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Scanner Data, Product Churn and Quality Adjustment

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  • Chihiro Shimizu
  • Erwin Diewert

Abstract

High technology products are characterized by the rapid introduction of new models and the corresponding disappearance of older models. The paper addresses the problems associated with the construction of price indexes for these products. Several methods for the quality adjustment of product prices are considered: hedonic regressions that use either product characteristics or the product itself (Time Product Dummy regressions). The paper also considers regressions where the economic importance of products is taken into account (weighted versus unweighted regressions). Finally, traditional index numbers are calculated that do not make any special adjustments for quality change. The various approaches are implemented using Japanese price and quantity data on laptop sales in Japan for the 24 months in the years 2020-2021. Somewhat surprisingly, the "best" hedonic regression price index was virtually identical to the "best" traditional index.

Suggested Citation

  • Chihiro Shimizu & Erwin Diewert, 2023. "Scanner Data, Product Churn and Quality Adjustment," Working Papers e185, Tokyo Center for Economic Research.
    • Handle: RePEc:tcr:wpaper:e185
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    References listed on IDEAS

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    1. W. Erwin Diewert & Chihiro Shimizu, 2022. "Residential Property Price Indexes: Spatial Coordinates Versus Neighborhood Dummy Variables," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(3), pages 770-796, September.
    2. Robert J. Hill, 2004. "Constructing Price Indexes across Space and Time: The Case of the European Union," American Economic Review, American Economic Association, vol. 94(5), pages 1379-1410, December.
    3. Allen, Robert C & Diewert, W Erwin, 1981. "Direct versus Implicit Superlative Index Number Formulae," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 430-435, August.
    4. Triplett, Jack E & McDonald, Richard J, 1977. "Assessing the Quality Error in Output Measures: The Case of Refrigerators," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 23(2), pages 137-156, June.
    5. Rao, D.S. Prasada & Hajargasht, Gholamreza, 2016. "Stochastic approach to computation of purchasing power parities in the International Comparison Program (ICP)," Journal of Econometrics, Elsevier, vol. 191(2), pages 414-425.
    6. Aizcorbe, Ana M., 2014. "A Practical Guide to Price Index and Hedonic Techniques," OUP Catalogue, Oxford University Press, number 9780198702429.
    7. W. Erwin Diewert & Kevin J. Fox, 2022. "Substitution Bias in Multilateral Methods for CPI Construction," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 355-369, January.
    8. Robert J. Hill, 1997. "A Taxonomy Of Multilateral Methods For Making International Comparisons Of Prices And Quantities," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 43(1), pages 49-69, March.
    9. Diewert, W. Erwin & Shimizu, Chihiro, 2016. "Hedonic regression models for Tokyo condominium sales," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 300-315.
    10. Diewert, Erwin & Shimizu, Chihiro, 2015. "Residential Property Price Indices For Tokyo," Macroeconomic Dynamics, Cambridge University Press, vol. 19(8), pages 1659-1714, December.
    11. Robert J. Hill, 1999. "Comparing Price Levels across Countries Using Minimum-Spanning Trees," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 135-142, February.
    12. Hill, Robert J, 2001. "Measuring Inflation and Growth Using Spanning Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(1), pages 167-185, February.
    13. Jack E. Triplett & Richard J. McDonald, 1977. "Assessing The Quality Error In Output Measures: The Case Of Refrigerators," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 23(2), pages 137-156, June.
    14. Jan de Haan & Frances Krsinich, 2014. "Scanner Data and the Treatment of Quality Change in Nonrevisable Price Indexes," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 341-358, July.
    15. Muellbauer, John, 1974. "Household Production Theory, Quality, and the "Hedonic Technique."," American Economic Review, American Economic Association, vol. 64(6), pages 977-994, December.
    16. Hill, Robert J. & Timmer, Marcel P., 2006. "Standard Errors as Weights in Multilateral Price Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 366-377, July.
    17. Sergey Sergeev, 2009. "Aggregation Methods Based on Structural International Prices," Chapters, in: D. S.P. Rao (ed.), Purchasing Power Parities of Currencies, chapter 11, pages 274-298, Edward Elgar Publishing.
    18. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
    19. D. S. Prasada Rao & Marcel P. Timmer, 2003. "Purchasing Power Parities for Industry Comparisons Using Weighted Elteto–Koves–Szulc (EKS) Methods," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 49(4), pages 491-511, December.
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