Setting Incentives for Scientists Who Engage in Research and Other Activities: An Application of Principal-Agent Theory

Abstract

 The objective of this paper is to develop an optimal incentive system for multitaskingscientists in universities or professors under repeat contracting. With the aid of a principalagentmodel under repeat contracting, we show that (i) when a second task is assigned to aprofessor and the two tasks are related, the size of the optimal incentive rate for the first task isreduced in some situations but not others relative to that of a single task, (ii) with an increasein the noise in the technical relationship of the second task or imprecision in outputmeasurement, the optimal incentive rate for that task is reduced and for the first task may bereduced or increased , (iii) with greater efficiency of the professor in producing the secondoutput, as reflected in ability relative to cost of effort, the optimal incentive rate for the firsttask generally decreases, (iv) if the output of the professor’s two tasks are negativelycorrelated then the optimal incentive rate on the first task declines as the size of thiscorrelation increases. The size of the guarantee is always reduced as the professor’s ability fora task increases, but is increased as his cost of effort, noisiness of the technology ormeasurement of output, or correlation between the two outputs increases. It is also possiblethat, as a professor undertakes several difficult-to-measure tasks, the incentive rate will bereduced to the point that an optimal compensation system will involve only a guaranteedsalary, which is a very weak incentive for effort. Selective audits may be useful in thesesituations.incentives; Principal-agent model; Multitask; scientists; professors; respeat contracting; linear contracts