Identification and Estimation of Continuous-Time Job Search Models with Preference Shocks

Peter Arcidiacono (), Attila Gyetvai (), Arnaud Maurel and Ekaterina Jardim
Additional contact information
Peter Arcidiacono: Duke University
Attila Gyetvai: Banco de Portugal
Ekaterina Jardim: Amazon

No 18309, IZA Discussion Papers from IZA Network @ LISER

Abstract: This paper applies some of the key insights of dynamic discrete choice models to continuous-time job search models. Our framework incorporates preference shocks into search models, resulting in a tight connection between value functions and conditional choice probabilities. In this environment, we establish constructive identification of the model parameters, including the wage offer distributions off- and on-the-job. Our framework makes it possible to estimate nonstationary search models in a simple and tractable way, without having to solve any differential equations. We apply our method using Hungarian administrative data. Longer unemployment durations are associated with lower offer arrival rates, resulting in accepted wages falling over time. Counterfactual simulations indicate that increasing unemployment benefits by 90 days results in a 14-day increase in expected unemployment duration.

Keywords: dynamic discrete choice; identification; job search (search for similar items in EconPapers)
JEL-codes: C31 C41 J31 J64 (search for similar items in EconPapers)
Date: 2025-12
New Economics Papers: this item is included in nep-dcm, nep-dge and nep-lma
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https://docs.iza.org/dp18309.pdf (application/pdf)

Related works:
Working Paper: Identification and Estimation of Continuous-Time Job Search Models with Preference Shocks (2025)
Working Paper: Identification and Estimation of Continuous-Time Job Search Models with Preference Shocks (2025)
Working Paper: Identification and Estimation of Continuous-Time Job Search Models with Preference Shocks (2022)
Working Paper: Identification and Estimation of Continuous-Time Job Search Models with Preference Shocks (2022)
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