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The Usefulness of the Median CPI in Bayesian VARs Used for Macroeconomic Forecasting and Policy

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  • Brent Meyer
  • Saeed Zaman

Abstract

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) across our set of monthly and quarterly BVARs. Although 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.

Suggested Citation

  • Brent Meyer & Saeed Zaman, 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.
    • Handle: RePEc:fip:fedawp:2016-13
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    References listed on IDEAS

    as
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    Cited by:

    1. Randal J. Verbrugge & Saeed Zaman, 2021. "Whose Inflation Expectations Best Predict Inflation?," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2021(19), pages 1-7, October.
    2. Daniel R. Carroll & Randal J. Verbrugge, 2019. "Behavior of a New Median PCE Measure: A Tale of Tails," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2019(10), July.
    3. Randal J. Verbrugge & Saeed Zaman, 2022. "Improving Inflation Forecasts Using Robust Measures," Working Papers 22-23R, Federal Reserve Bank of Cleveland, revised 30 May 2023.

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    More about this item

    Keywords

    inflation forecasting; trimmed-mean estimators; Bayesian vector autoregressions; conditional forecasting;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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