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

Author

Listed:
  • 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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    References listed on IDEAS

    as
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    5. Theodore M. Crone & N. Neil K. Khettry & Loretta J. Mester & Jason A. Novak, 2013. "Core Measures of Inflation as Predictors of Total Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(2‐3), pages 505-519, March.
    6. Jim Dolmas, 2005. "Trimmed mean PCE inflation," Working Papers 0506, Federal Reserve Bank of Dallas.
    7. Andrea Brischetto & Anthony Richards, 2006. "The Performance of Trimmed Mean Measures of Underlying Inflation," RBA Research Discussion Papers rdp2006-10, Reserve Bank of Australia.
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    9. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    10. Cogley, Timothy, 2002. "A Simple Adaptive Measure of Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 94-113, February.
    11. Michael F. Bryan & Christopher J. Pike, 1991. "Median price changes: an alternative approach to measuring current monetary inflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Dec.
    12. repec:mcb:jmoncb:v:45:y:2013:i::p:505-519 is not listed on IDEAS
    13. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-966, July.
    14. Michael F. Bryan & Stephen G. Cecchetti & Rodney L. Wiggins II, 1997. "Efficient Inflation Estimation," NBER Working Papers 6183, National Bureau of Economic Research, Inc.
    15. Brent Meyer & Mehmet Pasaogullari, 2010. "Simple ways to forecast inflation: what works best?," Economic Commentary, Federal Reserve Bank of Cleveland, issue Dec.
    16. Smith, Julie K, 2004. "Weighted Median Inflation: Is This Core Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(2), pages 253-263, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Amy Higgins & Randal J. 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.
    2. 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.
    3. 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.
    4. Jim Dolmas & Evan F. Koenig, 2019. "Two Measures of Core Inflation: A Comparison," Review, Federal Reserve Bank of St. Louis, vol. 101(4).
    5. 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.
    6. 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.
    7. 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.
    8. John O’Trakoun, 2023. "An alternative measure of core inflation: the Trimmed Persistence PCE price index," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 58(4), pages 205-223, October.
    9. Yiqun Gloria Chen, 2019. "Inflation, Inflation Expectations, and the Phillips Curve: Working Paper 2019-07," Working Papers 55501, Congressional Budget Office.
    10. 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.
    11. Verbrugge, Randal & Zaman, Saeed, 2024. "Improving inflation forecasts using robust measures," International Journal of Forecasting, Elsevier, vol. 40(2), pages 735-745.
    12. 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.
    13. Iris Day, 2017. "Underlying Consumer Price Inflation in China," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 29-36, December.
    14. Randal J. Verbrugge, 2021. "Is It Time to Reassess the Focal Role of Core PCE Inflation?," Working Papers 21-10, Federal Reserve Bank of Cleveland.

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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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