Payoff Information and Learning in Signaling Games

We add the assumption that players know their opponents' payoff functions and rationality to a model of non-equilibrium learning in signaling games. Agents are born into player roles and play against random opponents every period. Inexperienced agents are uncertain about the prevailing distribution of opponents' play, but believe that opponents never choose conditionally dominated strategies. Agents engage in active learning and update beliefs based on personal observations. Payoff information can refine or expand learning predictions, since patient young senders' experimentation incentives depend on which receiver responses they deem plausible. We show that with payoff knowledge, the limiting set of long-run learning outcomes is bounded above by rationality-compatible equilibria (RCE), and bounded below by uniform RCE. RCE refine the Intuitive Criterion (Cho and Kreps, 1987) and include all divine equilibria (Banks and Sobel, 1987). Uniform RCE sometimes but not always exists, and implies universally divine equilibrium.Comment: This material was previously part of a larger paper titled "Type-Compatible Equilibria in Signalling Games," which split into two smaller papers: "Learning and Type Compatibility in Signaling Games" and "Payoff Information and Learning in Signaling Games.

Learning and Type Compatibility in Signaling Games

Which equilibria will arise in signaling games depends on how the receiver interprets deviations from the path of play. We develop a micro-foundation for these off-path beliefs, and an associated equilibrium refinement, in a model where equilibrium arises through non-equilibrium learning by populations of patient and long-lived senders and receivers. In our model, young senders are uncertain about the prevailing distribution of play, so they rationally send out-of-equilibrium signals as experiments to learn about the behavior of the population of receivers. Differences in the payoff functions of the types of senders generate different incentives for these experiments. Using the Gittins index (Gittins, 1979), we characterize which sender types use each signal more often, leading to a constraint on the receiver's off-path beliefs based on "type compatibility" and hence a learning-based equilibrium selection

Topologies on Type

We define and analyze a "strategic topology" on types in the Harsanyi-Mertens- Zamir universal type space, where two types are close if their strategic behavior is similar in all strategic situations. For a fixed game and action define the distance be- tween a pair of types as the di¤erence between the smallest " for which the action is " interim correlated rationalizable. We define a strategic topology in which a sequence of types converges if and only if this distance tends to zero for any action and game. Thus a sequence of types converges in the strategic topology if that smallest " does not jump either up or down in the limit. As applied to sequences, the upper-semicontinuity prop- erty is equivalent to convergence in the product topology, but the lower-semicontinuity property is a strictly stronger requirement, as shown by the electronic mail game. In the strategic topology, the set of "finite types" (types describable by finite type spaces) is dense but the set of finite common-prior types is not.rationalizability, incomplete informa- tion, common knowledge, universal type space, strategic topology.

Competing Auctions

This paper studies the conditions under which two competing and otherwise identical markets or auction sites of different sizes can coexist in equilibrium, without the larger one attracting all of the smaller one’s patrons. We find that the range of equilibrium market sizes depends on the aggregate buyer-seller ratio, and also whether the markets are especially "thin. "

Knife Edge of Plateau: When Do Market Models Tip?

This paper studies whether agents must agglomerate at a single location in a class of models of two-sided interaction. In these models there is an increasing returns effect that favors agglomeration, but also a crowding or market-impact effect that makes agents prefer to be in a market with fewer agents of their own type. We show that such models do not tip in the way the term is commonly used. Instead, they have a broad plateau of equilibria with two active markets, and tipping occurs only when one market is below a critical size threshold. Our assumptions are fairly weak, and are satisfied in Krugman's [1991b] model of labor market pooling, a heterogeneous-agent version of Pagano's [1989] asset market model, and Ellison, Fudenberg and M”bius's [2002] model of competing auctions.