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Scanner Data and the Treatment of Quality Change in Nonrevisable Price Indexes

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  • Jan de Haan
  • Frances Krsinich

Abstract

The recently developed rolling year GEKS procedure makes maximum use of all matches in the data to construct nonrevisable price indexes that are approximately free from chain drift. A potential weakness is that unmatched items are ignored. In this article we use imputation Törnqvist price indexes as inputs into the rolling year GEKS procedure. These indexes account for quality changes by imputing the "missing prices" associated with new and disappearing items. Three imputation methods are discussed. The first method makes explicit imputations using a hedonic regression model which is estimated for each time period. The other two methods make implicit imputations; they are based on time dummy hedonic and time-product dummy regression models and are estimated on bilateral pooled data. We present empirical evidence for New Zealand from scanner data on eight consumer electronics products and find that accounting for quality change can make a substantial difference.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:jnlbes:v:32:y:2014:i:3:p:341-358
    DOI: 10.1080/07350015.2014.880059
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    References listed on IDEAS

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    1. Ivancic, Lorraine & Erwin Diewert, W. & Fox, Kevin J., 2011. "Scanner data, time aggregation and the construction of price indexes," Journal of Econometrics, Elsevier, vol. 161(1), pages 24-35, March.
    2. Diewert, Erwin, 2013. "The Consumer Price Index: Recent Developments," Economics working papers erwin_diewert-2013-45, Vancouver School of Economics, revised 24 Oct 2013.
    3. Iqbal Syed, 2010. "Consistency of Hedonic Price Indexes with Unobserved Characteristics," Discussion Papers 2010-03, School of Economics, The University of New South Wales.
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