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Trimmed-mean inflation statistics: just hit the one in the middle

Author Info

Listed author(s):
  • 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 CPI. Unlike previous research, we evaluate the performance of symmetric and asymmetric trimmed-means using a well-known equality of prediction test. We fi nd that there is a large swath of trimmed-means that have statistically indistinguishable performance. Also, while 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 relative to other standard inflation measures.

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Paper provided by Federal Reserve Bank of Cleveland in its series Working Paper with number 1217.

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Date of creation: 2012
Date of revision: 01 Feb 2014
Handle: RePEc:fip:fedcwp:1217
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Keywords: Inflation (Finance) ; Consumer price indexes;

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Find related papers by 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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  1. Michael F. Bryan & Stephen G. Cecchetti & Rodney L. Wiggins, 1997. "Efficient inflation estimation," Working Paper 9707, Federal Reserve Bank of Cleveland.
  2. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
  3. 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.
  4. Brent Meyer & Mehmet Pasaogullari, 2010. "Simple ways to forecast inflation: what works best?," Economic Commentary, Federal Reserve Bank of Cleveland, issue Dec.
  5. 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.
  6. 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.
  7. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, Elsevier.
  8. 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.
  9. 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, 03.
  10. Michael F. Bryan & Stephen G. Cecchetti, 1994. "Measuring Core Inflation," NBER Chapters,in: Monetary Policy, pages 195-219 National Bureau of Economic Research, Inc.
  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. Alan K. Detmeister, 2011. "The usefulness of core PCE inflation measures," Finance and Economics Discussion Series 2011-56, Board of Governors of the Federal Reserve System (U.S.).
  14. James Dolmas, 2005. "Trimmed mean PCE inflation," Working Papers 0506, Federal Reserve Bank of Dallas.
  15. Andrea Brischetto & Anthony Richards, 2006. "The Performance of Trimmed Mean Measures of Underlying Inflation," RBA Research Discussion Papers rdp2006-10, Reserve Bank of Australia.
  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.
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Cited by:

  1. Verbrugge, Randal & Higgins, Amy, 2015. "Tracking Trend Inflation: Nonseasonally Adjusted Variants of the Median and Trimmed-Mean CPI," Working Paper 1527, Federal Reserve Bank of Cleveland.
  2. 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.
  3. Brent Meyer & Saeed Zaman, 2013. "It’s not just for inflation: The usefulness of the median CPI in BVAR forecasting," Working Paper 1303, Federal Reserve Bank of Cleveland.
  4. Meyer, Brent & Zaman, Saeed, 2016. "The Usefulness of the Median CPI in Bayesian VARs Used for Macroeconomic Forecasting and Policy," FRB Atlanta Working Paper 2016-13, Federal Reserve Bank of Atlanta.
  5. Hanif, Muhammad Nadim & Malik, Muhammad Jahanzeb, 2015. "Evaluating Performance of Inflation Forecasting Models of Pakistan," MPRA Paper 66843, University Library of Munich, Germany.

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