Distribution regression in duration analysis: an application to unemployment spells

Lecture notes in statistics: Proceedings

Miguel Delgado (), Andrés García-Suaza and Pedro H C Sant’Anna
Authors registered in the RePEc Author Service: Andres Garcia-Suaza

The Econometrics Journal, 2022, vol. 25, issue 3, 675-698

Abstract: SummaryThis article proposes inference procedures for distribution regression models in duration analysis using randomly right-censored data. This generalizes classical duration models by allowing situations where explanatory variables’ marginal effects freely vary with duration time. The article discusses applications to testing uniform restrictions on the varying coefficients, inferences on average marginal effects, and others involving conditional distribution estimates. Finite sample properties of the proposed method are studied by means of Monte Carlo experiments. Finally, we apply our proposal to study the effects of unemployment benefits on unemployment duration.

Keywords: Conditional distribution; duration models; random censoring; unemployment duration; varying coefficients model (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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Working Paper: Distribution Regression in Duration Analysis: an Application to Unemployment Spells (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:emjrnl:v:25:y:2022:i:3:p:675-698.

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