This paper aims to improve the practical applicability of the classic theory of incentive contracts under moral hazard. We establish conditions under which the information provided by an A/B test of incentive contracts is sufficient for answering the question of how best to improve a status quo incentive contract, given a priori knowledge of the agent’s monetary preferences. We assess the empirical relevance of this result using data from DellaVigna and Pope’s (2018) study of a variety of incentive contracts. Finally, we discuss how our framework can be extended to incorporate additional considerations beyond those in the classic theory.

We study subgame-perfect implementation (SPI) mechanisms that have been proposed as a solution to incomplete contracting problems. We show that these mechanisms, which are based on off-equilibrium arbitration clauses that impose large fines for lying and the inappropriate use of arbitration, have severe behavioral constraints because the fines induce retaliation against legitimate uses of arbitration. Incorporating reciprocity preferences into the theory explains the observed behavioral patterns and helps us develop a new mechanism that is more robust and achieves high rates of truth-telling and efficiency. Our results highlight the importance of tailoring implementation mechanisms to the underlying behavioral environment.