Data and incentives

Annie Liang, Erik Madsen

    Research output: Contribution to journalArticlepeer-review

    Abstract

    “Big data” gives markets access to previously unmeasured characteristics of individual agents. Policymakers must decide whether and how to regulate the use of this data. We study how new data affects incentives for agents to exert effort in settings such as the labor market, where an agent's quality is initially unknown but is forecast from an observable outcome. We show that measurement of a new covariate has a systematic effect on the average effort exerted by agents, with the direction of the effect determined by whether the covariate is informative about long-run quality versus a shock to short-run outcomes. For a class of covariates satisfying a statistical property that we call strong homoskedasticity, this effect is uniform across agents. More generally, new measurements can impact agents unequally, and we show that these distributional effects have a first-order impact on social welfare.

    Original languageEnglish (US)
    Pages (from-to)407-448
    Number of pages42
    JournalTheoretical Economics
    Volume19
    Issue number1
    DOIs
    StatePublished - Jan 2024

    Keywords

    • Big data
    • C72
    • career concerns
    • D83
    • effort incentives
    • forecasting
    • L51

    ASJC Scopus subject areas

    • General Economics, Econometrics and Finance

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