nep-cbe New Economics Papers
on Cognitive and Behavioural Economics
Issue of 2022‒11‒14
five papers chosen by
Marco Novarese
Università degli Studi del Piemonte Orientale

  1. When Do Reminders Work? Memory Constraints and Medical Adherence By Kai Barron; Mette Trier Damgaard; Christina Gravert
  2. Artificial Intelligence, Ethics, and Intergenerational Responsibility By Victor Klockmann; Alicia von Schenk; Marie Claire Villeval
  3. Rationalizing Decision Choices: What Influences our Social Decision Making? By Chatterjee, Sidharta
  4. Human Behavioral Models Using Utility Theory and Prospect Theory By Anuradha M. Annaswamy; Vineet Jagadeesan Nair
  5. The Predictive Power of Luck: Luck and Risk-Taking in a Repeated Risky Investment Game By Holden, Stein T.; Tione, Sarah; Katengeza, Samson; Tilahun, Mesfin

  1. By: Kai Barron; Mette Trier Damgaard; Christina Gravert
    Abstract: An extensive literature shows that reminders can successfully change behavior. Yet, there exists substantial unexplained heterogeneity in their effectiveness, both: (i) across studies, and (ii) across individuals within a particular study. This paper investigates when and why re-minders work. We develop a theoretical model that highlights three key mechanisms through which reminders may operate. To test the predictions of the model, we run a nationwide field experiment on medical adherence with over 4000 pregnant women in South Africa and document several key results. First, we find an extremely strong baseline demand for reminders. This demand increases after exposure to reminders, suggesting that individuals learn how valuable they are for freeing up memory resources. Second, stated adherence is increased by pure reminders and reminders containing a moral suasion component, but interestingly, reminders containing health information reduce adherence in our setting. Using a structural model, we show that heterogeneity in memory costs (or, equivalently, annoyance costs) is crucial for explaining the observed behavior.
    Keywords: nudging, reminders, memory, attention, medication adherence, structural model
    JEL: D04 D91 C93 I12
    Date: 2022
    URL: http://d.repec.org/n?u=RePEc:ces:ceswps:_9996&r=cbe
  2. By: Victor Klockmann (Goethe-University Frankfurt am Main, University of Würzburg = Universität Würzburg , Max Planck Institute for Human Development - Max-Planck-Gesellschaft); Alicia von Schenk (Goethe-University Frankfurt am Main, University of Würzburg = Universität Würzburg , Max Planck Institute for Human Development - Max-Planck-Gesellschaft); Marie Claire Villeval (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - Université de Lyon - CNRS - Centre National de la Recherche Scientifique)
    Abstract: In the future, artificially intelligent algorithms will make more and more decisions on behalf of humans that involve humans' social preferences. They can learn these preferences through the repeated observation of human behavior in social encounters. In such a context, do individuals adjust the selfishness or prosociality of their behavior when it is common knowledge that their actions produce various externalities through the training of an algorithm? In an online experiment, we let participants' choices in dictator games train an algorithm. Thereby, they create an externality on future decision making of an intelligent system that affects future participants. We show that individuals who are aware of the consequences of their training on the payoffs of a future generation behave more prosocially, but only when they bear the risk of being harmed themselves by future algorithmic choices. In that case, the externality of artificially intelligence training increases the share of egalitarian decisions in the present.
    Keywords: Artificial Intelligence,Morality,Prosociality,Generations,Externalities
    Date: 2022
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-03778525&r=cbe
  3. By: Chatterjee, Sidharta
    Abstract: The goal of this paper is to examine and analyze how certain factors influence our social decision making process. I undertake an investigative study into the dynamics of rational choice theory which is behind making decisions rationally productive. The research touches on the foundational concepts of Social Choice Rationality—the theory that is grounded on searching and making choices socially rational for the decision maker. The welfare functional component of social choice theory underlying rational decision making have been examined, and new knowledge have been derived from the analysis that could be helpful for making collective decisions which concern public policy and social welfare.
    Keywords: Decision choice, rational choice theory, rational intelligence, social choice theory, social choice rationality.
    JEL: I3 I30 I31
    Date: 2022–10–16
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:114985&r=cbe
  4. By: Anuradha M. Annaswamy; Vineet Jagadeesan Nair
    Abstract: Several examples of Cyber-physical human systems (CPHS) include real-time decisions from humans as a necessary building block for the successful performance of the overall system. Many of these decision-making problems necessitate an appropriate model of human behavior. Tools from Utility Theory have been used successfully in several problems in transportation for resource allocation and balance of supply and demand \citep{ben1985discrete}. More recently, Prospect Theory has been demonstrated as a useful tool in behavioral economics and cognitive psychology for deriving human behavioral models that characterize their subjective decision-making in the presence of stochastic uncertainties and risks, as an alternative to conventional Utility Theory \citep{kahneman_prospect_2012}. These models will be described in this article. Theoretical implications of Prospect Theory are also discussed. Examples will be drawn from transportation use cases such as shared mobility to illustrate these models as well as the distinctions between Utility Theory and Prospect Theory.
    Date: 2022–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2210.07322&r=cbe
  5. By: Holden, Stein T. (Centre for Land Tenure Studies, Norwegian University of Life Sciences); Tione, Sarah (Centre for Land Tenure Studies, Norwegian University of Life Sciences); Katengeza, Samson (Centre for Land Tenure Studies, Norwegian University of Life Sciences); Tilahun, Mesfin (Centre for Land Tenure Studies, Norwegian University of Life Sciences)
    Abstract: Can luck predict risk-taking behavior in games of chance? Economists have not widely studied this issue although overconfidence, optimism-, and pessimism bias have received substantial attention in recent years. In this study, we investigate how good and bad luck outcomes in a simple repeated risky investment game affect risk-taking behavior in the following rounds of the same game where the outcome (luck) in the game is determined by the throwing of a die after each round. The outcome of the previous round's die-throw is known when the subjects decide how risky their next choice in the game will be. A sample of 718 university students is used as subjects in the game in a recursive within-subject design. The results demonstrate a strong impact of luck on risk-taking behavior that lasts not only to the next round but also into another two follow-up rounds, with cumulative effects. A time delay of 1-2 months between Round 1 and Round 2 did not wipe out the luck effect and it was only slightly weaker than the luck effect from Round 2 to Rounds 3 and 4 that followed immediately after Round 2. Many recent studies have shown that risk preferences respond to recent shocks. This study indicates that random shocks such as luck in previous games (states of nature) influence risk-taking behavior. Our study suggests that the causal mechanism goes through subjective beliefs in luck based on past experiences that influence expectations and thereby risk-taking behavior.
    Keywords: Risky investment game; Luck; Illusion of control; Repeated game; Predictive power.
    JEL: D80 H51
    Date: 2022–10–29
    URL: http://d.repec.org/n?u=RePEc:hhs:nlsclt:2022_009&r=cbe

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