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Do unobserved components models forecast inflation in Russia?


  • Bulat Gafarov

    () (Higher School of Economics (Moscow, Russia). Laboratory for Inflation Problems and Economic Growth Research.)


I apply the model with unobserved components and stochastic volatility (UC-SV) to forecast the Russian consumer price index. I extend the model which was previously suggested as a model for inflation forecasting in the USA to take into account a possible difference in model parameters and seasonal factor. Comparison of the out-of-sample forecasting performance of the linear AR model and the UC-SV model by mean squared error of prediction shows better results for the latter model. Relatively small absolute value of the standard error of the forecasts calculated by the UC-SV model makes it a reasonable candidate for a real time forecasting method for the Russian CPI.

Suggested Citation

  • Bulat Gafarov, 2013. "Do unobserved components models forecast inflation in Russia?," HSE Working papers WP BRP 35/EC/2013, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:35/ec/2013

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    References listed on IDEAS

    1. Jan Bartholdy & Dennis Olson & Paula Peare, 2007. "Conducting Event Studies on a Small Stock Exchange," The European Journal of Finance, Taylor & Francis Journals, vol. 13(3), pages 227-252.
    2. Eckbo, B. Espen, 1983. "Horizontal mergers, collusion, and stockholder wealth," Journal of Financial Economics, Elsevier, vol. 11(1-4), pages 241-273, April.
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    More about this item


    Stochastic volatility; MCMC; Russia; CPI; forecasting.;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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