arXiv subjects

Ashwin Kambhampati

Publications and source records attributed to Ashwin Kambhampati.

3 recordsLinked to original sources

arXiv2026

Lexicographic Robustness and the Efficiency of Optimal Mechanisms

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.

econ.TH↗

arXiv2025

Payoff Continuity in Games of Incomplete Information Across Models of Knowledge

Equilibrium predictions in games of incomplete information are sensitive to the assumed information structure. Monderer and Samet (1996) and Kajii and Morris (1998) define topological notions of proximity for common prior information structures such that two information structures are close if and only if (approximate) equilibrium payoffs are close. However, Monderer and Samet (1996) fix a common prior and define their topology on profiles of partitions over a state space, whereas Kajii and Morris (1998) define their topology on common priors over the product of a state space and a type space. We prove the open conjecture that two partition profiles are close in the Monderer and Samet (1996) topology if and only if there exists a labeling of types such that the associated common priors are close in the Kajii and Morris (1998) topology.

econ.TH↗

arXiv2024

Robust Performance Evaluation of Independent and Identical Agents

A principal provides nondiscriminatory incentives for independent and identical agents. The principal cannot observe the agents' actions, nor does she know the entire set of actions available to them. It is shown, very generally, that any worst-case optimal contract is nonaffine in performances. In addition, each agent's pay must depend on the performance of another. In the case of two agents and binary output, existence of a worst-case optimal contract is established and it is proven that any such contract exhibits joint performance evaluation -- each agent's pay is strictly increasing in the performance of the other. The analysis identifies a fundamentally new channel leading to the optimality of nonlinear team-based incentive pay.

econ.TH↗