Level-K Mechanism Design
Models of choice where agents see others as less sophisticated than themselves have significantly different, sometimes more accurate, pre- dictions in games than does Nash equilibrium. When it comes to mech- anism design, however, they turn out to have surprisingly similar impli- cations. This paper provides tight necessary and sufficient conditions for implementation with bounded depth of reasoning, discussing the role and implications of different behavioral anchors. The central con- dition slightly strenghthens standard incentive constraints, and we term it strict-if-responsive Bayesian incentive compatibility (SIRBIC).
|Date of creation:||2016|
|Contact details of provider:|| Postal: Department of Economics, Brown University, Providence, RI 02912|
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