MOREV | Motivated Reading of Evidence

Summary
Economists have distinguished for long soft and hard information with the understanding that cheap talk is more prone to subjective interpretation than hard evidence. In fact, any piece of evidence carries some of the true underlying information that agents are usually assumed to be willing and able to access. For various reasons, agents may however prefer to avoid disturbing truths or maintain wrong but encouraging beliefs. In MOREV, I propose to study motivated reading of evidence, that is, study how individuals interpret hard information in ways that serve their own purposes. I wish to identify the goals that push the reading of evidence in systematic ways. I also want to study how agents manage to distort this reading, for example by choosing not to read or reason about available evidence. The MOREV project is divided into two parts, each bringing the recent literature on motivated beliefs to a new area of study.

In part 1, I will focus on agents' motivated reading of evidence about other individuals (their ability, their socio-economic characteristics, etc.). Indeed, one may not view a person the same way ahead of cooperative or competitive tasks. It is well-established that how close agents feel to each other (as network members or in terms of social identity) affects what they do to each other. I propose to investigate experimentally and theoretically the converse relationship: how do agents’ strategic goals affect their perception of others?

In part 2, I will focus on agents' motivated reading of evidence about products. For example, consumers may purposefully distort their beliefs about some attributes to make their purchasing plans easier to execute or take on. To do so, agents may not interpret vague information skeptically or, more generally, use motivated reasoning processes. By studying these ideas in the lab and in new models, I aim at bringing a novel explanation to the fact that, in many markets, information does not unravel as theory predicts./
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/850996
Start date: 01-02-2020
End date: 31-01-2026
Total budget - Public funding: 1 234 878,00 Euro - 1 234 878,00 Euro
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Original description

Economists have distinguished for long soft and hard information with the understanding that cheap talk is more prone to subjective interpretation than hard evidence. In fact, any piece of evidence carries some of the true underlying information that agents are usually assumed to be willing and able to access. For various reasons, agents may however prefer to avoid disturbing truths or maintain wrong but encouraging beliefs. In MOREV, I propose to study motivated reading of evidence, that is, study how individuals interpret hard information in ways that serve their own purposes. I wish to identify the goals that push the reading of evidence in systematic ways. I also want to study how agents manage to distort this reading, for example by choosing not to read or reason about available evidence. The MOREV project is divided into two parts, each bringing the recent literature on motivated beliefs to a new area of study.

In part 1, I will focus on agents' motivated reading of evidence about other individuals (their ability, their socio-economic characteristics, etc.). Indeed, one may not view a person the same way ahead of cooperative or competitive tasks. It is well-established that how close agents feel to each other (as network members or in terms of social identity) affects what they do to each other. I propose to investigate experimentally and theoretically the converse relationship: how do agents’ strategic goals affect their perception of others?

In part 2, I will focus on agents' motivated reading of evidence about products. For example, consumers may purposefully distort their beliefs about some attributes to make their purchasing plans easier to execute or take on. To do so, agents may not interpret vague information skeptically or, more generally, use motivated reasoning processes. By studying these ideas in the lab and in new models, I aim at bringing a novel explanation to the fact that, in many markets, information does not unravel as theory predicts./

Status

SIGNED

Call topic

ERC-2019-STG

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2019
ERC-2019-STG