The public loss game: An experimental study of public bads

We analyze cooperative behavior of participants who faced a loss. In particular, we extend the Public Good Game by a fixed loss in the beginning of every period. We show that humans change their behavior compared to corresponding studies with gains only. First, in contrast to literature on gains, we observe significant order effects. When participants first play a treatment with punishment, they cooperate less and face higher punishment costs than when first playing a treatment without punishment. The changes are that drastic that punishment does not pay in the first case, while it does in the later. Second, for participants first playing without punishment the contributions in the very first period of play determine the contributions throughout both treatments of the game, yielding higher contributions in the punishment treatment than when playing with gains. Participants punishing first, show no comparable behavior. --public good,punishment,losses,experiment

What automaton model captures decision making? A call for finding a behavioral taxonomy of complexity

When investigating bounded rationality, economists favor finite-state automatons - for example the Mealy machine - and state complexity as a model for human decision making over other concepts. Finite-state automatons are a machine model, which are especially suited for (repetitions of) decision problems with limited strategy sets. In this paper, we argue that finite-state automatons do not suffice to capture human decision making when it comes to problems with infinite strategy sets, such as choice rules. To proof our arguments, we apply the concept of Turing machines to choice rules and show that rational choice has minimal complexity if choices are rationalizable, while complexity of rational choice dramatically increases if choices are no longer rationalizable. We conclude that modeling human behavior using space and time complexity best captures human behavior and suggest to introduce a behavioral taxonomy of complexity describing adequate boundaries for human capabilities

When proposers demand less without need Ultimatum bargaining in the loss domain

Subjects in the loss domain tend to split payoffs equally when bargaining. The ultimatum game offers an ideal mechanism through which economists can investigate whether equal splits are the consequence of proposer generosity or due to their anticipation that the responders will reject lower offers. This paper experimentally compares ultimatum bargaining in a loss domain with that under gains. The results reveal that, although responders do not expect more in the loss domain, proposers do make higher offers. As such, proposers reach agreements more often in the loss domain than they do in the gains domain, and responders receive higher payoffs

Do hormones impact behavior in the minimum effort game? An experimental investigation of human behavior during the weakest link game after the administration of vasopressin

This paper describes an experimental study involving the minimum effort game. In this game, each player faces a trade-off between risk and payoff. Within each group, half of the subjects were administered with vasopressin in nasal spray form while half received a placebo. We found that subjects who received vasopressin were more likely to play the minimally risky strategy in the group and less likely to focus on payoff levels than those who received the placebo

Complexity of Networking: An Experimental Study of the Network Hawk Dove Game

Complexity of strategies is central for human decision making and attracted interest of different game theorists in the recent years. Nevertheless, behavioral economists have neglected the importance of complexity in their analyses. In this paper, we analyze network formation and action selection in a Hawk Dove Game with focus on complexity aspects. We conduct experiments with three variants of the game which are equivalent from a game theoretic perspective, but differ from a complexity theoretic perspective. Our results show, that complexity of decision making has an impact on the strategies played and that efficiency is higher the less complex the decision problem is

Myopic behavior and overall utility maximization - A study of linked hawks and doves

At present, in the domain of simultaneous action selection and network formation games, game-theoretic behavior and experimental observations are not consistent. While theory typically predicts inefficient outcomes for (anti- )co-ordination games, experiments show that subjects tend to play efficient (non-Nash) strategy profiles. One reason for this discrepancy is the tendency to model corresponding games as one-shot and derive predictions. In this paper, we calculate the equilibria for a finitely repeated version of the Hawk-Dove game with endogenous network formation and show that the repetition leads to additional sub-game perfect equilibria; namely, the efficient strategy profiles played by human subjects. However, efficiency crucially depends on the design of the game. This paper theoretically demonstrates that, although technically feasible, the efficient profiles are not sub-game perfect equilibria if actions are fixed after an initial period. We confirm this result using an experimental study that demonstrates how payoffs are higher if actions are never fixed

When social preferences and anxiety drive behavior and vasopressin does not: An neuroeconomic analysis of vasopressin and the Hawk-Dove game

We delineated the causal influence of vasopressin on behavior in an iterated Hawk-Dove game. While subjects treated with vasopressin tend to be more aggressive in response to group members who did not coordinate on equilibrium instantaneously, this effect vanishes as soon as the subjects reach an equilibrium. More than vasopressin, social preferences and trait anxiety of the subjects predict the observed behavior

Equilibrium selection under limited control: An experimental study of the network Hawk-Dove game

For games of simultaneous action selection and network formation, game-theoretic behavior and experimental observations are not in line: While theory typically predicts inefficient outcomes for (anti-)coordination games, experiments show that subjects tend to play efficient (non Nash) strategy profiles. A reason for this discrepancy is the tendency to model corresponding games as one-shot and derive predictions. In this paper, we calculate the equilibria for a finitely repeated version of the Hawk-Dove game with endogenous network formation and show that the repetition leads to additional equilibria, namely the efficient ones played by human subjects. We confirm our results by an experimental study. In addition, we show both theoretically and experimentally that the equilibria reached crucially depend on the order in which subjects adjust their strategy. Subjects only reach efficient outcomes if they first adapt their action and then their network. If they choose their network first, they do not reach efficient outcomes