Conferencias y seminarios pasados

El Centro de Investigación Económica (CIE), te invita al seminario: "Selected Facts"

Presentado por: Archisman Chakroborty

El seminario se llevará a cabo el 7 de marzo de 12:00 a 13:30 horas en la Sala Isóptica "A",  Santa Teresa.

El Centro de Investigación Económica (CIE), te invita al Brown Bag: “Rolling Back Progresa: School and Work After the End of a Landmark Anti-Poverty Program”

Presentado por: Susan Parker

Se llevará a cabo el 4 de marzo de 14:00 a 15:00 horas en la Sala Isóptica A, Santa Teresa

El Centro de Investigación Económica (CIE), te invita al seminario presentado por: Casey Petroff (Rochester)

El seminario se llevará a cabo el 21 de febrero de 12:00 a 13:30 horas en la Sala Isóptica "A" de Santa Teresa.

El Centro de Investigación Económica (CIE), te invita al Brown Bag: "Miscommunicating Group Preferences: An Experimental Approach"

 Presentado por: Mauricio Fernández Duque

Se llevará a cabo el 11 de febrero de 14:00 a 15:00 horas en la Sala Isóptica "A de Santa Teresa.

Abstract:

Understanding when groups misunderstand what its members want is key to designing better communication policies and avoiding suboptimal outcomes, but studying this question is challenging due to the complexity of communication. In this project we build on a stylized setting and conversation developed in Fernández-Duque (2022), which provides sharp predictions about the evolution of beliefs about others and the probability of pluralistic ignorance: a situation in which members of a group have a mistaken view about the opinions of others and are influenced by that view. Our design allows us to answer several questions. How likely is it that miscommunication (in the form of pluralistic ignorance) arises? Can we predict the probability of miscommunication with a previously-measured indicator of how hot button the topic is, and by variation in the experimentally-generated distribution of beliefs held by those from which the group is drawn? Are miscommunication and mistaken beliefs explained by rational Bayesian processing, or are there specific behavioral biases that can better explain the outcomes? Evidence from an initial pilot study sheds some light on these questions and charts a path forward.