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Do unobserved components models forecast inflation in Russia?

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  • Bulat Gafarov

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

Abstract

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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    File URL: http://www.hse.ru/data/2013/09/30/1277205682/35EC2013.pdf
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    Keywords

    Stochastic volatility; MCMC; Russia; CPI; forecasting.;
    All these keywords.

    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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