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on Evolutionary Economics |
| By: | Aurel Stenzel; Johannes Lohse; Till Requate; Israel Waichman |
| Abstract: | We characterize 'Games of Altruistic Cooperation' as a class of games in which cooperation leaves the individual and the group of decision-makers worse off than defection, but favors individuals outside the group. An example is climate change mitigation. In this context, we experimentally investigate whether decentralized institutions using costly punishment and/or communication support altruistic cooperation to sustain the welfare of future generations. Without punishment or communication, cooperation is low; communication alone even increases the incidence of zero contributions. However, combining peer punishment with communication strongly increases cooperation, showing that an effective decentralized solution to a Game of Altruistic Cooperation exists. |
| Keywords: | games of altruistic cooperation, social dilemma, intergenerational good game, punishment, communication |
| JEL: | C92 D74 H41 Q54 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11880 |
| By: | Francesco Cozzi; Marco Pangallo; Alan Perotti; Andr\'e Panisson; Corrado Monti |
| Abstract: | Agent-Based Models (ABMs) are powerful tools for studying emergent properties in complex systems. In ABMs, agent behaviors are governed by local interactions and stochastic rules. However, these rules are, in general, non-differentiable, limiting the use of gradient-based methods for optimization, and thus integration with real-world data. We propose a novel framework to learn a differentiable surrogate of any ABM by observing its generated data. Our method combines diffusion models to capture behavioral stochasticity and graph neural networks to model agent interactions. Distinct from prior surrogate approaches, our method introduces a fundamental shift: rather than approximating system-level outputs, it models individual agent behavior directly, preserving the decentralized, bottom-up dynamics that define ABMs. We validate our approach on two ABMs (Schelling's segregation model and a Predator-Prey ecosystem) showing that it replicates individual-level patterns and accurately forecasts emergent dynamics beyond training. Our results demonstrate the potential of combining diffusion models and graph learning for data-driven ABM simulation. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.21426 |
| By: | David K Levine |
| Date: | 2025–06–18 |
| URL: | https://d.repec.org/n?u=RePEc:cla:levarc:735347000000000007 |
| By: | Ignacio Esponda; Demian Pouzo |
| Abstract: | We introduce Berk--Nash rationalizability, a new solution concept for misspecified learning environments. It parallels rationalizability in games and captures all actions that are optimal given beliefs formed using the model that best fits the data in the agent's misspecified model class. Our main result shows that, with probability one, every \emph{limit action} -- any action played or approached infinitely often -- is Berk--Nash rationalizable. This holds regardless of whether behavior converges. We apply the concept to known examples and identify classes of environments where it is easily characterized. The framework provides a general tool for bounding long-run behavior without assuming convergence to a Berk--Nash equilibrium. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.20708 |
| By: | Roberto Galbiati (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique); Emeric Henry (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique); Nicolas Jacquemet (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | What actions other people judge appropriate drives pro-social behavior. We show that such judgments depend on whether the observers previously faced the situation they judge (active observers) or not (passive observers). In an online giving experiment, active observers make more polarized judgments than passive ones -those who acted pro-socially judge selfish behavior more harshly and praise pro-social actions more. Moreover, active observers persistently avoid payoff-relevant information, both as dictators, likely to maintain their self-image, and then as observers. Our results imply a new link between descriptive (what most people do) and injunctive norms (what groups deem appropriate). |
| Keywords: | Observers, Injunctive norms, Descriptive norms, Polarization, Observers Injunctive norms Descriptive norms Polarization |
| Date: | 2025–06–16 |
| URL: | https://d.repec.org/n?u=RePEc:hal:cesptp:halshs-05115226 |