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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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