Marisa Ratto
This paper considers the role of task preferences on the relationship between risk and incentives. We analyse a principal-agent model in which an agent performs two tasks that determine two separate outputs. The model extends the standard approach of the multitasking literature by introducing the assumption that the cost of effort is not simply a function of total effort but varies depending on the effort allocation across tasks, to reflect the agent's task preferences. Results show that when the two outputs are measured with different precision, it can be optimal for the principal to set higher marginal incentives on the output measured with less precision. Hence the standard result of the negative correlation between risk and incentives does not necessarily hold.
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