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Machine learning algorithms for predicting unemployment duration in Russia

Author

Listed:
  • Anna A. Maigur

    (Gaidar Institute for Economic Policy, Moscow, Russia)

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.

Suggested Citation

  • Anna A. Maigur, 2024. "Machine learning algorithms for predicting unemployment duration in Russia," Russian Journal of Economics, ARPHA Platform, vol. 10(4), pages 365-384, December.
    • Handle: RePEc:arh:jrujec:v:10:y:2024:i:4:p:365-384
    DOI: 10.32609/j.ruje.10.128611
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    More about this item

    Keywords

    unemployment duration survival analysis machine learning models.;

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy

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