One for all, all for one---von Neumann, Wald, Rawls, and Pareto

Applications of the maximin criterion extend beyond economics to statistics, computer science, politics, and operations research. However, the maximin criterion---be it von Neumann's, Wald's, or Rawls'---draws fierce criticism due to its extremely pessimistic stance. I propose a novel concept, dubbed the optimin criterion, which is based on (Pareto) optimizing the worst-case payoffs of tacit agreements. The optimin criterion generalizes and unifies results in various fields: It not only coincides with (i) Wald's statistical decision-making criterion when Nature is antagonistic, (ii) the core in cooperative games when the core is nonempty, though it exists even if the core is empty, but it also generalizes (iii) Nash equilibrium in $n$-person constant-sum games, (iv) stable matchings in matching models, and (v) competitive equilibrium in the Arrow-Debreu economy. Moreover, every Nash equilibrium satisfies the optimin criterion in an auxiliary game

Boundedly rational versus optimization-based models of strategic thinking and learning in games

The paper is a comment on the article by R. Harstad and R. Selten and considers the tradeoff between bounded rationality and optimization models in the game-theoretic context. The author shows that in most of the models elements of opimization are still retained and that it is thus more productive to further improve the optimization-based modeling rather than to abandon them altogether in favour of bounded rationality

Comparing Loyalty Program Tiering Strategies: An investigation from the gaming industry

Loyalty programs are popular marketing strategies developed for the purpose of attracting, maintaining, and enhancing customer relationships. Due to the explosive worldwide growth of, and increased competition within, the casino industry has compelled contemporary casino marketers to rely more heavily on loyalty programs to increase guest allegiance and the frequency of repeat visits from their customers. Despite the widespread usage of loyalty programs across various gaming businesses in Las Vegas, its effectiveness has not quite been validated. The purpose of this study is to examine customers’ behavioral loyalty within the Las Vegas gaming industry and examine the effectiveness of a specific loyalty program using secondary data obtained from a Las Vegas casino hotel. Specifically, this study segmented loyalty program members to investigate the effectiveness of a casino loyalty program’s tiering strategy on members’ purchase behavior. Further, this study employed Recency-Frequency-Monetary (RFM) analysis to examine two different types of tiering strategies

The Threat of Exclusion and Relational Contracting

Relational contracts have been shown to mitigate moral hazard in labor and credit markets. A central assumption in most theoretical and experimental studies is that, upon misbehaving, agents can be excluded from their current source of income and have to resort to less attractive outside options. This threat of exclusion is unrealistic in many environments, and especially in credit and investment contexts. We examine experimentally the emergence and time structure of relational contracts when the threat of exclusion is weakened. We focus on bilateral credit relationships in which strategic default is possible. We compare a weak exclusion treatment in which defaulting borrowers can reinvest borrowed funds, to a strong exclusion treatment in which defaulting borrowers must liquidate borrowed funds. We find that under weak exclusion more relationships break down in early periods and credit relationships are more likely to “start small”

Behavioral Economics: Past, Present, Future

Behavioral economics increases the explanatory power of economics by providing it with more realistic psychological foundations. This book consists of representative recent articles in behavioral economics. This chapter is intended to provide an introduction to the approach and methods of behavioral economics, and to some of its major findings, applications, and promising new directions. It also seeks to fill some unavoidable gaps in the chapters’ coverage of topics

The effect of partner-directed emotion in social exchange decision-making

Despite the prevalence of studies examining economic decision-making as a purely rational phenomenon, common sense suggests that emotions affect our decision-making particularly in a social context. To explore the influence of emotions on economic decision-making, we manipulated opponent-directed emotions prior to engaging participants in two social exchange decision-making games (the Trust Game and the Prisoner's Dilemma). Participants played both games with three different (fictional) partners and their tendency to defect was measured. Prior to playing each game, participants exchanged handwritten “essays” with their partners, and subsequently exchanged evaluations of each essay. The essays and evaluations, read by the participant, were designed to induce either anger, sympathy, or a neutral emotional response toward the confederate with whom they would then play the social exchange games. Galvanic skin conductance level (SCL) showed enhanced physiological arousal during anger induction compared to both the neutral and sympathy conditions. In both social exchange games, participants were most likely to defect against their partner after anger induction and least likely to defect after sympathy induction, with the neutral condition eliciting intermediate defection rates. This pattern was found to be strongest in participants exhibiting low cognitive control (as measured by a Go/no-Go task). The findings indicate that emotions felt toward another individual alter how one chooses to interact with them, and that this influence depends both on the specific emotion induced and the cognitive control of the individual

Penalty-regulated dynamics and robust learning procedures in games

Starting from a heuristic learning scheme for N-person games, we derive a new class of continuous-time learning dynamics consisting of a replicator-like drift adjusted by a penalty term that renders the boundary of the game's strategy space repelling. These penalty-regulated dynamics are equivalent to players keeping an exponentially discounted aggregate of their on-going payoffs and then using a smooth best response to pick an action based on these performance scores. Owing to this inherent duality, the proposed dynamics satisfy a variant of the folk theorem of evolutionary game theory and they converge to (arbitrarily precise) approximations of Nash equilibria in potential games. Motivated by applications to traffic engineering, we exploit this duality further to design a discrete-time, payoff-based learning algorithm which retains these convergence properties and only requires players to observe their in-game payoffs: moreover, the algorithm remains robust in the presence of stochastic perturbations and observation errors, and it does not require any synchronization between players.Comment: 33 pages, 3 figure