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Identifying Turning Points in Bank of Russia Business Activity Indicators Using Machine Learning Methods

Author

Listed:
  • Valeria Zvereva

    (Bank of Russia; HSE University)

  • Anna Krupkina

    (Bank of Russia)

  • Andrey Andreev

    (Bank of Russia)

  • Oleg Semiturkin

    (Bank of Russia)

  • Maria Kudaeva

    (Bank of Russia)

Abstract

This study develops a methodology for identifying threshold values of Bank of Russia business activity indicators to determine business cycle phases using machine learning classification models. The study relies on monthly monitoring of businesses data from the Bank of Russia for the period from January 2009 to September 2025. The greatest contribution to the model predictions comes from the following monitoring indicators: enterprises' assessments of actual demand for products, business climate indicators, and enterprise expectations regarding changes in production volumes over the next three months. Comparative accuracy analysis shows the systematic superiority of ensemble methods (e.g. bagging and various types of boosting) over parametric models. The obtained threshold values make it possible to formalise and strengthen the analytical basis for expert judgements on the current phase of the business cycle using Bank of Russia survey data.

Suggested Citation

  • Valeria Zvereva & Anna Krupkina & Andrey Andreev & Oleg Semiturkin & Maria Kudaeva, 2026. "Identifying Turning Points in Bank of Russia Business Activity Indicators Using Machine Learning Methods," Russian Journal of Money and Finance, Bank of Russia, vol. 85(2), pages 3-36, June.
    • Handle: RePEc:bkr:journl:v:85:y:2026:i:2:p:3-36
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    Keywords

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    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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