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Hard Numbers: Open Consumer Price Database

Author

Listed:
  • Alex Isakov

    (VTB Capital)

  • Rodion Latypov

    (VTB Capital)

  • Andrey Repin

    (VTB Capital)

  • Egor Postolit

    (VTB Capital)

  • Alexey Evseev

    (RANEPA)

  • Elena Sinelnikova-Muryleva

    (RANEPA)

Abstract

We document a new source of consumer price microdata. The new database allows researchers studying consumer price behaviour to access current and granular raw statistical observations. The range of observed prices fully covers goods and services of the Rosstat's CPI sample and extends beyond it. In this paper, we pursue two objectives. First, we describe the data collection mechanism, data structure, and their access protocols, as well provide four complete illustrations of their application using open API: i) training machine models of product classification based on text labels, ii) real-time tracking of product prices, iii) estimating hedonic regressions for product groups, and iv) calculating arbitrary analytical price indices. Second, we share a set of basic skills and technologies for the benefit of researchers interested in creating their own sources of alternative data.

Suggested Citation

  • Alex Isakov & Rodion Latypov & Andrey Repin & Egor Postolit & Alexey Evseev & Elena Sinelnikova-Muryleva, 2021. "Hard Numbers: Open Consumer Price Database," Russian Journal of Money and Finance, Bank of Russia, vol. 80(1), pages 104-119, March.
    • Handle: RePEc:bkr:journl:v:80:y:2021:i:1:p:104-119
    DOI: 10.31477/rjmf.202101.104
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    References listed on IDEAS

    as
    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. Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
    3. Crystal G. Konny & Brendan K. Williams & David M. Friedman, 2019. "Big Data in the US Consumer Price Index: Experiences and Plans," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 69-98, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Vladimir Bessonov, 2021. "What Opportunities Do New Technologies Bring About for Price Statistics?," Russian Journal of Money and Finance, Bank of Russia, vol. 80(1), pages 120-126, March.

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    More about this item

    Keywords

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    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other

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