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Eliminating chain drift in price indexes based on scanner data

Author

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

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.

Suggested Citation

  • de Haan, Jan & van der Grient, Heymerik A., 2011. "Eliminating chain drift in price indexes based on scanner data," Journal of Econometrics, Elsevier, vol. 161(1), pages 36-46, March.
  • Handle: RePEc:eee:econom:v:161:y:2011:i:1:p:36-46
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    References listed on IDEAS

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    1. Silver, Mick & Heravi, Saeed, 2005. "A Failure in the Measurement of Inflation: Results From a Hedonic and Matched Experiment Using Scanner Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 269-281, July.
    2. W. Erwin Diewert & Saeed Heravi & Mick Silver, 2009. "Hedonic Imputation versus Time Dummy Hedonic Indexes," NBER Chapters,in: Price Index Concepts and Measurement, pages 161-196 National Bureau of Economic Research, Inc.
    3. 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.
    4. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
    5. 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 University Rotterdam.
    6. Hill, Robert J., 2006. "Superlative index numbers: not all of them are super," Journal of Econometrics, Elsevier, vol. 130(1), pages 25-43, January.
    7. Robert C. Feenstra & Matthew D. Shapiro, 2003. "High-Frequency Substitution and the Measurement of Price Indexes," NBER Chapters,in: Scanner Data and Price Indexes, pages 123-150 National Bureau of Economic Research, Inc.
    8. 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.
    9. W. Erwin Diewert, 1995. "Axiomatic and Economic Approaches to Elementary Price Indexes," NBER Working Papers 5104, National Bureau of Economic Research, Inc.
    10. 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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    Citations

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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 0.5 ," CARF F-Series CARF-F-342, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. Abe, Naohito & Inakura, Noriko & Tonogi, Akiyuki, 2017. "Effects of the Entry and Exit of Products on Price Indexes," RCESR Discussion Paper Series DP17-2, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    4. Diewert, W. Erwin & Fox, Kevin J., 2016. "Kevin J. Fox Interview of W. Erwin Diewert," Microeconomics.ca working papers erwin_diewert-2016-6, Vancouver School of Economics, revised 02 Jun 2016.
    5. Abe, Naohito & Enda, Toshiki & Inakura, Noriko & Tonogi, Akiyuki, 2015. "Effects of New Goods and Product Turnover on Price Indexes," RCESR Discussion Paper Series DP15-2, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    6. Fox, Kevin J. & Syed, Iqbal A., 2016. "Price discounts and the measurement of inflation," Journal of Econometrics, Elsevier, vol. 191(2), pages 398-406.
    7. repec:aea:jecper:v:31:y:2017:i:2:p:187-210 is not listed on IDEAS
    8. Kota Watanabe & Tsutomu Watanabe, 2014. "Estimating Daily Inflation Using Scanner Data: A Progress Report," UTokyo Price Project Working Paper Series 020, University of Tokyo, Graduate School of Economics.
    9. Daniel Leigh & Weicheng Lian & Marcos Poplawski-Ribeiro & Rachel Szymanski & Viktor Tsyrennikov & Hong Yang, 2017. "Exchange Rates and Trade; A Disconnect?," IMF Working Papers 17/58, International Monetary Fund.
    10. , & 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.
    11. Jan de Haan & Rens Hendriks & Michael Scholz, 2016. "A Comparison of Weighted Time-Product Dummy and Time Dummy Hedonic Indexes," Graz Economics Papers 2016-13, University of Graz, Department of Economics.
    12. Diewert, W. Erwin, 2017. "Productivity Measurement in the Public Sector: Theory and Practice," Microeconomics.ca working papers erwin_diewert-2017-1, Vancouver School of Economics, revised 02 Feb 2017.
    13. repec:eee:jfpoli:v:74:y:2018:i:c:p:212-224 is not listed on IDEAS
    14. Kevin J, Fox. & Iqbal A. Syed, 2016. "Price Discounts and the Measurement of Inflation: Further Results," Discussion Papers 2016-05, School of Economics, The University of New South Wales.
    15. Castellari, Elena & 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.

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