nep-cbe New Economics Papers
on Cognitive and Behavioural Economics
Issue of 2024‒07‒15
six papers chosen by



  1. Thoughts about the dictator and trust game By Detemple, Julian
  2. Decision-Making Behavior Evaluation Framework for LLMs under Uncertain Context By Jingru Jia; Zehua Yuan; Junhao Pan; Paul McNamara; Deming Chen
  3. Algorithmic Cooperation By Bernhard Kasberger; Simon Martin; Hans-Theo Normann; Tobias Werner
  4. Guilt and Inequality in Dictator Games By Pierpaolo Battigalli; Giovanni Di Bartolomeo; Stefano Papa
  5. Incorporating Conditional Morality into Economic Decisions By David MASCLET; David L. DICKINSON
  6. Moral Content Diminishes Preference Falsification By Maxine Bonneau; Tanya O'Garra; Praveen Kujal

  1. By: Detemple, Julian
    Abstract: Experiments are an important tool in economic research. However, it is unclear to which extent the control of experiments extends to the perceptions subjects form of such experimental decision situations. This paper is the first to explicitly elicit perceptions of the dictator and trust game and shows that there is substantial heterogeneity in how subjects perceive the same game. Moreover, game perceptions depend not only on the game itself but also on the order of games (i.e., the broader experimental context in which the game is embedded) and the subject herself. This highlights that the control of experiments does not necessarily extend to game perceptions. The paper also demonstrates that perceptions are correlated with game behavior and moderate the relationship between game behavior and field behavior, thereby underscoring the importance and relevance of game perceptions for economic research.
    Keywords: dictator game, trust game, game perceptions
    JEL: C90 D01 D91
    Date: 2024
    URL: https://d.repec.org/n?u=RePEc:zbw:safewp:297999&r=
  2. By: Jingru Jia; Zehua Yuan; Junhao Pan; Paul McNamara; Deming Chen
    Abstract: When making decisions under uncertainty, individuals often deviate from rational behavior, which can be evaluated across three dimensions: risk preference, probability weighting, and loss aversion. Given the widespread use of large language models (LLMs) in decision-making processes, it is crucial to assess whether their behavior aligns with human norms and ethical expectations or exhibits potential biases. Several empirical studies have investigated the rationality and social behavior performance of LLMs, yet their internal decision-making tendencies and capabilities remain inadequately understood. This paper proposes a framework, grounded in behavioral economics, to evaluate the decision-making behaviors of LLMs. Through a multiple-choice-list experiment, we estimate the degree of risk preference, probability weighting, and loss aversion in a context-free setting for three commercial LLMs: ChatGPT-4.0-Turbo, Claude-3-Opus, and Gemini-1.0-pro. Our results reveal that LLMs generally exhibit patterns similar to humans, such as risk aversion and loss aversion, with a tendency to overweight small probabilities. However, there are significant variations in the degree to which these behaviors are expressed across different LLMs. We also explore their behavior when embedded with socio-demographic features, uncovering significant disparities. For instance, when modeled with attributes of sexual minority groups or physical disabilities, Claude-3-Opus displays increased risk aversion, leading to more conservative choices. These findings underscore the need for careful consideration of the ethical implications and potential biases in deploying LLMs in decision-making scenarios. Therefore, this study advocates for developing standards and guidelines to ensure that LLMs operate within ethical boundaries while enhancing their utility in complex decision-making environments.
    Date: 2024–06
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2406.05972&r=
  3. By: Bernhard Kasberger; Simon Martin; Hans-Theo Normann; Tobias Werner
    Abstract: Algorithms play an increasingly important role in economic situations. These situations are often strategic, where the artificial intelligence may or may not be cooperative. We study the deter-minants and forms of algorithmic cooperation in the infinitely repeated prisoner’s dilemma. We run a sequence of computational experiments, accompanied by additional repeated prisoner’s dilemma games played by humans in the lab. We find that the same factors that increase human cooperation largely also determine the cooperation rates of algorithms. However, algorithms tend to play different strategies than humans. Algorithms cooperate less than humans when cooperation is very risky or not incentive-compatible.
    Keywords: artificial intelligence, cooperation, large language models, Q-learning, repeated prisoner’s dilemma
    JEL: C72 C73 C92 D83
    Date: 2024
    URL: https://d.repec.org/n?u=RePEc:ces:ceswps:_11124&r=
  4. By: Pierpaolo Battigalli; Giovanni Di Bartolomeo; Stefano Papa
    Abstract: We examine the interplay between guilt aversion and inequality in decision-making, speci…cally in the context of a dictator game. Considering different initial allocations of the surplus, we investigate how the material opportunity cost of reducing inequality in‡uences sharing behavior, revealing complex relationship among guilt-driven choices and opportunity costs.
    Keywords: guilt aversion; psychological games; dictator games; second-order beliefs
    JEL: A13 C91 D01 D64
    Date: 2024–06
    URL: https://d.repec.org/n?u=RePEc:sap:wpaper:wp252&r=
  5. By: David MASCLET (Univ Rennes, CNRS, CREM – UMR6211, F-35000 Rennes France and CIRANO, Montreal, Canada); David L. DICKINSON (Appalachian State University, IZA, ESI)
    Abstract: We present a theoretical framework of individual-decision making that incorporates both moral motivations and social influence into the utility function. The main idea of the paper is that individuals face a trade-off between their material individual interests and their desire to follow moral obligation. In our model, we assume that moral motivation is weak or conditional in the sense that it may be influenced by others’ actions. Specifically, in our framework one’s moral obligation is a combination of two main components: an autonomous component and a social component that captures the influence of others. Our theoretical framework is able to explain many stylized results commonly observed in the literature and suggests a different mechanism to explain economic behavior.
    Keywords: Behavioral Economics, Ethical Decision Making, Fairness
    JEL: C9 D9 D91
    Date: 2024–06
    URL: https://d.repec.org/n?u=RePEc:tut:cremwp:2024-04&r=
  6. By: Maxine Bonneau (Imperial College London); Tanya O'Garra (Imperial College London); Praveen Kujal (Middlesex University Business School and Chapman University)
    Abstract: We examine how the moral (or neutral) content of an issue influences the tendency to falsify attitudes, given varying social and monetary incentives to engage in such ‘preference falsification’. We conduct an incentivized two stage online experimental study where, in a prior first stage, attitude strength over moral and neutral issues is elicited. Then, in the second stage participants in groups of ten were asked to express their preferences regarding the moral or neutral issues for each possible combination of supporters and opposers in their group, each associated with varying monetary payoffs. More than half of the participants falsify their preferences between the two phases for both moral and neutral frames. The rate is significantly lower for the moral (vs neutral) issues. Participants’ average monetary cost to avoid falsifying preferences is higher in moral treatments, and increases with the level of attitude strength.
    Keywords: Morality, preference falsification, incentives
    JEL: C9 C90 C92 D02 D7 D74
    Date: 2024
    URL: https://d.repec.org/n?u=RePEc:chu:wpaper:24-11&r=

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