Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/217189 
Year of Publication: 
2020
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 11 [Issue:] 1 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2020 [Pages:] 315-348
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
Combining weekly productivity data with weekly productivity beliefs for a large sample of truckers over 2 years, we show that workers tend to systematically and persistently overpredict their productivity. If workers are overconfident about their own productivity at the current firm relative to their outside option, they should be less likely to quit. Empirically, all else equal, having higher productivity beliefs is associated with an employee being less likely to quit. To study the implications of overconfidence for worker welfare and firm profits, we estimate a structural learning model with biased beliefs that accounts for many key features of the data. While worker overconfidence moderately decreases worker welfare, it also substantially increases firm profits.
Subjects: 
Overconfidence
biased learning
turnover
JEL: 
D03
J24
J41
M53
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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