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I study the effect of task difficulty on workers' effort and compare it to the effect of monetary rewards in an incentivized lab experiment. I find that task difficulty has an inverse-U effect on effort, and that this effect is quantitatively large 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. I show that the inverse-U pattern of effort response to difficulty is not consistent with the Expected Utility model but is consistent with the Rank-Dependent Utility model that allows for non-linear probability weighting. I structurally estimate the model and find that it successfully captures the treatment effects observed in the data. I discuss the implications of my findings for the design of optimal incentive schemes for workers and modeling effort.


ESI Working Paper 19-21



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