  Economic mechanisms administer the allocation of resources to interested
agents based on their self-reported types. One objective in mechanism design is
to design a strategyproof process so that no agent will have an incentive to
misreport its type. However, typical analyses of the incentives properties of
mechanisms operate under strong, usually untestable assumptions. Empirical,
data-oriented approaches are, at best, under-developed. Furthermore,
mechanism/policy evaluation methods usually ignore the dynamic nature of a
multi-agent system and are thus inappropriate for estimating long-term effects.
We introduce the problem of estimating the causal effects of mechanisms on
incentives and frame it under the Rubin causal framework \citep{rubin74,
rubin78}. This raises unique technical challenges since the outcome of interest
(agent truthfulness) is confounded with strategic interactions and,
interestingly, is typically never observed under any mechanism. We develop a
methodology to estimate such causal effects that using a prior that is based on
a strategic equilibrium model. Working on the domain of kidney exchanges, we
show how to apply our methodology to estimate causal effects of kidney
allocation mechanisms on hospitals' incentives. Our results demonstrate that
the use of game-theoretic prior captures the dynamic nature of the kidney
exchange multiagent system and shrinks the estimates towards long-term effects,
thus improving upon typical methods that completely ignore agents' strategic
behavior.

Computer Science and Game Theory;Methodology