Empirical Economics

, Volume 57, Issue 2, pp 603–630 | Cite as

The usefulness of the median CPI in Bayesian VARs used for macroeconomic forecasting and policy

  • Brent Meyer
  • Saeed ZamanEmail author


In this paper, we investigate the forecasting performance of the median Consumer Price Index (CPI) in a variety of Bayesian Vector Autoregressions (BVARs) that are often used for monetary policy. Until now, the use of trimmed-mean price statistics in forecasting inflation has often been relegated to simple univariate or “Phillips-Curve” approaches, thus limiting their usefulness in applications that require consistent forecasts of multiple macro-variables. We find that inclusion of an extreme trimmed-mean measure—the median CPI—improves the forecasts of both core and headline inflation (CPI and personal consumption expenditures price index) across our set of monthly and quarterly BVARs. While the inflation forecasting improvements are perhaps not surprising given the current literature on core inflation statistics, we also find that inclusion of the median CPI improves the forecasting accuracy of the central bank’s primary instrument for monetary policy—the federal funds rate. We conclude with a few illustrative exercises that highlight the usefulness of using the median CPI.


Inflation forecasting Trimmed-mean estimators Bayesian Vector Autoregression Conditional forecasting 

JEL classifications

C11 E31 E37 E52 

Supplementary material

181_2018_1472_MOESM1_ESM.docx (98 kb)
Supplementary material 1 (DOCX 97 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Research DepartmentFederal Reserve Bank of Atlanta (Policy Advisor and Economist)AtlantaUSA
  2. 2.Economics DepartmentEmory UniversityAtlantaUSA
  3. 3.Federal Reserve Bank of Cleveland (Economist)ClevelandUSA
  4. 4.Economics DepartmentUniversity of StrathclydeGlasgowUK

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