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What measures of real economic activity slack are helpful for forecasting Russian inflation?

Author

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  • Ramis Khabibullin

    (Bank of Russia, Russian Federation)

Abstract

This paper investigates inflation forecasting accuracy of several real activity slack measures for the Russian economy. Several Bayesian unobservable-components models using several real activity variables were considered. I show that real-activity slacks gain no improvement in Russian inflation forecasting. This is true for the monthly and for the quarterly data. The estimation was made in the period from the beginning of 2003 to the end of 2018 for monthly data and from the beginning of 1999 to the end of 2018 for the quarterly data. Moreover, their real-times estimates are unreliable in the sense of the magnitude of their revisions.

Suggested Citation

  • Ramis Khabibullin, 2019. "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series wps50, Bank of Russia.
  • Handle: RePEc:bkr:wpaper:wps50
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    References listed on IDEAS

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    More about this item

    Keywords

    Phillips curve; factor model; unobserved components model; output gap; real activity slack; Bayesian estimation;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • 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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