Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287036 
Year of Publication: 
2021
Citation: 
[Journal:] Experimental Economics [ISSN:] 1573-6938 [Volume:] 25 [Issue:] 1 [Publisher:] Springer US [Place:] New York, NY [Year:] 2021 [Pages:] 170-202
Publisher: 
Springer US, New York, NY
Abstract: 
I study the effect of task difficulty on workers' effort. I find that task difficulty has an inverse-U effect on effort and that this effect is quantitatively large, especially when compared to the effect of conditional monetary rewards. Difficulty acts as a mediator of monetary rewards: conditional rewards are most effective at the intermediate or high levels of difficulty. The inverse-U pattern of effort response to difficulty is inconsistent with many popular models in the literature, including the Expected Utility models with the additively separable cost of effort. I propose an alternative mechanism for the observed behavior based on non-linear probability weighting. I structurally estimate the proposed model and find that it successfully captures the behavioral patterns observed in the data. I discuss the implications of my findings for the design of optimal incentive schemes for workers and for the models of effort provision.
Subjects: 
Incentives
Task difficulty
Monetary rewards
Effort provision
Probability weighting
JEL: 
C91
D91
D81
J20
J33
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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