Noisy commitments: The impact of information accuracy on efficiency

We report an experiment designed to test the influence of noisy commitments on efficiency in a simple bargaining game. We investigate two different levels of commitment reliability in a variant of the peasant-dictator game. Theoretical analysis suggests that the reliability of commitments in this game does not affect efficiency. We find that accurate commitments promote efficiency, as expected by game theory. However, noisy commitments are found to impair efficiency. We explain this effect by the differences between incentives off the equilibrium path under conditions of accurate commitments and noisy commitments. This difference changes the game structure and in the current game facilitates more random responses.Commitments, efficiency, experimental economics, information, trust

Cynicism in Negotiation: When Communication Increases Buyers’ Skepticism

The economic literature on negotiation shows that strategic concerns can be a barrier to agreement, even when the buyer values the good more than the seller. Yet behavioral research demonstrates that human interaction can overcome these strategic concerns through communication. We show that there is also a downside of this human interaction: cynicism. Across two studies we focus on a seller-buyer interaction in which the buyer has uncertain knowledge about the goods for sale, but has a positive expected payoff from saying “yes” to the available transaction. Study 1 shows that most buyers accept offers made by computers, but that acceptance rates drop significantly when offers are made by human sellers who communicate directly with buyers. Study 2 clarifies that this effect results from allowing human sellers to communicate with buyers, and shows that such communication focuses the buyers’ attention on the seller’s trustworthiness. The mere situation of negotiated interaction increases buyers’ attention to the sellers’ self-serving motives and, consequently, buyers’ cynicism. Unaware of this downside of interaction, sellers actually prefer to have the opportunity to communicate with buyers

On the descriptive value of loss aversion in decisions under risk: Six clarifications

Previous studies of loss aversion in decisions under risk have led to mixed results. Losses appear to loom larger than gains in some settings, but not in others. The current paper clarifies these results by highlighting six experimental manipulations that tend to increase the likelihood of the behavior predicted by loss aversion. These manipulations include: (1) framing of the safe alternative as the status quo; (2) ensuring that the choice pattern predicted by loss aversion maximizes the probability of positive (rather than zero or negative) outcomes; (3) the use of high nominal (numerical) payoffs; (4) the use of high stakes; (5) the inclusion of highly attractive risky prospects that creates a contrast effect; and (6) the use of long experiments in which no feedback is provided and in which the computation of the expected values is difficult. In addition, the results suggest the possibility of learning in the absence of feedback: The tendency to select simple strategies, like “maximize the worst outcome” which implies “loss aversion”, increases when this behavior is not costly. Theoretical and practical implications are discussed

Cynicism in negotiation: When communication increases buyers’ skepticism

The economic literature on negotiation shows that strategic concerns can be a barrier to agreement, even when the buyer values the good more than the seller. Yet behavioral research demonstrates that human interaction can overcome these strategic concerns through communication. We show that there is also a downside of this human interaction: cynicism. Across two studies we focus on a seller-buyer interaction in which the buyer has uncertain knowledge about the goods for sale, but has a positive expected payoff from saying “yes” to the available transaction. Study 1 shows that most buyers accept offers made by computers, but that acceptance rates drop significantly when offers are made by human sellers who communicate directly with buyers. Study 2 clarifies that this effect results from allowing human sellers to communicate with buyers, and shows that such communication focuses the buyers’ attention on the seller’s trustworthiness. The mere situation of negotiated interaction increases buyers’ attention to the sellers’ self-serving motives and, consequently, buyers’ cynicism. Unaware of this downside of interaction, sellers actually prefer to have the opportunity to communicate with buyers

The Emergence of “Us and Them” in 80 Lines of Code: Modeling Group Genesis in Homogeneous Populations

Psychological explanations of group genesis often require population heterogeneity in identity or other characteristics, whether deep (e.g., religion) or superficial (e.g., eye color). We use game-theoretical agent-based models to explore group genesis in homogeneous populations, and find robust group formation with just two basic principles: reciprocity and transitivity. These emergent groups demonstrate in-group cooperation and out-group defection, even though agents lack common identity. Group formation increases individual payoffs, and group structure is robust to varying levels of reciprocity and transitivity. Increasing population size increases group size more than group number, and manipulating baseline trust in a population has predictable effects on group genesis. An interactive online demonstration enables first-hand exploration of the parameter space (www.mpmlab.org/groups), and available source code (supplementary materials) provides a guide to implementing psychological agent-based models

A Choice Prediction Competition: Choices From Experience and From Description

Erev, Ert, and Roth organized three choice prediction competitions focused on three related choice tasks: one shot decisions from description (decisions under risk), one shot decisions from experience, and repeated decisions from experience. Each competition was based on two experimental datasets: An estimation dataset, and a competition dataset. The studies that generated the two datasets used the same methods and subject pool, and examined decision problems randomly selected from the same distribution. After collecting the experimental data to be used for estimation, the organizers posted them on the Web, together with their fit with several baseline models, and challenged other researchers to compete to predict the results of the second (competition) set of experimental sessions. Fourteen teams responded to the challenge: the last seven authors of this paper are members of the winning teams. The results highlight the robustness of the difference between decisions from description and decisions from experience. The best predictions of decisions from descriptions were obtained with a stochastic variant of prospect theory assuming that the sensitivity to the weighted values decreases with the distance between the cumulative payoff functions. The best predictions of decisions from experience were obtained with models that assume reliance on small samples. Merits and limitations of the competition method are discussed.Economic

The Emergence of 'Us and Them' in 80 Lines of Code: Modeling Group Genesis in Homogeneous Populations

Psychological explanations of group genesis often require population heterogeneity in identity or other characteristics, whether deep (e.g., religion) or superficial (e.g., eye color). We use game-theoretical agent-based models to explore group genesis in homogeneous populations and find robust group formation with just two basic principles: reciprocity and transitivity. These emergent groups demonstrate in-group cooperation and out-group defection, even though agents lack common identity. Group formation increases individual payoffs, and group structure is robust to varying levels of reciprocity and transitivity. Increasing population size increases group size more than group number, and manipulating baseline trust in a population has predictable effects on group genesis. An interactive online demonstration enables first-hand exploration of the parameter space (www.mpmlab.org/groups), and available source code (supplementary materials) provides a guide to implementing psychological agent-based models