Lexicographic Robustness and the Efficiency of Optimal Mechanisms
TLDR
This paper introduces lexicographic robustness to refine maxmin optimality, characterizing the efficiency of optimal mechanisms.
Key contributions
- Proposes a lexicographic approach to refine the maxmin optimality criterion.
- Characterizes the efficiency of optimal mechanisms using this refined robustness.
- Proper robustness selects ex post efficient mechanisms in screening and auction environments.
- Identifies optimal inefficiencies in public good provision, which worsen in large economies.
Why it matters
The maxmin optimality criterion for robust mechanism design is often too broad and uninformative. This paper refines it with a lexicographic approach, offering clearer insights into optimal mechanism efficiency and its limitations across various economic environments.
Original Abstract
A central challenge in mechanism design is to identify mechanisms whose performance is robust under uncertainty about the environment. The maxmin optimality criterion is commonly used for this purpose, but it often yields a large and economically uninformative set of mechanisms. This paper proposes a lexicographic approach to refining the maxmin criterion and characterizes the efficiency of optimal mechanisms. In canonical screening and auction environments, the strongest refinement $\unicode{x2013}$ proper robustness $\unicode{x2013}$ selects ex post efficient mechanisms. By contrast, in a public good provision environment, it identifies the precise form of optimal inefficiencies, which become severe in large economies.
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