Economics serving society

Research Activities

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Economics and Psychology seminar - dedicated page

Behavior seminar - dedicated page

Behavior Work Group - dedicated page

Lunch Seminar TOM (Theory, Organisation and Markets) - dedicated page

nEuro-economics seminar - dedicated page

Working papers, 2019-2021

  • Béatrice Boulu-Reshef & Nina Rapoport, 2020. “Voluntary contributions in cascades: The tragedy of ill-informed leadership,” Documents de travail du Centre d’Economie de la Sorbonne 20023, Université Panthéon-Sorbonne (Paris 1)
  • Béatrice Boulu-Reshef & Jonah Schulhofer-Wohl, 2019. “Social Distance and Parochial Altruism: An Experimental Study,” Working Papers hal-02135633, HAL.
  • Boissonnet, Niels & Ghersengorin, Alexis & Gleyze, Simon, 2020. “Revealed Deliberate Preference Changes,” MPRA Paper 101756, University Library of Munich, Germany.
  • Galbiati, Roberto & Henry, Emeric & Jacquemet, Nicolas & Lobeck, Max, 2020. “How Laws Affect the Perception of Norms: Empirical Evidence from the Lockdown,” CEPR Discussion Papers 15119, C.E.P.R. Discussion Papers.
  • Nicolas Jacquemet & Stéphane Luchini & Jason F. Shogren & Verity Watson, 2019. “Discrete Choice under Oaths,” Documents de travail du Centre d’Economie de la Sorbonne 19007, Université Panthéon-Sorbonne (Paris 1), Centre d’Economie de la Sorbonne.
  • Roberto Galbiati & Emeric Henry & Nicolas Jacquemet, 2019. “Learning to cooperate in the shadow of the law,” Sciences Po publications 2019-06, Sciences Po.
  • Philippe Jehiel, 2021. “Communication with forgetful liars,” Post-Print halshs-03229984, HAL.
  • Roberta de Filippis & Antonio Guarino & Philippe Jehiel & Toru Kitagawa, 2021. “Non-Bayesian updating in a social learning experiment,” PSE-Ecole d’économie de Paris (Postprint) halshs-03229978, HAL.
  • David Ettinger & Philippe Jehiel, 2020. “An experiment on deception, reputation and trust,” Post-Print hal-03105728, HAL.
  • Philippe Jehiel, 2019. “Robust Mechanism Design: An Analogy-Based Expectation Equilibrium Perspective,” Post-Print halshs-02491939, HAL.
  • Milo Bianchi & Philippe Jehiel, 2019. “Bundling, Belief Dispersion, and Mispricing in Financial Markets,” PSE Working Papers halshs-02183306, HAL.
  • Bianchi, Milo & Jehiel, Philippe, 2019. “Bundlers Dilemmas in Financial Markets with Sampling Investors,” TSE Working Papers 19-1042, Toulouse School of Economics (TSE).
  • Philippe Jehiel & Juni Singh, 2019. “Multi-state choices with aggregate feedback on unfamiliar alternatives,” PSE Working Papers halshs-02183444, HAL.
  • Barron, Kai & Huck, Steffen & Jehiel, Philippe, 2019. “Everyday econometricians: Selection neglect and overoptimism when learning from others,” Discussion Papers, Research Unit: Economics of Change SP II 2019-301, WZB Berlin Social Science Center.
  • Jeanne Hagenbach & Frédéric Koessler, 2021. “Selective Memory of a Psychological Agent,” Working Papers halshs-03151009, HAL.
  • Hagenbach, Jeanne & Koessler, Frédéric, 2019. “Partial Language Competence,” CEPR Discussion Papers 13488, C.E.P.R. Discussion Papers.
  • Philipp Harfst & Damien Bol & Jean-François Laslier, 2021. “Designing Preference Voting,” PSE-Ecole d’économie de Paris (Postprint) halshs-03033239, HAL.
  • Louis-Gaëtan Giraudet & Bénédicte Apouey & Hazem Arab & Simon Baeckelandt & Philippe Begout & Nicolas Berghmans & Nathalie Blanc & Jean-Yves Boulin & Eric Buge & Dimitri Courant & Amy Dahan & Adrien F, 2021. “Deliberating on Climate Action: Insights from the French Citizens’ Convention for Climate,” Working Papers hal-03119539, HAL.
  • Jean-François Laslier, 2020. “Do Kantians drive others to extinction?,” PSE Working Papers halshs-02652020, HAL.
  • Luc Arrondel & Richard Duhautois & Jean-François Laslier, 2020. “Existe-t-il un avantage à commencer la séance de tirs au but au football ?,” PSE-Ecole d’économie de Paris (Postprint) hal-03095074, HAL.
  • Alger, Ingela & Laslier, Jean-François, 2020. “Homo moralis goes to the voting booth: coordination and information aggregation,” IAST Working Papers 20-118, Institute for Advanced Study in Toulouse (IAST).
  • Jean-François Laslier, 2019. “Experiments on the Reaction of Citizens to New Voting Rules: A Survey,” Post-Print halshs-02088107, HAL.
  • Hoven M, De Boer N, Goudriaan A, Denys D, van Holst R*, Luigjes J* & Lebreton M* (2020). How motivational signals disrupt metacognitive signals in the human VMPFC. bioRxiv [pdf]
  • Engelmann JB*, Lebreton M*, Schwardman P*, & Van de Weele J* & Chang LA. (2019) Anticipatory Anxiety and Wishful Thinking. Tinbergen working paper
  • Negrini, M., Riedl, A. & Wibral, M. (2020) “Still in search of the sunk cost bias”. Maastricht University, Graduate School of Business and Economics, 53 p. (GSBE Research Memoranda; No. 028).
  • Marieke Pahlke (2019) Dynamic Consistency in Incomplete Information Games with Multiple Priors
  • Marieke Pahlke (2019) Dynamic Consistency in Ambiguous Persuasion
  • Béatrice Boulu-Reshef & Nina Rapoport, 2020. “Voluntary contributions in cascades: The tragedy of ill-informed leadership,” Documents de travail du Centre d’Economie de la Sorbonne 20023, Université Panthéon-Sorbonne (Paris 1), Centre d’Economie de la Sorbonne.

Published academic articles, 2017-2021

  • Béatrice Boulu-Reshef & Constance Monnier-Schlumberger, 2019. “Lutte contre les cartels : comment dissuader les têtes brûlées ?,” Revue économique, Presses de Sciences-Po, vol. 70(6), pages 1187-1199.
  • Béatrice Boulu-Reshef & Samuel H. Brott & Adam Zylbersztejn, 2017. “Does Uncertainty Deter Provision of Public Goods?,” Revue économique, Presses de Sciences-Po, vol. 68(5), pages 785-791.
  • Béatrice Boulu-Reshef, Béatrice & Comeig, Irene & Donze, Robert & Weiss, Gregory D., 2016. “Risk aversion in prediction markets: A framed-field experiment,” Journal of Business Research, Elsevier, vol. 69(11), pages 5071-5075.
  • B Garcia, F Cerrotti, S Palminteri, 2021. “The description–experience gap: a challenge for the neuroeconomics of decision-making under uncertainty,” Philosophical Transactions of the Royal Society, B 376 (1819), 20190665 8 2021.
  • A Nioche, B Garcia, T Boraud, N Rougier, S Bourgeois-Gironde (2019).“Interaction effects between consumer information and firms’ decision rules in a duopoly: how cognitive features can impact market dynamics”, Palgrave Communications 5 (1), 1-11
  • Nicolas Jacquemet & Alexander G James & Stéphane Luchini & James J Murphy & Jason F Shogren, 2021. “Do truth-telling oaths improve honesty in crowd-working?,” PLOS ONE, Public Library of Science, vol. 16(1), pages 1-18, January.
  • Jacquemet, N. & Luchini, S. & Malézieux, A. & Shogren, J.F., 2020. “Who’ll stop lying under oath? Empirical evidence from tax evasion games,” European Economic Review, Elsevier, vol. 124(C).
  • Jacquemet Nicolas & Luchini Stéphane & Malézieux Antoine & Shogren Jason F., 2019. “A Psychometric Investigation of the Personality Traits Underlying Individual Tax Morale,” The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 19(3), pages 1-25, July.
  • Nicolas Jacquemet & Stéphane Luchini & Julie Rosaz & Jason F. Shogren, 2019. “Truth Telling Under Oath,” Management Science, INFORMS, vol. 65(1), pages 426-438, January.
  • Roberto Galbiati & Emeric Henry & Nicolas Jacquemet, 2018. “Dynamic effects of enforcement on cooperation,” Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(49), pages 12425-12428, December.
  • Nicolas Jacquemet & Stéphane Luchini & Jason F. Shogren & Adam Zylbersztejn, 2018. “Coordination with communication under oath,” Experimental Economics, Springer;Economic Science Association, vol. 21(3), pages 627-649, September.
  • Nicolas Jacquemet & Fabrice Le Lec, 2017. “Développements récents de l’économie comportementale et expérimentale. Introduction,” Revue économique, Presses de Sciences-Po, vol. 68(5), pages 719-725.
  • Nicolas Jacquemet & Stéphane Luchini & Antoine Malézieux & Jason F. Shogren, 2017. “L’évasion fiscale est-elle un trait de personnalité ?. Une évaluation empirique des déterminants psychologiques de la « morale fiscale »,” Revue économique, Presses de Sciences-Po, vol. 68(5), pages 809-828.
  • Nicolas Jacquemet & Alexander James & Stéphane Luchini & Jason F. Shogren, 2017. “Referenda Under Oath,” Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(3), pages 479-504, July.
  • Youenn Lohéac & Alia Hayyan & Cécile Bazart & Mohamed Ali Bchir & Serge Blondel & Mihaela Bonescu & Alexandrine Bornier & Joëlle Brouard & Nathalie Chappe & François Cochard & Alexandre Flage & Fabio , 2017. “Mise en place d’une expérience avec le grand public : entre recherche, vulgarisation et pédagogie,” Revue économique, Presses de Sciences-Po, vol. 68(5), pages 941-953.
  • Philippe Jehiel & Jakub Steiner, 2020. “Selective Sampling with Information-Storage Constraints [On interim rationality, belief formation and learning in decision problems with bounded memory],” Economic Journal, Royal Economic Society, vol. 130(630), pages 1753-1781.
  • Philippe Jehiel, 2018. “Investment Strategy and Selection Bias: An Equilibrium Perspective on Overoptimism,” American Economic Review, American Economic Association, vol. 108(6), pages 1582-1597, June.
  • Jouxtel, Justine, 2019. “Voluntary contributions of time: Time-based incentives in a linear public goods game,” Journal of Economic Psychology, Elsevier, vol. 75(PA).
  • Hagenbach, Jeanne & Koessler, Frédéric, 2020. “Cheap talk with coarse understanding,” Games and Economic Behavior, Elsevier, vol. 124(C), pages 105-121.
  • Koessler, Frederic & Skreta, Vasiliki, 2019. “Selling with evidence,” Theoretical Economics, Econometric Society, vol. 14(2), May.
  • Hagenbach, Jeanne & Koessler, Frédéric, 2017. “The Streisand effect: Signaling and partial sophistication,” Journal of Economic Behavior & Organization, Elsevier, vol. 143(C), pages 1-8.
  • Jeanne Hagenbach & Frédéric Koessler, 2017. “Simple versus rich language in disclosure games,” Review of Economic Design, Springer;Society for Economic Design, vol. 21(3), pages 163-175, September.
  • Mehdi Ayouni & Frédéric Koessler, 2017. “Hard evidence and ambiguity aversion,” Theory and Decision, Springer, vol. 82(3), pages 327-339, March.
  • Arrondel, Luc & Duhautois, Richard & Laslier, Jean-François, 2019. “Decision under psychological pressure: The shooter’s anxiety at the penalty kick,” Journal of Economic Psychology, Elsevier, vol. 70(C), pages 22-35.
  • Baujard, Antoinette & Gavrel, Frédéric & Igersheim, Herrade & Laslier, Jean-François & Lebon, Isabelle, 2018. “How voters use grade scales in evaluative voting,” European Journal of Political Economy, Elsevier, vol. 55(C), pages 14-28.
  • Damien Bol & André Blais & Jean-François Laslier, 2018. “A mixed-utility theory of vote choice regret,” Public Choice, Springer, vol. 176(3), pages 461-478, September.
  • Casella, Alessandra & Laslier, Jean-François & Macé, Antonin, 2017. “Democracy for Polarized Committees: The Tale of Blotto’s Lieutenants,” Games and Economic Behavior, Elsevier, vol. 106(C), pages 239-259.
  • Isabelle Lebon & Antoinette Baujard & Frédéric Gavrel & Herrade Igersheim & Jean-François Laslier, 2017. “Ce que le vote par approbation révèle des préférences des électeurs français,” Revue économique, Presses de Sciences-Po, vol. 68(6), pages 1063-1076.
  • Laslier, Jean-François & Núñez, Matías, 2017. “Pivots et élections,” L’Actualité Economique, Société Canadienne de Science Economique, vol. 93(1-2), pages 79-111, Mars-Juin.
  • Ting CC, Palminteri S, Lebreton M* & Engelmann JB* (2021). The elusive effects of anxiety on reinforcement learning. JEP: LM&C, in press [pdf]
  • Ting CC, Palminteri S, Engelmann JB* & Lebreton M* (2020) Robust valence-induced biases on motor response and confidence in human reinforcement learning. Cogn. Aff. Behav. Neuro, 20(6), 1184-1199 [pdf] [code and data]
  • Couto J, van Maanen L**, Lebreton M**. Investigating the origin and consequences of endogenous default options in repeated economic choices (2020) PLoS ONE, 15(8):e023238 [pdf] [code and data]
  • Rojek-Giffin M, Lebreton M, Scholte SH, van Winden F, Ridderinkhof KR, De Dreu CKW (2020) Neurocognitive Underpinnings of Aggressive Predation in Economic Contests. Journal of Cognitive Neuroscience 32 (7), 1276-1288 [pdf] [code and data] [fMRIdata]
  • Rhanev D, (…), Lebreton M, (…) et al. (2020) A database of confidence studies. Nature Human Behavior 4 (3), 317-325 [pdf] [code and data]
  • Hoven H, Lebreton M, Engelmann JB, Denys D, Luigjes J & van Holst R (2019) Abnormalities of confidence in psychiatry: an overview and future perspectives. Translational Psychiatry 9(1), 1–18. [pdf]
  • Lebreton M, Bavard S, Daunizeau J & Palminteri S. (2019) Assessing inter-individual differences with task-related functional neuroimaging. Nature Human Behavior 3(9), 897–905. [pdf]
  • Fontanesi L, Lebreton M* and Palminteri S* (2019). Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: A meta-analytical approach using diffusion decision modeling. Cogn. Aff. Behav. Neuro. 19(3), 490-502. [pdf] [code and data]
  • Lebreton M, Bacily K, Palminteri S & JB Engelmann (2019). Contextual influence on confidence judgments in human reinforcement learning. PLoS Computational Biology, 15(4): e1006973 [pdf] [code and data] [press release]
  • Karlsson Linnér R, Biroli P, Kong E, Meddens FW, Wedow R, Fontana MA, Lebreton M, (…) et al. (2019) . GWAS of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and reveal shared genetic influences. Nature Genetics, 51:245–257 [pdf] [data]
  • Correa CMC, Noorman S, Jiang J, Palminteri S, Cohen MX, Lebreton M*, van Gaal S* (2018). How the level of reward awareness changes the computational and electrophysiological signatures of reinforcement learning. Journal of Neuroscience, 38(48):10338 –10348 [pdf] [code and data]
  • Bavard S*, Lebreton M*, Khamassi M, Coricelli G, & Palminteri S. (2018). Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences. Nature Communications. 9 (4503) [pdf] [code and data]
  • Lebreton M, Langdon S, Slieker MJ, Nooitgedacht JS, Goudriaan AE, Denys D, Luigjes J*, van Holst RJ* (2018). Two sides of the same coin: monetary incentives concurrently improve and bias confidence judgments. Science Advances. 4, eaaq0668 [pdf] [code and data] [press release]
  • Lefebvre G, Lebreton M, Meyniel F, Bourgeois-Gironde S and Palminteri S. (2017) Behavioural and neural characterization of optimistic reinforcement learning. Nature Human Behaviour. 1, 0067 (2017). [pdf] [code and data] [fMRI data]
  • Negrini, M., Brkic, D., Pizzamiglio, S., Premoli, I. & Rivolta, D., Neurophysiological Correlates of Featural and Spacing Processing for Face and Non-face Stimuli, 13 Mar 2017, In: Frontiers in Psychology. 8, 9 p., 333
  • Johann Lussange & Ivan Lazarevich & Sacha Bourgeois-Gironde & Stefano Palminteri & Boris Gutkin, 2021. “Modelling Stock Markets by Multi-agent Reinforcement Learning,” Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 113-147, January.
  • Germain Lefebvre & Aurélien Nioche & Sacha Bourgeois-Gironde & Stefano Palminteri, 2018. “Contrasting temporal difference and opportunity cost reinforcement learning in an empirical money-emergence paradigm,” Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(49), pages 11446-11454, December.
  • Antoine Billot & Sujoy Mukerji & Jean-Marc Tallon, 2020. “Market Allocations under Ambiguity: A Survey,” Revue économique, Presses de Sciences-Po, vol. 71(2), pages 267-282.
  • Milo Bianchi & Jean-Marc Tallon, 2019. “Ambiguity Preferences and Portfolio Choices: Evidence from the Field,” Management Science, INFORMS, vol. 65(4), pages 1486-1501, April.
  • Fabrice Collard & Sujoy Mukerji & Kevin Sheppard & Jean‐Marc Tallon, 2018. “Ambiguity and the historical equity premium,” Quantitative Economics, Econometric Society, vol. 9(2), pages 945-993, July.
  • Jeleva, Meglena & Tallon, Jean-Marc, 2016. “Ambiguïté, comportements et marchés financiers,” L’Actualité Economique, Société Canadienne de Science Economique, vol. 92(1-2), pages 351-383, Mars-Juin.
  • Eric Danan & Thibault Gajdos & Brian Hill & Jean-Marc Tallon, 2016. “Robust Social Decisions,” American Economic Review, American Economic Association, vol. 106(9), pages 2407-2425, September.
  • Schoeller, F., Zenasni, F., Bertrand, P., Gerry, L. J., Jain, A., & Horowitz, A. H. (2019). Combining virtual reality and biofeedback to foster empathic abilities in humans. Frontiers in psychology, 9, 2741.
  • Botella, M., Nelson, J., & Zenasni, F. (2019). It is time to observe the creative process: How to use a creative process report diary (CRD). The Journal of Creative Behavior, 53(2), 211-221.
  • Brunet-Gouet, E., Myszkowski, N., Ehrminger, M., URBACH, M., Aouizerate, B., Brunel, L., … Zenasni, F & Fond, G. B. (2019). Confirmation of a two-factor solution to the Questionnaire of Cognitive and Affective Empathy (QCAE) in a French population of patients with schizophrenia spectrum disorders. Frontiers in Psychiatry, 10, 751.
  • Hodzic, S., Scharfen, J, Ripoll, P, Holling, H., Zenasni, F. (2018). How efficient are emotional intelligence trainings: A meta-analysis? Emotion Review, 10(2), 138-148.
  • Robieux, L., Zenasni, F., Flahault, C., & Tavani, J. L. (2018). L’espoir dans la maladie chronique : représentations sociales de l’espoir chez les patients et soignants. Psychologie Française, 63(1), 37-50.
  • Bertrand, P., Guegan, J., Robieux, L., McCall, C. A., & Zenasni, F. (2018). Learning empathy through virtual reality: Multiple strategies for training empathy-related abilities using body ownership Illusions in embodied virtual reality. Frontiers in Robotics and AI, 5, 26.
  • Myszkowski, N., Brunet-Gouet, E., Roux, P., Robieux, L., Malézieux, A., Boujut, E., & Zenasni, F. (2017). Is the Questionnaire of Cognitive and Affective Empathy measuring two or five dimensions? Evidence in a French sample. Psychiatry Research 255, 292-296.,.
  • Pène, S., Bihanic, D., Zenasni, F., Le Bœuf, J. & Vial, S. (2017). Éditorial. Sciences du Design, 6,(2), 8-11.
  • Liang, C.T., Zenasni, F., Liu, Y.C., Liang C (2017). The role of intrinsic motivation in student imagination: A comparison between Engineering and Science majors. International Journal of. Engineering Education, 33(5), 1672-1683
  • Myszkowski, N., Villoing, B., Zenasni, F., Jaury, P., Boujut, E. (2017). Monitoring stress among internal medicine residents: An experience-driven, practical and short measure. Psychology Health and Medicine, 22(6), 719-726.
  • Lec, F., Alexopoulos, T., Boulu-Reshef, B., Fayant, M., Zenasni, F., Lubart, T., & Jacquemet, N. (2017). The outof-my-league effect. Behavioral and Brain Sciences, 40. doi:10.1017/S0140525X16000534


Mai 2021 « Économie comportementale des politiques publiques »
Yannick Gabuthy, Nicolas Jacquemet* et Olivier L’Haridon
Editions La découverte (collection Repères)

Juin 2020 « Comment lutter contre la fraude fiscale ? Les enseignements de l’économie comportementale »
Nicolas Jacquemet*, Stéphane Luchini et Antoine Malézieux
Éditions rue d’Ulm

Août 2019 « Précis d’économie expérimentale »
Fabrice Le Lec, Nicolas Jacquemet* et Olivier L’Haridon

Mai 2019 « Voter autrement »
Jean-François Laslier*
Cepremap, Éditions Rue d’Ulm

Novembre 2018 « Experimental Economics - Method and Applications »
Nicolas Jacquemet* et Olivier L’Haridon
Cambridge University Press

Research Projects

Characterizing information integration in reinforcement learning: a neuro-computational investigation

  • 2021-2026 [INFORL GA: 948671]
  • Funding: ERC, StG-2020 call
  • PI: Mael Lebreton

Most of our beliefs, habits and behavioral strategies unfold from learning, by trial and errors, to select options that maximize the occurrence of rewards, and minimize the occurrence of punishments – a process known as reinforcement-learning (RL). While the behavioural, computational and neurobiological features of learning from singular experienced outcomes have been extensively studied, the mechanisms by which RL could leverage multiple, concurrent information samples – including abstract information about prospective outcomes – have been largely overlooked. As a consequence, and although these processes likely critically contribute to shaping our behaviour, little is known about how we prioritize, filter or value outcome information in RL. This project will address this gap, and assess how humans learn from multiple concurrent information samples. We will notably focus on how (neuro)computational limitations and affective biases curb information integration and impedes learning performances. By investigating an overlooked aspect of reinforcement learning –the integration of available information–, this project could not only help refine computational and neurobiological models of the learning process, but also shed new lights on maladaptive traits of human behaviour in social and clinical contexts

Learning in strategic environments under various feedback

  • 2020-2022 [LSE-Feed]
  • Funding agency: CNRS, 80|Prime call.
  • PI : Jean-Marc Tallon, Stefano Palminteri, Valérian Chambon.

This project seeks to combine the neuroscience and the economic approaches to study how humans behave in strategic environments. Crucial to any such interaction is a notion of beliefs of the agents over the payoffs of playing a certain strategy, and how these payoffs can be learned. This can take the form of predicting the behavior of other players or directly predicting the reward of each action. Economics has developed different models of learning in repeated games. In more general environments, agents could also form their expectations by bundling data that come from multiple situations and reason as if the coarse statistics so obtained could safely be used to describe each situation accurately. Recent advances in neuroeconomics suggest different neural and behavioral channels for positive and negative values update. The project will look for ways to intertwine these aspects of learning from a theoretical, computational, and experimental perspective.

Ambiguity in Dynamic Environments

  • 2018 -2022 [AmbDyn]
  • Funding: ANR-18-ORAR-0005-01
  • PI: Jean-Marc Tallon

In many real-world situations, it is not possible to model uncertainty by means of well-defined probability distributions. Instead, participants face Knightian uncertainty: they do not know the exact probability distribution over possible outcomes. In view of this, it is important to incorporate such Knightian uncertainty or ambiguity into the analysis of markets and strategic conflicts. This project aims to clarify the foundations for ambiguity in dynamic financial markets and strategic interactions. As a by-product, we aim to unify different (extant) approaches to modeling preferences and decision making in games under ambiguity. The issue of dynamic consistency will now be of particular concern. We apply our newly developed theoretical tools to a concrete economic problems by studying in detail the consequences of Knightian uncertainty in strategic interactions like dynamic contracts and elections on the one hand, as well as in markets under uncertainty, including portfolio choice and asset pricing with heterogeneous agents and incomplete information.

Coping with Heterogeneous Opinions

  • 2017-2022 [CHOp]
  • Funding: ANR-17-CE26-003-03
  • PI: Eric Danan, Jean-Marc Tallon

This project tackles the issue of the diversity of opinions in a society. It is grounded in Economics but is at the intersection with several other fields: Psychology, Statistics, Decision Theory, Analytical Philosophy, Social Choice, and Political Science. It goes beyond equating individuals’ opinions with their probabilistic beliefs, a standard practice in Economics, and aims at encompassing notions like unawareness, ambiguity, and competence to analyze opinion heterogeneity more broadly. The general questions we will explore are the following ones: How does diversity of opinions come about and how can it survive? What is the impact of this diversity on economic arrangements? How do individuals react when confronted with other’s opinions? How can one aggregate the various opinions to make the best decisions? These questions deserve to be treated both normatively and positively, calling for various analytical approaches (e.g. axiomatic treatment, modelling of markets, etc.) and experimental approaches (from psychophysics and social psychology). From a positive side, we will provide models explaining how individuals exposed to the same information can disagree. This requires to think outside of the usual Bayesian, common prior framework. Getting outside of this framework is also required to provide an understanding of how disagreements can survive in the long run, as we aim to show, contrary to a long-standing view in economics that “irrational” opinions get wiped out of the market. Experimentally, we will focus on how individuals integrate heterogeneous opinions when making decisions and, in particular, how social pressure affects individuals’ opinions. We will finally analyze how opinion heterogeneity affects economic arrangements such as bargaining, risk sharing and financial markets, incentive provision, etc. From a normative side, we will concentrate on the many ways different opinions can be aggregated to form a social or group opinion. A particular attention will be given to procedures that allow one to extract a measure of competence or expertise from opinions expressed by members of a society or group. These degrees of competence will then be used to weight the various opinions in order to make the best informed decision for the group. We will provide an experimental assessment of these rules, compared with other rules studied in the literature. We will also go beyond taking opinions as exogenous and will see how correlations (and, possibly, failure to recognize these) among the sources of information accessible to individuals changes the way aggregating procedures like voting work. This study will fit into a more general research question which is how to aggregate “ill-defined” or “biased” opinions. The project’s aim is mainly to advance scientific knowledge on these issues. It could lead to define practical ways of aggregating opinions or rankings that could be of interest for the private and public sectors. The team of researchers assembled for this project have expertise in the various fields the project is touching. They have already worked, produced scientific papers published in the best international outlets and organized events together.