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Trimmed-Mean Inflation Statistics: Just Hit the One in the Middle

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  • Brent Meyer
  • Guhan Venkatu

Abstract

This paper reinvestigates the performance of trimmed-mean inflation measures some 20 years since their inception, asking whether there is a particular trimmed-mean measure that dominates the median consumer price index (CPI). Unlike previous research, we evaluate the performance of symmetric and asymmetric trimmed means using a well known equality of prediction test. We find that there is a large swath of trimmed means that have statistically indistinguishable performance. Also, although the swath of statistically similar trims changes slightly over different sample periods, it always includes the median CPI - an extreme trim that holds conceptual and computational advantages. We conclude with a simple forecasting exercise that highlights the advantage of the median CPI (and trimmed-mean estimators in general) relative to other standard measures in forecasting headline inflation.

Suggested Citation

  • Brent Meyer & Guhan Venkatu, 2014. "Trimmed-Mean Inflation Statistics: Just Hit the One in the Middle," FRB Atlanta Working Paper 2014-3, Federal Reserve Bank of Atlanta.
  • Handle: RePEc:fip:fedawp:2014-03
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    5. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
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    11. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    12. Brent Meyer & Mehmet Pasaogullari, 2010. "Simple ways to forecast inflation: what works best?," Economic Commentary, Federal Reserve Bank of Cleveland, issue Dec.
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    Cited by:

    1. Shahzad Ahmad & Farooq Pasha, 2015. "A Pragmatic Model for Monetary Policy Analysis I: The Case of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 1-42.
    2. Jim Dolmas & Evan F. Koenig, 2019. "Two Measures of Core Inflation: A Comparison," Review, Federal Reserve Bank of St. Louis, vol. 101(4).
    3. 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.
    4. Brent Meyer & Saeed Zaman, 2013. "It’s not just for inflation: The usefulness of the median CPI in BVAR forecasting," Working Papers (Old Series) 1303, Federal Reserve Bank of Cleveland.
    5. Brent Meyer & Saeed Zaman, 2019. "The usefulness of the median CPI in Bayesian VARs used for macroeconomic forecasting and policy," Empirical Economics, Springer, vol. 57(2), pages 603-630, August.
    6. Garciga, Christian & Knotek II, Edward S., 2019. "Forecasting GDP growth with NIPA aggregates: In search of core GDP," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1814-1828.
    7. Muhammad Nadim Hanif & Muhammad Jahanzeb Malik, 2015. "Evaluating the Performance of Inflation Forecasting Models of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 43-78.
    8. Amy Higgins & Randal Verbrugge, 2015. "Tracking Trend Inflation: Nonseasonally Adjusted Variants of the Median and Trimmed-Mean CPI," Working Papers (Old Series) 1527, Federal Reserve Bank of Cleveland.
    9. Yiqun Gloria Chen, 2019. "Inflation, Inflation Expectations, and the Phillips Curve: Working Paper 2019-07," Working Papers 55501, Congressional Budget Office.
    10. Iris Day, 2017. "Underlying Consumer Price Inflation in China," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 29-36, December.

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    More about this item

    Keywords

    inflation; inflation forecasting; trimmed-mean estimators;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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