| 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. |