Trimmed-Mean Inflation Statistics: Just Hit the One in the Middle
Brent Meyer and Guhan Venkatu
Working Paper 2014-3
Download the full text of this paper (343 KB)
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.
JEL classification: E31, E37
Key words: inflation, inflation forecasting, trimmed-mean estimators
The authors thank Julio Blanco, Todd Clark, Alan Detmeister, and Tim Dunne for their helpful comments, criticisms, and guidance. This paper is a revised version of an earlier Federal Reserve Bank of Cleveland working paper (WP12-17) first posted in September 2012. The views expressed here are the authors' and not necessarily those of the Federal Reserve Banks of Cleveland or Atlanta or the Federal Reserve System. Any remaining errors are the authors' responsibility.
Please address questions regarding content to Brent Meyer, Research Department, Federal Reserve Bank of Atlanta, 1000 Peachtree Street, N.E., Atlanta, GA 30309-4470, 404-498-8852, firstname.lastname@example.org; or Guhan Venkatu, Research Department, Federal Reserve Bank of Cleveland, P.O. Box 6387, Cleveland, OH 44101-1387, email@example.com.
Use the WebScriber Service to receive e-mail e-mail notifications about new papers.