Economic experiments on truth-telling, information aggregation, and income inequality

This thesis contains three chapters employing controlled economic experiments. The first chapter studies to what extent laboratory measures of cheating generalize to the field. I present a novel measure that allows for individual level observations of cheating, and I relate decisions made in this laboratory task with individual choices taken in the field, where subjects can lie by mis-reporting their experimental earnings. According to this new measure, no correlation of behaviour between the laboratory and the field is found. The second chapter contributes to the literature on the ability of financial markets to perfectly aggregate private information into asset prices. Along with my co-authors, I conduct an experiment designed to benchmark information aggregation in markets, by randomly assigning subjects to different institutional environments, either a market or a BDM (Becker-DeGroot-Marschak) mechanism. We find a difference between the two environments that seems to be driven by price-insensitive traders, who appear to be unable to learn from market prices. In the third chapter, my co-author and I provide a causal identification of the impact of income inequality on attribution and social trust. We do so by using a combination of surveys and behavioral lab experiments. Using positional primes we find that a higher relative position has a positive impact on belief in meritocracy and social trust, which we causally identify both using a novel incentivized lab task as well as standard survey measures. These results are in line with correlational associations we find using larger general surveys. They speak to why inequality can be so socially and economically corrosive while at the same time remaining largely unaddressed.

Name dc:type.qualificationname

phd

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

University of Essex

Year dc:date.issued

2021

Author dc:creator

• Albertazzi, Andrea

• H Social Sciences (General)

Language dc:language

en