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Life Cycle Price Trends and Product Replacement: Implications for the Measurement of Inflation

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  • Daniel Melser

    () (Moody's Analytics)

  • Iqbal A. Syed

    () (School of Economics, Australian School of Business, the University of New South Wales)

Abstract

The paper explores the extent to which products follow systematic pricing patterns over their life cycle and the impact this has on the measurement of inflation. Using a large US scanner data set on supermarket products and applying flexible regression methods, we find that on average prices decline as items age. This life cycle price change is often attributed to quality difference in the construction of CPI as items are replaced due to disappearance or during sample rotations. This introduces a systematic bias in the measurement of inflation. For our data we find that the life cycle bias leads to the underestimation of inflation by around 0.30 percentage points each year for the products examined.

Suggested Citation

  • Daniel Melser & Iqbal A. Syed, 2014. "Life Cycle Price Trends and Product Replacement: Implications for the Measurement of Inflation," Discussion Papers 2014-40, School of Economics, The University of New South Wales.
  • Handle: RePEc:swe:wpaper:2014-40
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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2014-40.pdf
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    References listed on IDEAS

    as
    1. Mark Bils, 2009. "Do Higher Prices for New Goods Reflect Quality Growth or Inflation?," The Quarterly Journal of Economics, Oxford University Press, vol. 124(2), pages 637-675.
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    3. Robert J. Hill & Daniel Melser, 2008. "Hedonic Imputation And The Price Index Problem: An Application To Housing," Economic Inquiry, Western Economic Association International, vol. 46(4), pages 593-609, October.
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    7. Mark Bils & Peter J. Klenow & Benjamin A. Malin, 2012. "Reset Price Inflation and the Impact of Monetary Policy Shocks," American Economic Review, American Economic Association, vol. 102(6), pages 2798-2825, October.
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    12. D.S. Prasada Rao, 2004. "The Country-Product-Dummy Method: A Stochastic Approach to the Computation of Purchasing Power Parities in the ICP," CEPA Working Papers Series WP032004, School of Economics, University of Queensland, Australia.
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    Cited by:

    1. Adam, Klaus & Weber, Henning, 2017. "Optimal trend inflation," Discussion Papers 25/2017, Deutsche Bundesbank.
    2. Nobuhiro Abe & Yojiro Ito & Ko Munakata & Shinsuke Ohyama & Kimiaki Shinozaki, 2016. "Pricing Patterns over Product Life-Cycle and Quality Growth at Product Turnover: Empirical Evidence from Japan," Bank of Japan Working Paper Series 16-E-5, Bank of Japan.
    3. Jan de Haan & Rens Hendriks & Michael Scholz, 2016. "A Comparison of Weighted Time-Product Dummy and Time Dummy Hedonic Indexes," Graz Economics Papers 2016-13, University of Graz, Department of Economics.
    4. Daniel Melser & Iqbal A. Syed, 2017. "The product life cycle and sample representativity bias in price indexes," Applied Economics, Taylor & Francis Journals, vol. 49(6), pages 573-586, February.
    5. Kozo Ueda & Kota Watanabe & Tsutomu Watanabe, 2016. "Product Turnover and Deflation: Evidence from Japan," CARF F-Series CARF-F-400, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

    More about this item

    Keywords

    Consumer price index (CPI); matched-model index; price skimming strategy; quality change bias; sample rotation;

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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