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It’s not just for inflation: The usefulness of the median CPI in BVAR forecasting

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  • Brent Meyer
  • Saeed Zaman

Abstract

In this paper we investigate the forecasting performance of the median CPI in a variety of Bayesian VARs (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 “Philips-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—significantly improves the forecasts of both headline and core CPI. across our wide-ranging set of 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.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Cleveland in its series Working Paper with number 1303.

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Date of creation: 2013
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Handle: RePEc:fip:fedcwp:1303

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Keywords: Bayesian statistical decision theory ; Forecasting ; Monetary policy ; Simulation modeling;

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References

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  1. Laurence M. Ball & Sandeep Mazumder, 2011. "Inflation Dynamics and the Great Recession," NBER Working Papers 17044, National Bureau of Economic Research, Inc.
  2. Michael F. Bryan & Stephen G. Cecchetti & Rodney L. Wiggins II, 1997. "Efficient inflation estimation," Working Paper 9707, Federal Reserve Bank of Cleveland.
  3. Michael F. Bryan & Stephen G. Cecchetti, 1994. "Measuring Core Inflation," NBER Chapters, in: Monetary Policy, pages 195-219 National Bureau of Economic Research, Inc.
  4. Todd E. Clark & Michael W. McCracken, 2011. "Tests of equal forecast accuracy for overlapping models," Working Papers 2011-024, Federal Reserve Bank of St. Louis.
  5. Kenneth Beauchemin & Saeed Zaman, 2011. "A medium scale forecasting model for monetary policy," Working Paper 1128, Federal Reserve Bank of Cleveland.
  6. Smith, Julie K, 2004. "Weighted Median Inflation: Is This Core Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(2), pages 253-63, April.
  7. Christopher A. Sims & Tao Zha, 1996. "Bayesian methods for dynamic multivariate models," Working Paper 96-13, Federal Reserve Bank of Atlanta.
  8. 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 254-59, April.
  9. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  10. Jim Dolmas, 2005. "Trimmed mean PCE inflation," Working Papers 0506, Federal Reserve Bank of Dallas.
  11. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
  12. Brent Meyer & Guhan Venkatu, 2012. "Trimmed-mean inflation statistics: just hit the one in the middle," Working Paper 1217, Federal Reserve Bank of Cleveland.
  13. David Norman & Anthony Richards, 2012. "The Forecasting Performance of Single Equation Models of Inflation," The Economic Record, The Economic Society of Australia, vol. 88(280), pages 64-78, 03.
  14. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
  15. Kadiyala, K. Rao & Karlsson, Sune, 1994. "Numerical Aspects of Bayesian VAR-modeling," Working Paper Series in Economics and Finance 12, Stockholm School of Economics.
  16. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2011. "Bayesian VARs: Specification Choices and Forecast Accuracy," CEPR Discussion Papers 8273, C.E.P.R. Discussion Papers.
  17. Brent Meyer & Mehmet Pasaogullari, 2010. "Simple ways to forecast inflation: what works best?," Economic Commentary, Federal Reserve Bank of Cleveland, issue Dec.
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