Machine learning algorithms for predicting unemployment duration in Russia

Anna A. Maigur ()
Additional contact information
Anna A. Maigur: Gaidar Institute for Economic Policy, Moscow, Russia

Russian Journal of Economics, 2024, vol. 10, issue 4, 365-384

Abstract: Predictions of the individual unemployment duration will allow to distribute target support while searching for a job more effectively. The paper uses survival models to predict the unemployment duration based on data from Russian employment centers in 2017–2021. The dataset includes socio-demographic characteristics, such as age, gender, education level, etc., as well as the job search duration. Two models' forecasts are investigated: the proportional and the non-proportional hazards models. Both models take into account censored data, but only the second one captures nonlinear dependencies and the disproportionate influence of independent variables over time. The forecast quality is estimated with the C-index, equality of which to 1 indicates the most accurate forecast. The highest index value is demonstrated by the non-proportional hazards model (0.64). Moreover, it was found that variable that contributes the most to the prediction quality is region of a job search so that job-search time is heterogeneous among different regional labour markets. To sum up, forecast quality is quite high and stable over time and the implementation of model forecasts by employment centers will increase their efficiency.

Keywords: unemployment; duration; survival; analysis; machine; learning; models. (search for similar items in EconPapers)
JEL-codes: C34 C41 C45 C52 C53 J64 J68 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://rujec.org/article/128611/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arh:jrujec:v:10:y:2024:i:4:p:365-384

DOI: 10.32609/j.ruje.10.128611

Access Statistics for this article

Russian Journal of Economics is currently edited by Alexey Kudrin

More articles in Russian Journal of Economics from ARPHA Platform
Bibliographic data for series maintained by Teodor Georgiev ().