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The Seasonality of Consumer Prices

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  • Michael F. Bryan
  • Stephen G. Cecchetti

Abstract

In this paper, we reevaluate the evidence of seasonality in prices which we find to be substantially greater than previous research has indicated. That is, seasonal price movements have become more prominent in the relatively stable inflation environment that has prevailed since 1982. One main conclusion is drawn from this analysis: The amount of seasonality in prices differs greatly by item, making it difficult to generalize about seasonal price movements. A casual reading fails to reveal an easily identifiable origin of the seasonal variation of prices. That is, seasonality in consumer prices is predominantly idiosyncratic in nature, a result that contrasts with studies demonstrating a common seasonal cycle in real economic variables. This finding has an important practical implication: Given the selective, disaggregated approach taken by the Bureau of Labor Statistics to adjust data seasonally, the existence of idiosyncratic seasonality increases the likelihood of allowing noise in the aggregate CPI at a seasonal frequency. This argues in favor of seasonally adjusting the index after aggregation.

Suggested Citation

  • Michael F. Bryan & Stephen G. Cecchetti, 1995. "The Seasonality of Consumer Prices," NBER Working Papers 5173, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:5173
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    References listed on IDEAS

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    1. Beaulieu, J. Joseph & Miron, Jeffrey A., 1991. "The seasonal cycle in U.S. manufacturing," Economics Letters, Elsevier, vol. 37(2), pages 115-118, October.
    2. Mankiw, N. Gregory & Miron, Jeffrey A., 1991. "Should the fed smooth interest rates? the case of seasonal monetary policy," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 34(1), pages 41-69, January.
    3. Jeffrey A. Miron, 1996. "The Economics of Seasonal Cycles," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262133237, December.
    4. Beaulieu, J Joseph & Miron, Jeffrey A, 1992. "A Cross Country Comparison of Seasonal Cycles and Business Cycles," Economic Journal, Royal Economic Society, vol. 102(413), pages 772-788, July.
    5. Michael F. Bryan & Stephen G. Cecchetti, 1994. "Measuring Core Inflation," NBER Chapters, in: Monetary Policy, pages 195-219, National Bureau of Economic Research, Inc.
    6. Barsky, Robert B & Miron, Jeffrey A, 1989. "The Seasonal Cycle and the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 503-534, June.
    7. Stephen G. Cecchetti & Anil K. Kashyap & David W. Wilcox, 1995. "Do Firms Smooth the Seasonal in Production in a Boom? Theory and Evidence," NBER Working Papers 5011, National Bureau of Economic Research, Inc.
    8. Andrew R. Biehl & John P. Judd, 1993. "Inflation, interest rates, and seasonality," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue oct15.
    9. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    10. Stephen G. Cecchetti & Anil Kashyap & David Wilcox, 1995. "Why Firms Smooth Seasonals in a Boom," Working Papers 001, Ohio State University, Department of Economics.
    11. repec:fth:harver:1531 is not listed on IDEAS
    12. N. Gregory Mankiw, 1994. "Monetary Policy," NBER Books, National Bureau of Economic Research, Inc, number greg94-1, March.
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    Cited by:

    1. Tsyplakov Alexander, 2004. "Constructing Core Inflation Index for Russia," EERC Working Paper Series 04-04e, EERC Research Network, Russia and CIS.
    2. Malmendier, Ulrike & Nagel, Stefan & Yan, Zhen, 2021. "The making of hawks and doves," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 19-42.
    3. Pierzak, Agnieszka, 2010. "Identyfikacja i usuwanie sezonowości ze wskaźników cen towarów i usług konsumpcyjnych w Polsce," MF Working Papers 6, Ministry of Finance in Poland, revised 25 Aug 2010.

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    More about this item

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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