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Core and `Crust': Consumer Prices and the Term Structure of Interest Rates

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  • Olena Chyruk

    (Federal Reserve Bank of Chicago)

  • Luca Benzoni

    (Federal Reserve Bank of Chicago)

  • Andrea Ajello

    (Board of Governors of the Federal Reserve System)

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    Abstract

    We estimate a model for nominal and real term structures of interest rates that includes dynamics for the three main components of total inflation: core, food, and energy. These dynamics combine together to produce a measure of expected total inflation that investors use to price nominal Treasuries. This framework captures different frequencies in inflation fluctuations: shocks to core are more persistent and less volatile than shocks to food and, especially, energy (the `crust'). The model fits yields and inflation data well in sample, and produces inflation forecasts that outperform several benchmarks out of sample. A common structure of latent factors explains most of the variance of the forecasting error for core inflation and bond yields. This evidence suggests that interest rates contain useful predictive content for inflation. Moreover, we estimate real interest rates, as well as inflation and real rate risk premia, that are consistent with related market-based measures.

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    File URL: http://www.economicdynamics.org/meetpapers/2012/paper_922.pdf
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    Bibliographic Info

    Paper provided by Society for Economic Dynamics in its series 2012 Meeting Papers with number 922.

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    Date of creation: 2012
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    Handle: RePEc:red:sed012:922

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    1. Philippe Mueller & Mikhail Chernov, 2008. "The Term Structure of Inflation Expectations," 2008 Meeting Papers 346, Society for Economic Dynamics.
    2. Charles L. Evans & David Marshall, 2001. "Economic determinants of the nominal treasury yield curve," Working Paper Series WP-01-16, Federal Reserve Bank of Chicago.
    3. Andrew Ang & Monika Piazzesi, 2001. "A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables," NBER Working Papers 8363, National Bureau of Economic Research, Inc.
    4. Andrew Ang & Monika Piazzesi & Min Wei, 2004. "What Does the Yield Curve Tell us about GDP Growth?," NBER Working Papers 10672, National Bureau of Economic Research, Inc.
    5. Pennacchi, George G, 1991. "Identifying the Dynamics of Real Interest Rates and Inflation: Evidence Using Survey Data," Review of Financial Studies, Society for Financial Studies, vol. 4(1), pages 53-86.
    6. Greg Duffee, 2005. "Term structure estimation without using latent factors," Computing in Economics and Finance 2005 103, Society for Computational Economics.
    7. Albert Lee Chun, 2005. "Expectations, Bond Yields and Monetary Policy," Discussion Papers 04-023, Stanford Institute for Economic Policy Research, revised Nov 2010.
    8. West, K.D., 1994. "Asymptotic Inference About Predictive Ability," Working papers 9417, Wisconsin Madison - Social Systems.
    9. Mönch, Emanuel, 2005. "Forecasting the yield curve in a data-rich environment: a no-arbitrage factor-augmented VAR approach," Working Paper Series 0544, European Central Bank.
    10. Monika Piazzesi, 2005. "Bond Yields and the Federal Reserve," Journal of Political Economy, University of Chicago Press, vol. 113(2), pages 311-344, April.
    11. John H. Boyd & Ravi Jagannathan & Jian Hu, 2001. "The Stock Market's Reaction to Unemployment News: Why Bad News is Usually Good for Stocks," NBER Working Papers 8092, National Bureau of Economic Research, Inc.
    12. Souleles, Nicholas S, 2004. "Expectations, Heterogeneous Forecast Errors, and Consumption: Micro Evidence from the Michigan Consumer Sentiment Surveys," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(1), pages 39-72, February.
    13. Francis X. Diebold & Glenn D. Rudebusch & S. Boragan Aruoba, 2004. "The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach," NBER Working Papers 10616, National Bureau of Economic Research, Inc.
    14. McCracken, Michael W., 2004. "Parameter estimation and tests of equal forecast accuracy between non-nested models," International Journal of Forecasting, Elsevier, vol. 20(3), pages 503-514.
    15. Estrella, Arturo & Mishkin, Frederic S., 1997. "The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank," European Economic Review, Elsevier, vol. 41(7), pages 1375-1401, July.
    16. Refet S. Gürkaynak & Brian Sack & Jonathan H. Wright, 2008. "The TIPS yield curve and inflation compensation," Finance and Economics Discussion Series 2008-05, Board of Governors of the Federal Reserve System (U.S.).
    17. Adrian, Tobias & Crump, Richard K. & Moench, Emanuel, 2013. "Pricing the term structure with linear regressions," Journal of Financial Economics, Elsevier, vol. 110(1), pages 110-138.
    18. James D. Hamilton & Jing Cynthia Wu, 2012. "Identification and Estimation of Gaussian Affine Term Structure Models," NBER Working Papers 17772, National Bureau of Economic Research, Inc.
    19. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
    20. Lloyd B. Thomas, 1999. "Survey Measures of Expected U.S. Inflation," Journal of Economic Perspectives, American Economic Association, vol. 13(4), pages 125-144, Fall.
    21. Olesya V. Grishchenko & Jing-zhi Huang, 2012. "Inflation risk premium: evidence from the TIPS market," Finance and Economics Discussion Series 2012-06, Board of Governors of the Federal Reserve System (U.S.).
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