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Application of MF-PVAR Model for Nowcasting Gross Regional Products in Russia

Author

Listed:
  • Anastasia Pankratova

    (European University at St. Petersburg)

Abstract

The significant lags in Rosstat's publication of estimates of annual gross regional product (GRP) severely constrain the timely analysis of economic dynamics across the regions of Russia, heightening the demand for nowcasting techniques. This study uses a mixed-frequency panel vector autoregression (MF-PVAR) model for GRP nowcasting that integrates heterogeneous data and accounts for spatial heterogeneity and cross-sectional dependence among the regions. The sample used is a balanced panel of 68 Russian regions covering 2010-2022 and includes annual growth rates of real GRP together with monthly growth rates of sectoral indicators. The model is estimated over 2010-2018 and validated on 2019-2022 data. The results show that the precision of the MF-PVAR forecast is higher compared to the naive forecast, Ridge regression, and dynamic panel models based on generalised method of moments.

Suggested Citation

  • Anastasia Pankratova, 2025. "Application of MF-PVAR Model for Nowcasting Gross Regional Products in Russia," Russian Journal of Money and Finance, Bank of Russia, vol. 84(4), pages 47-62, December.
    • Handle: RePEc:bkr:journl:v:84:y:2025:i:4:p:47-62
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    References listed on IDEAS

    as
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    Keywords

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    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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