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Evaluating underlying inflation measures for Russia

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  • Elena Deryugina
  • Alexey Ponomarenko
  • Andrey Sinyakov
  • Constantine Sorokin

Abstract

We apply several tests to the underlying inflation measures used in practice by central banks and/or proposed in the academic literature in an attempt to find the best-performing indicators. We find that although there is no single best measure of underlying inflation, indicators calculated on the basis of dynamic factor models are generally among the best performers. These best performers not only outdid the simpler traditional underlying indicators (trimmed and exclusion-based measures) but also proved to be economically meaningful and interpretable.

Suggested Citation

  • Elena Deryugina & Alexey Ponomarenko & Andrey Sinyakov & Constantine Sorokin, 2018. "Evaluating underlying inflation measures for Russia," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 11(2), pages 124-145, May.
    • Handle: RePEc:taf:macfem:v:11:y:2018:i:2:p:124-145
    DOI: 10.1080/17520843.2017.1301511
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    1. Brent Meyer & Guhan Venkatu, 2012. "Trimmed-mean inflation statistics: just hit the one in the middle," Working Papers (Old Series) 1217, Federal Reserve Bank of Cleveland.
    2. Scott Davis, 2012. "The Effect of Commodity Price Shocks on Underlying Inflation: The Role of Central Bank Credibility," Working Papers 272012, Hong Kong Institute for Monetary Research.
    3. Svensson, Lars E. O., 1997. "Inflation forecast targeting: Implementing and monitoring inflation targets," European Economic Review, Elsevier, vol. 41(6), pages 1111-1146, June.
    4. Nicoletti Altimari, Sergio, 2001. "Does money lead inflation in the euro area?," Working Paper Series 63, European Central Bank.
    5. Andrew Blake & Haroon Mumtaz, 2015. "Applied Bayesian Econometrics for central bankers," Handbooks, Centre for Central Banking Studies, Bank of England, number 36, April.
    6. Mick Silver, 2006. "Core Inflation Measures and Statistical Issues in Choosing Among Them," IMF Working Papers 2006/097, International Monetary Fund.
    7. Marlene Amstad & Simon M. Potter & Robert W. Rich, 2017. "The New York Fed Staff Underlying Inflation Gauge (UIG)," Economic Policy Review, Federal Reserve Bank of New York, issue 23-2, pages 1-32.
    8. Elena Deryugina & Alexey Ponomarenko, 2013. "Money-based inflation risk indicator for Russia: a structural dynamic factor model approach," Joint Research Papers 3, Centre for Central Banking Studies, Bank of England.
    9. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2009. "Opening The Black Box: Structural Factor Models With Large Cross Sections," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1319-1347, October.
    10. Martin Fukac, 2011. "Have rising oil prices become a greater threat to price stability?," Economic Review, Federal Reserve Bank of Kansas City, vol. 96(Q IV), pages 27-53.
    11. Nessen, Marianne & Soderstrom, Ulf, 2001. "Core Inflation and Monetary Policy," International Finance, Wiley Blackwell, vol. 4(3), pages 401-439, Winter.
    12. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    13. Ricardo Reis & Mark W. Watson, 2010. "Relative Goods' Prices, Pure Inflation, and the Phillips Correlation," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(3), pages 128-157, July.
    14. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    15. David Gruen & John Romalis & Naveen Chandra, 1999. "The Lags of Monetary Policy," The Economic Record, The Economic Society of Australia, vol. 75(3), pages 280-294, September.
    16. Duguay, Pierre, 1994. "Empirical evidence on the strength of the monetary transmission mechanism in Canada: An aggregate approach," Journal of Monetary Economics, Elsevier, vol. 33(1), pages 39-61, February.
    17. Mikael Khan & Louis Morel & Patrick Sabourin, 2013. "The Common Component of CPI: An Alternative Measure of Underlying Inflation for Canada," Staff Working Papers 13-35, Bank of Canada.
    18. Marlene Amstad & Simon M. Potter & Robert W. Rich, 2014. "The FRBNY staff underlying inflation gauge: UIG," Staff Reports 672, Federal Reserve Bank of New York.
    19. Michal Andrle & Jan Bruha & Serhat Solmaz, 2013. "Inflation and Output Comovement in the Euro Area: Love at Second Sight?," Working Papers 2013/07, Czech National Bank.
    20. Domenico Giannone & Troy D. Matheson, 2007. "A New Core Inflation Indicator for New Zealand," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 145-180, December.
    21. Forni, Mario & Gambetti, Luca, 2010. "The dynamic effects of monetary policy: A structural factor model approach," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 203-216, March.
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    Cited by:

    1. Elena Deryugina & Alexey Ponomarenko, 2020. "Disinflation and Reliability of Underlying Inflation Measures," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(1), pages 91-111, March.
    2. Elena Deryugina & Natalia Karlova & Alexey Ponomarenko & Anna Tsvetkova, 2019. "The role of regional and sectoral factors in Russian inflation developments," Economic Change and Restructuring, Springer, vol. 52(4), pages 453-474, November.
    3. Vadim Napalkov & Anna Novak & Andrey Shulgin, 2021. "Variations in the Effects of a Single Monetary Policy: The Case of Russian Regions," Russian Journal of Money and Finance, Bank of Russia, vol. 80(1), pages 3-45, March.
    4. Alexey Ponomarenko, 2016. "Measuring Domestically Generated Inflation," Bank of Russia Working Paper Series note2, Bank of Russia.

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    More about this item

    JEL classification:

    • 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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • 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

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