Abstract
A recursive dynamic agency model is developed for situations where the state of nature follows a Markov process. The repeated agency model is a special case. It is found that the optimal effort depends not only on current performance but also on past performances, and the disparity between current and past performances is a crucial determinant in the optimal contract. In a special case when both the principal and the agent are risk neutral, the first best is achieved by a semi-linear contract. In another special case of a repeated version, the first best is again achieved when the discount rate converges to zero. For the general model, a computing algorithm is developed, which can be implemented in MathCAD to find the solution numerically.
Published Version
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