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The benefits of transaction-level data: The case of NielsenIQ scanner data

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  • Dichev, Ilia D.
  • Qian, Jingyi

Abstract

This study explores whether NielsenIQ scanner data from U.S. retailers contain incremental information about the GAAP revenue of corresponding manufacturers. Using retail product/store/week data from 2006 to 2018, we construct a measure of aggregated consumer purchases at the manufacturer/quarter level, and find that it strongly predicts GAAP revenues. In addition, analyst forecasts of revenues have predictable errors, which implies that analysts do not fully incorporate the information in consumer purchases. Exploring investment implications, we find that hedge portfolios that buy (sell) stocks of firms with high (low) abnormal consumer purchases generate annualized returns on the magnitude of 14%–19%, depending on specification. Overall, these findings suggest that scanner data on consumer purchases provide an information edge over GAAP revenue, shedding light on the benefits of using transactional data.

Suggested Citation

  • Dichev, Ilia D. & Qian, Jingyi, 2022. "The benefits of transaction-level data: The case of NielsenIQ scanner data," Journal of Accounting and Economics, Elsevier, vol. 74(1).
    • Handle: RePEc:eee:jaecon:v:74:y:2022:i:1:s0165410122000180
    DOI: 10.1016/j.jacceco.2022.101495
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    More about this item

    Keywords

    Transactional data; Consumer purchase; Equity valuation; Market efficiency;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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