Year: 2025
Type: article
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.
Source: Econometrics
Authors: Miguel A. Delgado, Andrés García-Suaza
Institutions: Universidad Carlos III de Madrid, Universidad del Rosario
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
SDG: Reduced inequalities
Open Access status: gold
Estimated APC paid: $1,689
OpenAlex ID: W4415684908