Le Economics and Psychology Seminar est dédié à la recherche en économie comportementale et expérimentale. Il est organisé conjointement par le Centre d’Economie de la Sorbonne (CNRS & Univ. Paris-1) et de Paris School of Economics . Il est ouvert aux spécialistes de divers domaines tels que l’économie, la psychologie, la sociologie, la philosophie et les neurosciences.
Le séminaire a lieu le vendredi de 11h15 à 12h30 à la Maison des Sciences Economiques.
Si vous souhaitez suivre le calendrier du séminaire sur GCal, utilisez le lien suivant.
Les organisateurs sont :
Charlotte Saucet et Leonardo Pejsachowicz
Si vous souhaitez présenter votre article, veuillez contacter Leonardo Pejsachowicz (leonardo.pejsachowicz@univ-paris1.fr).
Lieu du séminaire :
Maison des Sciences Economiques (MSE)
112 Boulevard de l’Hôpital, 75013 Paris
Accès : http://centredeconomiesorbonne.univ-paris1.fr/menu-bas-ces/acces/
Plan : http://goo.gl/maps/rJxRY
Zoom Broadcast :
Les séminaires se tiendront sur place. De plus, nous diffuserons les séminaires via Zoom. Les participants en ligne pourront intervenir via le chat et pendant les questions-réponses à la fin de la conférence. Si vous souhaitez recevoir le lien pour la participation à Zoom, veuillez vous inscrire à la liste de diffusion ci-dessous.
Liste de diffusion :
Pour recevoir des mises à jour sur les conférences, des liens vers la diffusion Zoom, ou pour gérer votre abonnement à la liste de diffusion du séminaire, veuillez utiliser ce lien.
Ce séminaire est soutenu conjointement par l’Université Paris 1 Panthéon Sorbonne, le Centre d’Economie de la Sorbonne et le Paris School of Economics
Ce séminaire est également cofinancé par une subvention du gouvernement français gérée par l’Agence Nationale de la Recherche dans le cadre du programme Investissements d’avenir référence ANR-17-EURE-0001.
Dates d’événements multiples
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The Convergent and External Validity of Risk and Time Preference Elicitation Methods: Controlling for Measurement Error in a Large Population Sample
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We evaluate the convergent and external validity of several commonly used risk and time preference elicitation methods with and without controlling for measurement error using the obviously related instrumental variable (ORIV) approach (Gillen et al., 2019). Preferences are elicited in a large sample of the Dutch population (N = 4,282) and linked to actual and self-reported field behavior in financial, occupational, and Covid-19 related health domains based on register data and survey questions. We find that controlling for measurement error improves the correlation between methods, suggesting that not accounting for measurement error can partly explain the lack of convergent validity among risk and time preference elicitation methods found in previous studies. In addition, we find differences between revealed and stated preference methods in terms of their external validity for risk preferences but not for time preferences. For risk preferences, stated methods correlate well with most types of field behavior and correlations are of economic significance, whereas revealed methods are at best weakly related to field behavior. In contrast, for time preferences both stated and revealed methods correlate well with field behavior. The difference between revealed and stated methods for risk preferences appears not to be driven by the higher complexity of the incentivized tasks. -
Minding the Gap: On the Origins of Probability Weighting and the Description-Experience Gap
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We provide evidence that “noisy coding” is responsible for both (i) classic probability weighting and (ii) its reversal when the properties of lotteries are learned by sampling rather than by explicit description. Guided by a stylized model of noisy sampling, we show that simply forcing experimental subjects to sample redundant information about the primitives of lotteries causes both probability weighting and the description-experience gap to disappear, replaced with broadly neoclassical behavior. This strongly suggests that these anomalies are a joint outgrowth of decision makers’ noisy representations of the primitives of lotteries rather than expressions of true risk preferences
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Co-authors: C.Alos-Ferrer, S. Barberà, D. Coelho High-stakes conflicts between firms and countries are often settled through structured bargaining protocols, for example for the selection of arbitrators. Those protocols are extensive form games with perfect information, and they are judged on the merits of their subgame-perfect equilibria, e.g.efficiency. However, real-life agents often fail to implement backwards induction and exhibit other-regarding preferences. In a large experiment, we compare two prominent protocols and show that those concerns affect outcomes. Bargaining protocols whose equilibria are unfair (in a maximin sense) fare poorly compared to those favoring compromises. However, lengthy protocols are at a disadvantage because they elicit non-equilibrium behavior.
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Leveraging Social Comparisons: The Role of Peer Assignment Policies
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Using a large-scale real effort experiment, we explore whether and how different peer assignment mechanisms affect worker performance and stress. Letting individuals choose whom to compare to, increases productivity to the same extent as a targeted exogenous matching policy designed to maximize motivational spillovers. These effects are significantly larger than those obtained through random assignment and their magnitude is comparable to the impact of an increase in pay of about 10 percent. A downside of targeted peer assignment is that, unlike endogenous peer selection, it leads to a large increase in stress. The key advantage of letting workers choose whom to compare to is that it allows those workers who want to be motivated to compare to a motivating peer while also permitting those for whom social comparisons have little benefits or are too stressful to avoid them. Finally, we show that social comparisons yield stronger motivational effects than comparable non-social goals. Joint work with Jan Schmitz and Christian Zehnder
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Should Individuals Choose Their Own Incentives? Evidence from a Mindfulness Meditation Intervention
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Coauthors: Andrej Woerner, Birgit M. Probst, Nina Bartmann, Jonathan N. Cloughesy, Jan Willem Lindemans. Traditionally, incentives to promote behavioral change are assigned rather than chosen. In this paper, we theoretically and empirically investigate the alternative approach of letting people choose their own incentives from a menu of increasingly challenging and rewarding options. When individuals are heterogeneous and have private information about their costs and benefits, we theoretically show that leaving them the choice of incentives can improve both adherence and welfare. We test the theoretical predictions in a field experiment based on daily meditation sessions. We randomly assign some participants to one of two incentive schemes and allow others to choose between the two schemes. As predicted, participants sort into schemes in (partial) agreement with the objectives of the policymaker. However, in contrast to our prediction, participants who could choose complete significantly fewer sessions than participants that were randomly assigned. Because the results are not driven by poor selection, we infer that letting people choose between incentive schemes may bring in psychological effects that discourage adherence.
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Introspecting influence in choice: accuracy of metacognitive reports in detecting choice bias
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Can we successfully ignore information we deem irrelevant or unreliable? And can we become aware of how such information can bias our choices? The ability to introspect and evaluate the factors influencing our decisions constitutes a key metacognitive function but little is known of the cognitive processes that underlie this ability. In this talk, I will present new studies where we measured participants’ ability to voluntarily ignore information that could bias their choices. Using a computational modelling approach of choice, we demonstrated that irrelevant or unreliable information continued to bias decisions, even when explicitly labelled as such. Participants were able to become aware of some of those biases but did not manage to compensate for them, showing a dissociation between metacognitive knowledge and metacognitive control. -
The effects of time blocking and goal setting on work performance
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We experimentally study the effect of time blocking (dividing a work period into smaller intervals) and non-binding assigned goals on workers performance. While time-blocking increases performance by around 10% overall, goals have no significant effect on average. We find heterogeneous effects depending on a worker’s ability levels. Goal-setting only boosts the performance of high ability workers, but time blocking is equally effective regardless of ability levels. Moreover, for low-ability workers, the combination of time blocking and goal setting results in more mistakes and lower performance. In contrast, high-ability workers’ performance improves under both non-monetary incentive mechanisms. Our findings highlight time blocking as an effective, easy to implement motivational technique that works well for most individuals. On the other hand, the effectiveness of goal setting depends critically on worker’s abilities. Finally, our results caution against combining motivational techniques that might inadvertently hinder performance for low-ability workers.
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How Numbers and Categories Compete in a Complex World
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Real-world news environments comprise both granular quantitative information and coarse categorizations. For instance, company earnings are reported as a dollar figure alongside categorizations, such as whether earnings beat or missed market expectations. When processing capacity is limited, these components may compete for attention. We study the hypothesis that more severe processing constraints increase the relative reliance on coarser signals: people still discriminate between categories but distinguish less granularly within them, creating higher sensitivity around category thresholds but lower sensitivity elsewhere. Using stock market reactions to earnings announcements as our empirical setting, we document that hard-to-value stocks are associated with a more pronounced S-shaped response pattern around category thresholds. Naturalistic experiments that exogenously manipulate processing constraints provide supporting causal evidence. We test two determinants of processing constraints in the field. First, more common sizes of surprise may be processed more precisely. Indeed, regions with more historical mass exhibit far higher return sensitivity and lower medium-term price corrections. Second, a surprise about the category realization may capture attention, leaving less capacity to process the numerical signal. We find that category surprises, e.g., a profit when a loss was expected, are associated with diminished sensitivity to numerical earnings information.
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