IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2310.04242.html
   My bibliography  Save this paper

A New Weighted Food CPI from Scanner Big Data in China

Author

Listed:
  • Zhenkun Zhou
  • Zikun Song
  • Tao Ren

Abstract

Scanner big data has potential to construct Consumer Price Index (CPI). The study introduces a new weighted price index called S-FCPIw, which is constructed using scanner big data from retail sales in China. We address the limitations of China's CPI especially for its high cost and untimely release, and demonstrate the reliability of S-FCPIw by comparing it with existing price indices. S-FCPIw can not only reflect the changes of goods prices in higher frequency and richer dimension, and the analysis results show that S-FCPIw has a significant and strong relationship with CPI and Food CPI. The findings suggest that scanner big data can supplement traditional CPI calculations in China and provide new insights into macroeconomic trends and inflation prediction. We have made S-FCPIw publicly available and update it on a weekly basis to facilitate further study in this field.

Suggested Citation

  • Zhenkun Zhou & Zikun Song & Tao Ren, 2023. "A New Weighted Food CPI from Scanner Big Data in China," Papers 2310.04242, arXiv.org, revised Oct 2023.
    • Handle: RePEc:arx:papers:2310.04242
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2310.04242
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. W. Erwin Diewert, 1998. "Index Number Issues in the Consumer Price Index," Journal of Economic Perspectives, American Economic Association, vol. 12(1), pages 47-58, Winter.
    3. 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.
    4. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou, Zhenkun & Wu, Danni & Su, Zhi & Ren, Tao, 2024. "Exploring the investment value of retail sales growth: Evidence from the China Retailer Alliance," Finance Research Letters, Elsevier, vol. 63(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Patrick Bajari & Zhihao Cen & Victor Chernozhukov & Manoj Manukonda & Jin Wang & Ramon Huerta & Junbo Li & Ling Leng & George Monokroussos & Suhas Vijaykunar & Shan Wan, 2023. "Hedonic prices and quality adjusted price indices powered by AI," CeMMAP working papers 08/23, Institute for Fiscal Studies.
    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, pages 437-473, National Bureau of Economic Research, Inc.
    3. 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.
    4. W. Erwin Diewert & Kevin J. Fox, 2022. "Measuring real consumption and consumer price index bias under lockdown conditions," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 480-502, February.
    5. Zhenkun Zhou & Zikun Song & Tao Ren, 2022. "Predicting China's CPI by Scanner Big Data," Papers 2211.16641, arXiv.org, revised Oct 2023.
    6. 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.
    7. Diewert, Erwin & Feenstra, Robert, 2019. "Estimating the Benefits of New Products: Some Approximations," Microeconomics.ca working papers erwin_diewert-2019-3, Vancouver School of Economics, revised 13 Mar 2019.
    8. 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.
    9. Diewert, Erwin & Shimizu, Chihiro, 2015. "Residential Property Price Indices For Tokyo," Macroeconomic Dynamics, Cambridge University Press, vol. 19(8), pages 1659-1714, December.
    10. 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.
    11. 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.
    12. Tsutomu Watanabe & Tomoyoshi Yabu, 2018. "The Demand for Money at the Zero Interest Rate Bound," CARF F-Series CARF-F-444, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    13. Erica L. Groshen & Brian C. Moyer & Ana M. Aizcorbe & Ralph Bradley & David M. Friedman, 2017. "How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 187-210, Spring.
    14. Kozo Ueda & Kota Watanabe & Tsutomu Watanabe, 2021. "Household Inventory, Temporary Sales, and Price Indices," CARF F-Series CARF-F-520, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    15. 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.
    16. Erwin Diewert & John Greenlees & Charles R. Hulten, 2009. "Introduction: What Are the Issues?," NBER Chapters, in: Price Index Concepts and Measurement, pages 1-16, National Bureau of Economic Research, Inc.
    17. Diewert, Erwin & FOX, Kevin J. Fox & SCHREYER, Paul, 2017. "The Digital Economy, New Products and Consumer Welfare," Microeconomics.ca working papers erwin_diewert-2017-12, Vancouver School of Economics, revised 14 Dec 2017.
    18. Leonard I. Nakamura, 2010. "Intangible Assets And National Income Accounting," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(s1), pages 135-155, June.
    19. Sueyoshi, Toshiyuki & Goto, Mika, 2001. "Slack-adjusted DEA for time series analysis: Performance measurement of Japanese electric power generation industry in 1984-1993," European Journal of Operational Research, Elsevier, vol. 133(2), pages 232-259, January.
    20. Brynjolfsson, Erik & Collis, Avinash & Diewert, W. Erwin & Eggers, Felix & Fox, Kevin J., 2019. "GDP-B: Accounting for the Value of New and Free Goods in the Digital Economy," OSF Preprints sptfu, Center for Open Science.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2310.04242. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.