Microeconomic Theory

Title: Keeping the agents in the dark: Competing Mechanisms, Private Disclosures, and the Revelation Principle (with Andrea Attar, Eloisa Campioni, and Alessandro Pavan).

Abstract: We study the design of market information in competing-mechanism games. We identify a new dimension, private disclosures, whereby the principals asymmetrically inform the agents of how their mechanisms operate. We show that private disclosures have two important effects. First, they can raise a principal's payoff guarantee against her competitors' threats. Second, they can support equilibrium outcomes and payoffs that cannot be supported with standard mechanisms. These results call for a novel approach to competing mechanisms, which we develop to identify a canonical game and a canonical class of equilibria, thereby establishing a new revelation principle for this class of environments.

Title: Too many cooks (together with Hyungmin Park)

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Title: Learning, Fast and Slow

Abstract: As learning agents are increasingly deployed in strategic environments, the question of how to strategically choose a learning method becomes economically relevant. We introduce a meta-game in which decision makers select learning rates in continuous-time projected gradient dynamics and evaluate payoffs along the entire trajectory of the resulting inner game, not merely at its limit.

We use $2 \times 2$ games to map the strategic considerations that arise in choosing the speed of learning. Three game classes produce three qualitatively distinct phenomena. In dominance-solvable games, faster learning is unambiguously beneficial under strategic complementarity, but best responses become non-monotonic under strategic substitutability, so that both players may optimally moderate their speeds. In coordination games, the ratio of learning rates governs basins of attraction, enabling equilibrium selection but introducing payoff discontinuities that cause standard existence results to fail. In zero-sum games, each player has a strictly monotonic incentive to increase their learning rate, generating an arms race with no equilibrium when rates are unbounded. Finally, we show that near any convergent Nash equilibrium every player strictly prefers to learn faster, implying that the richer phenomena above are driven by behaviour away from equilibria.

Title: Signaling with Plausible Deniability joint with Andrew McClellan

This is a new paper so there is no draft yet.

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