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Seasonality, consumer heterogeneity and price indexes: the case of prepackaged software

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Abstract

This paper measures constant-quality price change for prepackaged software in the US using detailed and comprehensive scanner data. Because there is a large sales surge over the winter-holiday, it is important to account for seasonal variation. Using a novel approach to constructing a seasonally-adjusted cost-of-living price index that explicitly accounts for consumer heterogeneity, I find that from 1997 to 2003 constant-quality software prices declined at an average 15.9% at an annual rate. As a point of comparison, the Bureau of Labor Statistics reports average annual price declines of only 7.7% for prepackaged software. Copyright Springer Science+Business Media, LLC 2013

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  • Adam Copeland, 2013. "Seasonality, consumer heterogeneity and price indexes: the case of prepackaged software," Journal of Productivity Analysis, Springer, vol. 39(1), pages 47-59, February.
  • Handle: RePEc:kap:jproda:v:39:y:2013:i:1:p:47-59
    DOI: 10.1007/s11123-012-0266-2
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    References listed on IDEAS

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    1. Franklin M. Fisher & Zvi Griliches, 1995. "Aggregate Price Indices, New Goods, and Generics," The Quarterly Journal of Economics, Oxford University Press, vol. 110(1), pages 229-244.
    2. Mark Bils, 1989. "Pricing in a Customer Market," The Quarterly Journal of Economics, Oxford University Press, vol. 104(4), pages 699-718.
    3. Aizcorbe, Ana & Bridgman, Benjamin & Nalewaik, Jeremy, 2010. "Heterogeneous car buyers: A stylized fact," Economics Letters, Elsevier, vol. 109(1), pages 50-53, October.
    4. Marc Prud'homme & Dimitri Sanga & Kam Yu, 2005. "A computer software price index using scanner data," Canadian Journal of Economics, Canadian Economics Association, vol. 38(3), pages 999-1017, August.
    5. Robert C. Feenstra & Matthew D. Shapiro, 2003. "Introduction to "Scanner Data and Price Indexes"," NBER Chapters,in: Scanner Data and Price Indexes, pages 1-14 National Bureau of Economic Research, Inc.
    6. Robert C. Feenstra & Matthew D. Shapiro, 2003. "Scanner Data and Price Indexes," NBER Books, National Bureau of Economic Research, Inc, number feen03-1, January.
    7. Diewert, W. Erwin, 1999. "Index Number Approaches To Seasonal Adjustment," Macroeconomic Dynamics, Cambridge University Press, vol. 3(01), pages 48-68, March.
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    Cited by:

    1. David M. Byrne & John G. Fernald & Marshall B. Reinsdorf, 2016. "Does the United States Have a Productivity Slowdown or a Measurement Problem?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(1 (Spring), pages 109-182.
    2. Daniel Melser & Iqbal A. Syed, 2013. "Prices over the Product Life Cycle: Implications for Quality-Adjustment and the Measurement of Inflation," Discussion Papers 2013-26, School of Economics, The University of New South Wales.
    3. repec:aei:rpaper:37301 is not listed on IDEAS
    4. David M. Byrne & Stephen D. Oliner & Daniel E. Sichel, 2013. "Is the Information Technology Revolution Over?," International Productivity Monitor, Centre for the Study of Living Standards, vol. 25, pages 20-36, Spring.

    More about this item

    Keywords

    Seasonal adjustment; Software prices; Heterogeneity; Price indexes; C43; E31; L86;

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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