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How Much Do Official Price Indexes Tell Us About Inflation?

Author

Listed:
  • Jessie Handbury

    (University of Pennsylvania)

  • Tsutomu Watanabe

    (The University of Tokyo)

  • David E. Weinstein

    (Columbia University and NBER)

Abstract
Official price indexes, such as the CPI, are imperfect indicators of inflation calculated using ad hoc price formulae different from the theoretically well-founded inflation indexes favored by economists. This paper provides the first estimate of how accurately the CPI informs us about "true" inflation. We use the largest price and quantity dataset ever employed in economics to build a Törnqvist inflation index for Japan between 1989 and 2010. Our comparison of this true inflation index with the CPI indicates that the CPI bias is not constant but depends on the level of inflation. We show the informativeness of the CPI rises with inflation. When measured inflation is low (less than 2.4% per year) the CPI is a poor predictor of true inflation even over 12-month periods. Outside this range, the CPI is a much better measure of inflation. We find that the U.S. PCE Deflator methodology is superior to the Japanese CPI methodology but still exhibits substantial measurement error and biases rendering it a problematic predictor of inflation in low inflation regimes as well.

Suggested Citation

  • Jessie Handbury & Tsutomu Watanabe & David E. Weinstein, 2013. "How Much Do Official Price Indexes Tell Us About Inflation?," CARF F-Series CARF-F-328, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Handle: RePEc:cfi:fseres:cf328
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    References listed on IDEAS

    as
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    Cited by:

    1. Satoshi Imai & Tsutomu Watanabe, 2015. "Replicating Japan's CPI Using Scanner Data," CARF F-Series CARF-F-364, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    2. Elias Bouacida & Daniel Martin, 2021. "Predictive Power in Behavioral Welfare Economics," Journal of the European Economic Association, European Economic Association, vol. 19(3), pages 1556-1591.
    3. Fox, Kevin J. & Levell, Peter & O'Connell, Martin, 2023. "Inflation measurement with high frequency data," CEPR Discussion Papers 18539, C.E.P.R. Discussion Papers.
    4. Richard Davies, 2021. "Prices and inflation in the UK - A new dataset," CEP Occasional Papers 55, Centre for Economic Performance, LSE.
    5. David Argente & Munseob Lee, 2021. "Cost of Living Inequality During the Great Recession," Journal of the European Economic Association, European Economic Association, vol. 19(2), pages 913-952.
    6. Michael D. Bordo & Andrew T. Levin, 2017. "Central Bank Digital Currency and the Future of Monetary Policy," NBER Working Papers 23711, National Bureau of Economic Research, Inc.
    7. repec:hal:wpaper:halshs-01489252 is not listed on IDEAS
    8. Abe, Naohito & Moriguchi, Chiaki & Inakura, Noriko, 2014. "The Impact of the Great East Japan Earthquake on Commodity Prices: New Evidence from High-Frequency Scanner Data," Research Center for Price Dynamics Working Paper Series 12, Research Center for Price Dynamics, Institute of Economic Research, Hitotsubashi University.
    9. Elias Bouacida & Daniel Martin, 2017. "Predictive Power in Behavioral Welfare Economics," PSE Working Papers halshs-01489252, HAL.
    10. Kota Watanabe & Tsutomu Watanabe, 2014. "Estimating Daily Inflation Using Scanner Data: A Progress Report," UTokyo Price Project Working Paper Series 020, University of Tokyo, Graduate School of Economics.
    11. Ambrose, Brent W. & Coulson, N. Edward & Yoshida, Jiro, 2017. "Inflation Rates Are Very Different When Housing Rents Are Accurately Measured," HIT-REFINED Working Paper Series 71, Institute of Economic Research, Hitotsubashi University.
    12. Judith A. Chevalier & Anil K. Kashyap, 2019. "Best Prices: Price Discrimination and Consumer Substitution," American Economic Journal: Economic Policy, American Economic Association, vol. 11(1), pages 126-159, February.
    13. Glandon, PJ, 2018. "Sales and the (Mis)measurement of price level fluctuations," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 60-77.
    14. Satoshi Imai & Tsutomu Watanabe, 2015. "Replicating Japan’s CPI Using Scanner Data," UTokyo Price Project Working Paper Series 054, University of Tokyo, Graduate School of Economics.
    15. Kota Watanabe & Tsutomu Watanabe, 2014. "We construct a Törnqvist daily price index using Japanese point of sale (POS) scannerdata spanning from 1988 to 2013. We find the following. First, the POS based inflation rate tends to be about 0.5 ," CARF F-Series CARF-F-342, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    16. Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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