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Substitution Bias in Multilateral Methods for CPI Construction using Scanner Data

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  • Diewert, W. Erwin
  • Fox, Kevin J.

Abstract

The use of multilateral comparison methods in a time series context is increasingly becoming an accepted approach for incorporating scanner data in a Consumer Price Index. The attractiveness stems from the ability to be able to control for chain drift bias. Consensus on two key issues has yet to be achieved: (i) the best multilateral method to use, and (ii) the best way of extending the resulting series when new observations become available. This paper presents theoretical and simulation evidence on the extent of substitution biases in alternative multilateral methods. The multilateral index number formulae studied include the GEKS, CCDI, Geary-Khamis and Weighted Time Product Dummy Methods as well as some price similarity linking methods. The paper also assesses alternative methods for extending non-revisable series, with particular regard to the possibility of introducing chain drift bias. Overall, our results suggest the use of the CCDI index with a new method, the “mean splice†, for updating.

Suggested Citation

  • Diewert, W. Erwin & Fox, Kevin J., 2017. "Substitution Bias in Multilateral Methods for CPI Construction using Scanner Data," Microeconomics.ca working papers erwin_diewert-2017-3, Vancouver School of Economics, revised 23 Mar 2017.
  • Handle: RePEc:ubc:pmicro:erwin_diewert-2017-3
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    12. Sato, Kazuo, 1976. "The Ideal Log-Change Index Number," The Review of Economics and Statistics, MIT Press, vol. 58(2), pages 223-228, May.
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    14. D. S. Prasada Rao, 2005. "On The Equivalence Of Weighted Country‐Product‐Dummy (Cpd) Method And The Rao‐System For Multilateral Price Comparisons," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 51(4), pages 571-580, December.
    15. Inklaar, Robert & Diewert, W. Erwin, 2016. "Measuring industry productivity and cross-country convergence," Journal of Econometrics, Elsevier, vol. 191(2), pages 426-433.
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    Cited by:

    1. W. Erwin Diewert & Kiyohiko G. Nishimura & Chihiro Shimizu & Tsutomu Watanabe, 2020. "Measuring the Services of Durables and Owner Occupied Housing," Advances in Japanese Business and Economics, in: Property Price Index, chapter 0, pages 223-298, Springer.
    2. W. Erwin Diewert & Robert C. Feenstra, 2021. "Estimating the Benefits of New Products," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, National Bureau of Economic Research, Inc.
    3. Diewert, W, Erwin & Feenstra, Robert, 2017. "Estimating the Benefits and Costs of New and Disappearing Products," Microeconomics.ca working papers tina_marandola-2017-12, Vancouver School of Economics, revised 19 Dec 2017.
    4. Jacek Bia{l}ek & Maciej Berk{e}sewicz, 2020. "Scanner data in inflation measurement: from raw data to price indices," Papers 2005.11233, arXiv.org.
    5. Diewert, Erwin, 2019. "Quality Adjustment and Hedonics: A Unified Approach," Microeconomics.ca working papers erwin_diewert-2019-2, Vancouver School of Economics, revised 14 Mar 2019.
    6. Antonio G. Chessa & Robert Griffioen, 2019. "Comparing Price Indices of Clothing and Footwear for Scanner Data and Web Scraped Data," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 509, pages 49-68.
    7. W. Erwin Diewert & Kevin J. Fox, 2020. "Measuring Real Consumption and CPI Bias under Lockdown Conditions," NBER Working Papers 27144, National Bureau of Economic Research, Inc.
    8. Diewert, Erwin & Shimizu, Chihiro, 2019. "Residential Property Price Indexes: Spatial Coordinates versus Neighbourhood Dummy Variables," Microeconomics.ca working papers erwin_diewert-2019-11, Vancouver School of Economics, revised 10 Jan 2020.
    9. Diewert, Erwin, 2018. "Scanner Data, Elementary Price Indexes and the Chain Drift Problem," Microeconomics.ca working papers erwin_diewert-2018-10, Vancouver School of Economics, revised 25 Oct 2018.
    10. Diewert, Erwin & Marandola, Tina, 2018. "Scanner Data, Elementary Price Indexes and the Chain Drift Problem," Microeconomics.ca working papers tina_marandola-2018-9, Vancouver School of Economics, revised 10 Oct 2018.
    11. Robert J. Hill & Michael Scholz & Chihiro & Miriam Steurer, 2020. "Rolling-Time-Dummy House Price Indexes: Window Length, Linking and Options for Dealing with the Covid-19 Shutdown," Graz Economics Papers 2020-14, University of Graz, Department of Economics.

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    More about this item

    Keywords

    Consumer Price Indexes; superlative indexes; chain drift; scanner data; Time Product Dummy method; Geary-Khamis; GEKS and CCDI methods for making inte;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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