Washington University in Saint Louis
August 1, 2014
I examine what basic properties of the monitoring technology allow us to implement near-efficient outcomes in dynamic agency models with imperfect public monitoring. Specifically, in a T-period model where signals can depend arbitrarily on past actions and exhibit serial correlation, I show that near-efficiency obtains when T is large if the signal process has sufficiently concentrated measures and conveys enough information about the agent's true profit contribution, a condition that is almost tight in a class of agency models with frequent actions. To prove these results, I construct test contracts which attain robust performances for each T even if details of the signal process are not exactly known to the contract designer.
Number of Pages in PDF File: 39
Keywords: dynamic agency; robust incentives
JEL Classification: D86working papers series
Date posted: July 6, 2013 ; Last revised: September 29, 2014
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