We investigate in a laboratory setting whether revealing information on intelligence affects behavior in games with repeated interactions. In our experimental design we communicate information on the cognitive ability of both players. We use three stage games: Prisoners’ Dilemma (PD) and two...

Under the assumption that individuals know the conditional distributions of signals given the payoff-relevant parameters, existing results conclude that as individuals observe infinitely many signals, their beliefs about the parameters will eventually merge. We first show that these results are...

We develop a model of information exchange through communication and investigate its implications for information aggregation in large societies. An \textit{underlying state} determines payoffs from different actions. Agents decide which others to form a costly \textit{communication link} with,...

Predictions under common knowledge of payoffs may differ from those under arbitrarily, but finitely, many orders of mutual knowledge; Rubinstein's (1989)Email game is a seminal example. Weinstein and Yildiz (2007) showed that the discontinuity in the example generalizes: for all types with...

Restricting attention to economic environments, we study implementation under perturbed better-response dynamics (BRD). A social choice function (SCF) is implementable in stochastically stable strategies of perturbed BRD whenever the only outcome supported by the stochastically stable strategies...

A high court has to decide whether a lawis constitutional, unconstitutional, or interpretable. The voting system is runoff. Runoff voting systems can be interpreted both, as social choice functions or as mechanisms. It is known that, for universal domains of preferences, runoff voting systems...

We introduce a learning framework in which a principal seeks to determine the ability of a strategic agent. The principal assigns a test consisting of a finite sequence of tasks. The test is adaptive: each task that is assigned can depend on the agent's past performance. The probability of...

This paper provides a simple theoretical framework to evaluate the effect of key parameters of ranking algorithms, namely popularity and personalization parameters, on measures of platform engagement, misinformation and polarization. The results show that an increase in the weight assigned to...

Bayesian updating is the dominant theory of learning. However, the theory is silent about how individuals react to events that were previously unforeseeable or unforeseen. Building on a recently developed axiomatic framework to analyze such situations, we test if subjects update their beliefs...