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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.)

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    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.

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

    Paper provided by National Research University Higher School of Economics in its series HSE Working papers with number WP BRP 35/EC/2013.

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    Length: 14 pages
    Date of creation: 2013
    Date of revision:
    Publication status: Published in WP BRP Series: Economics / EC, September 2013, pages 1-14
    Handle: RePEc:hig:wpaper:35/ec/2013

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    Related research

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

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