguel A. Delgado: Department of Economics, Universidad Carlos III de Madrid, 28903 Madrid, Spain
Andrés García-Suaza: School of Economics, Universidad del Rosario, Bogota 111711, Colombia

Econometrics, 2025, vol. 13, issue 4, 1-20

Abstract: This article introduces new counterfactual standardization techniques for comparing duration distributions subject to random censoring through counterfactual decompositions. The counterfactual distribution of one population relative to another is computed after estimating the conditional distribution, using either a semiparametric or a nonparametric specification. We consider both the semiparametric proportional hazard model and a fully nonparametric partition-based estimator. The finite-sample performance of the proposed methods is evaluated through Monte Carlo experiments. We also illustrate the methodology with an application to unemployment duration in Spain during the period between 2004 and 2007, focusing on gender differences. The results indicate that observable characteristics account for only a small portion of the observed gap.

Keywords: standardizations; censored data; Cox’s proportional hazard model; Kaplan–Meier estimator; unemployment gender gaps (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:13:y:2025:i:4:p:42-:d:1782811

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