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on Evolutionary Economics |
| By: | Anderlini, Luca; Felli, Leonardo; Piccione, Michele |
| Abstract: | How do mechanisms that enforce cooperation emerge in a society where none are available and agents are endowed with just raw power that allows a more powerful agent to expropriate a less powerful one? We study a model where expropriation is costly and agents can choose whether to engage in surplus-augmenting cooperation or engage in expropriation. While in bilateral relations, if cooperation is not overwhelmingly productive and expropriation is not too costly, the latter will prevent cooperation, when there are three or more agents, powerful ones can become enforcers of cooperation for agents ranked below them. In equilibrium they will expropriate smaller amounts from multiple weaker cooperating agents who in turn will not deviate for fear of being expropriated more heavily because of their larger expropriation proceeds. Surprisingly, the details of the power structure are irrelevant for the existence of equilibria with enforcement provided that enough agents are present and one is ranked above all others. These details are instead key to the existence of other highly noncooperative equilibria that are obtained in certain cases. |
| Keywords: | Jungle, power structures, enforcement, rule of law |
| JEL: | C79 D00 D01 D31 K19 K40 K49 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:wzbmbh:301156 |
| By: | Böhm, Robert; Glowacki, Luke; Rusch, Hannes (RS: GSBE UM-BIC, Microeconomics & Public Economics, RS: GSBE other - not theme-related research); Thielmann, Isabel |
| Abstract: | The scale of violent intergroup conflict in humans is astonishingly large compared to other mammals. This capacity for war is closely linked to our exceptionally cooperative abilities. The parochial altruism model formally describes how within-group cooperation and between-group competition could be dynamically intertwined. However, whether this influential model correctly captures the fast-paced processes of preference adaptation in humans has not been systematically scrutinized yet. Here, we develop the psychometric toolkit required for this task and test key assumptions and predictions of the model in groups involved in real intergroup conflicts of varying intensities (total N = 1, 121). Conceptually corroborating the model, we find that our new measures which cleanly separate interindividual altruism from intergroup parochialism characterize individuals’ preferences better than previous metrics and improve behavioral predictions of contributions to conflict. However, our results also show that parochialism varies for different outgroups, a finding that is not anticipated by the model. Thus, the five studies we report here provide new methods for studying individual- and group-level social preferences in the context of intergroup conflict and present new evidence that can inform substantive theoretical improvement. |
| Date: | 2024–08–19 |
| URL: | https://d.repec.org/n?u=RePEc:unm:umagsb:2024009 |
| By: | Uri Gneezy; Yoram Halevy; Brian Hall; Theo Offerman; Jeroen van de Ven |
| Abstract: | Researchers in behavioral and experimental economics often argue that only incentive-compatible mechanisms can elicit effort and truthful responses from participants. Others argue that participants make less-biased decisions when the stakes are sufficiently high. Are these claims correct? We investigate the change in behavior as incentives are scaled up in the Allais paradox, and document an increase , not decrease, in deviations from expected utility with higher stakes. We also find that if one needs to approximate participants’ behavior in real high-stakes Allais (which are often too expensive to conduct), it is better to use hypothetically high stakes than real low stakes, as is typically the practice today. |
| Keywords: | high stakes, real and hypothetical incentives, Allais paradox, Expected Utility |
| JEL: | C91 D81 |
| Date: | 2024–08–17 |
| URL: | https://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-783 |
| By: | Jian-Qiao Zhu; Joshua C. Peterson; Benjamin Enke; Thomas L. Griffiths |
| Abstract: | Understanding how people behave in strategic settings--where they make decisions based on their expectations about the behavior of others--is a long-standing problem in the behavioral sciences. We conduct the largest study to date of strategic decision-making in the context of initial play in two-player matrix games, analyzing over 90, 000 human decisions across more than 2, 400 procedurally generated games that span a much wider space than previous datasets. We show that a deep neural network trained on these data predicts people's choices better than leading theories of strategic behavior, indicating that there is systematic variation that is not explained by those theories. We then modify the network to produce a new, interpretable behavioral model, revealing what the original network learned about people: their ability to optimally respond and their capacity to reason about others are dependent on the complexity of individual games. This context-dependence is critical in explaining deviations from the rational Nash equilibrium, response times, and uncertainty in strategic decisions. More broadly, our results demonstrate how machine learning can be applied beyond prediction to further help generate novel explanations of complex human behavior. |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2408.07865 |
| By: | Samuel Luethi; Stefan C. Wolter |
| Abstract: | This study empirically demonstrates the influence of culturally different values for long-term orientation and patience on the educational progress of migrants in the post-compulsory education system in Switzerland. Using longitudinal PISA data from Switzerland, we show individual differences according to the migrants' country of origin for several outcomes, such as time to graduation, choice of academic education, and entry into tertiary education. Heterogeneity analyses show that this cultural transmission often differs according to the student's position in the achievement distribution and, in some cases, for women and second-generation migrants. |
| Keywords: | Time preference, patience, long-term orientation, educational trajectories |
| JEL: | D91 I21 I23 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:iso:educat:0226 |
| By: | Brian Jabarian |
| Abstract: | In this article, we explore the transformative potential of integrating generative AI, particularly Large Language Models (LLMs), into behavioral and experimental economics to enhance internal validity. By leveraging AI tools, researchers can improve adherence to key exclusion restrictions and in particular ensure the internal validity measures of mental models, which often require human intervention in the incentive mechanism. We present a case study demonstrating how LLMs can enhance experimental design, participant engagement, and the validity of measuring mental models. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.12032 |
| By: | John List |
| Abstract: | This document is meant to introduce my forthcoming book, titled “Experimental Economics: Theory and Practice, †which is to be published in 2025 by The University of Chicago Press. The document first contains the book’s outline followed by a Preface, which summarizes my inspiration for writing the book and my goals and aspirations for choosing the content contained in the book. |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:feb:natura:00792 |