  This paper studies the design of mechanisms that are robust to
misspecification. We introduce a novel notion of robustness that connects a
variety of disparate approaches and study its implications in a wide class of
mechanism design problems. This notion is quantifiable, allowing us to
formalize and answer comparative statics questions relating the nature and
degree of misspecification to sharp predictions regarding features of feasible
mechanisms. This notion also has a behavioral foundation which reflects the
perception of ambiguity, thus allowing the degree of misspecification to emerge
endogenously. In a number of standard settings, robustness to arbitrarily small
amounts of misspecification generates a discontinuity in the set of feasible
mechanisms and uniquely selects simple, ex post incentive compatible mechanisms
such as second-price auctions. Robustness also sheds light on the value of
private information and the prevalence of full or virtual surplus extraction.
