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Antonio Guarino

Dados Biográficos

ID6411040
NOMEAntonio Guarino
PRENOMESAntonio
SOBRENOMEGuarino
ASSINATURAGUARINO A
AFILIAÇÕESUniversity of Southern California
ORCID0000-0001-5241-5855
VERIFICADOSim
TOTAL DE OBRAS4
TOTAL DE CITAÇÕES0
TOTAL COMO AUTOR4
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2017
ANO MAIS RECENTE DE PUBLICAÇÃO2022
ÍNDICE H0
  • Information redundancy neglect versus overconfidence

    Marco Angrisani, Antonio Guarino et al.•REPORT•2022

    We study social learning in a continuous action space experiment. Subjects, acting in sequence, state their belief about the value of a good, after observing their predecessors' statements and a private signal. We compare the behavior in the laboratory with the Perfect Bayesian Equilibrium prediction and the predictions of bounded rationality models of decision making: the redundancy of information neglect model and the overconfidence model. The …

  • Non-Bayesian updating in a social learning experiment

    Open Access•Roberta De Filippis, Antonio Guarino et al.•ARTICLE•Journal of Economic Theory•2021

  • Non-Bayesian updating in a social learning experiment

    Roberta De Filippis, Antonio Guarino et al.•REPORT•2020

    In our laboratory experiment, subjects, in sequence, have to predict the value of a good. The second subject in the sequence makes his prediction twice: first ("first belief"), after he observes his predecessor's prediction; second ("posterior belief"), after he observes his private signal. We find that the second subjects weigh their signal as a Bayesian agent would do when the signal confirms their first belief; they overweight the signal when …

  • Updating ambiguous beliefs in a social learning experiment

    Roberta De Filippis, Antonio Guarino et al.•REPORT•2017

    We present a novel experimental design to study social learning in the laboratory. Subjects have to predict the value of a good in a sequential order. We elicit each subject's belief twice: first ("prior belief"), after he observes his predecessors' action; second ("posterior belief"), after he observes a private signal on the value of the good. We are therefore able to disentangle social learning from learning from a private signal. Our main res…

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  • Updating ambiguous beliefs in a social learning experiment

    Roberta De Filippis, Antonio Guarino et al.•REPORT•2017

    We present a novel experimental design to study social learning in the laboratory. Subjects have to predict the value of a good in a sequential order. We elicit each subject's belief twice: first ("prior belief"), after he observes his predecessors' action; second ("posterior belief"), after he observes a private signal on the value of the good. We are therefore able to disentangle social learning from learning from a private signal. Our main res…

  • Non-Bayesian updating in a social learning experiment

    Roberta De Filippis, Antonio Guarino et al.•REPORT•2020

    In our laboratory experiment, subjects, in sequence, have to predict the value of a good. The second subject in the sequence makes his prediction twice: first ("first belief"), after he observes his predecessor's prediction; second ("posterior belief"), after he observes his private signal. We find that the second subjects weigh their signal as a Bayesian agent would do when the signal confirms their first belief; they overweight the signal when …

  • Non-Bayesian updating in a social learning experiment

    Open Access•Roberta De Filippis, Antonio Guarino et al.•ARTICLE•Journal of Economic Theory•2021

  • Information redundancy neglect versus overconfidence

    Marco Angrisani, Antonio Guarino et al.•REPORT•2022

    We study social learning in a continuous action space experiment. Subjects, acting in sequence, state their belief about the value of a good, after observing their predecessors' statements and a private signal. We compare the behavior in the laboratory with the Perfect Bayesian Equilibrium prediction and the predictions of bounded rationality models of decision making: the redundancy of information neglect model and the overconfidence model. The …

Artificial Intelligence (4 obras) · Computer Science (4 obras) · Experimental Behavioral Economics Studies (3 obras) · Opinion Dynamics and Social Influence (3 obras) · Bayesian inference (2 obras) · Bayesian probability (2 obras) · Cognitive psychology (2 obras) · Game Theory and Applications (2 obras) · Machine learning (2 obras) · Psychology (2 obras)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae