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Eliminating chain drift in price indexes based on scanner data

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  • de Haan, Jan
  • van der Grient, Heymerik A.
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    Abstract

    The use of scanner data in the CPI makes it possible to compile superlative price indexes at detailed aggregation levels since prices and quantities are available. A potential drawback is the high attrition rate of items. The usual solution to handle this problem, high-frequency chaining, can create drift in the index series due to price and quantity bouncing arising from sales. Ivancic, Diewert and Fox (2009) have recently proposed an approach that provides drift free, superlative-type indexes through adapting multilateral index number theory. In this paper we apply their proposal to seven product groups and find promising results. We compare the results with those obtained by using the Dutch method to deal with supermarket scanner data.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 161 (2011)
    Issue (Month): 1 (March)
    Pages: 36-46

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    Handle: RePEc:eee:econom:v:161:y:2011:i:1:p:36-46

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    Web page: http://www.elsevier.com/locate/jeconom

    Related research

    Keywords: Consumer price index (CPI) Chain drift Multilateral index number methods Scanner data Superlative indexes;

    References

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    1. Balk, B.M., 2001. "Aggregation Methods in International Comparisons," ERIM Report Series Research in Management ERS-2001-41-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
    2. W. E. Diewert & Mick Silver & Saeed Heravi, 2007. "Hedonic Imputation Versus Time Dummy Hedonic Indexes," IMF Working Papers 07/234, International Monetary Fund.
    3. W. Erwin Diewert, 1995. "Axiomatic and Economic Approaches to Elementary Price Indexes," NBER Working Papers 5104, National Bureau of Economic Research, Inc.
    4. Robert C. Feenstra & Matthew D. Shapiro, 2001. "High-Frequency Substitution and the Measurement of Price Indexes," NBER Working Papers 8176, National Bureau of Economic Research, Inc.
    5. Silver, Mick & Heravi, Saeed, 2002. "A failure in the measurement of inflation: results from a hedonic and matched experiment using scanner data," Working Paper Series 0144, European Central Bank.
    6. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
    7. Hill, Robert J., 2006. "Superlative index numbers: not all of them are super," Journal of Econometrics, Elsevier, vol. 130(1), pages 25-43, January.
    8. Diewert, W. Erwin, 1999. "Index Number Approaches To Seasonal Adjustment," Macroeconomic Dynamics, Cambridge University Press, vol. 3(01), pages 48-68, March.
    9. Jack E. Triplett, 2003. "Using Scanner Data in Consumer Price Indexes. Some Neglected Conceptual Considerations," NBER Chapters, in: Scanner Data and Price Indexes, pages 151-162 National Bureau of Economic Research, Inc.
    10. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
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    Cited by:
    1. Marcelo Delajara & José Antonio Murillo Garza, 2012. "Weekday with Low Prices: Evidence on Daily Seasonality of Foods, Beverages, and Tobacco Prices," Working Papers 2012-09, Banco de México.
    2. Kota Watanabe & Tsutomu Watanabe, 2014. "We construct a Törnqvist daily price index using Japanese point of sale (POS) scannerdata spanning from 1988 to 2013. We find the following. First, the POS based inflation rate tends to be about 0.," CARF F-Series CARF-F-342, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. Kevin J. Fox & Iqbal A. Syed, 2014. "Price Discounts and the Measurement of Inflation," Discussion Papers 2014-05, School of Economics, The University of New South Wales.
    4. Castellari, E. & Moro, D. & Platoni, S. & Sckokai, P., 2013. "Measuring the impact of retailers’ strategies on food price inflation using scanner data," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150258, Agricultural and Applied Economics Association.
    5. , & Diewert, Erwin, 2014. "An Empirical Illustration of Index Construction using Israeli Data on Vegetables," Economics working papers erwin_diewert-2014-11, Vancouver School of Economics, revised 11 Mar 2014.

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