Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/296463 
Year of Publication: 
2024
Citation: 
[Journal:] Theoretical Economics [ISSN:] 1555-7561 [Volume:] 19 [Issue:] 1 [Year:] 2024 [Pages:] 407-448
Publisher: 
The Econometric Society, New Haven, CT
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 or about a shock to short-run outcomes. For a class of covariates satisfying a statistical property 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.
Subjects: 
Big data
career concerns
effort incentives
forecasting
JEL: 
C72
D83
L51
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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