Theory-Experimental Seminar

Georg Weizsäcker (with P. Albert, M. Costa-Gomes and S. Huck)

Humboldt-Universität zu Berlin

5-Mar-2018

Seminar 3 – 14:30

Abstract

The talk covers an experimental paper as well as a theory paper, both on economic situations where an agent’s payoff depends on market interactions between other agents. In the experimental paper, we assess the ability of human agents to predict the equilibrium of such interactions. The relevant market includes a seller and a buyer who can be one of two types, enabling a possible selection in equilibrium. We find that choices coincide with the prediction of cursed equilibrium Eyster and Rabin (2005), neglecting the selection, much more than those of Bayes Nash Equilibrium. The bias is substantially reduced in an economically equivalent treatment where Bayesian reasoning requires only first-order beliefs about other agents. In the theoretical paper, written with Steffen Huck, we study a market for sensitive personal information. An agent wants to communicate with another party but any revealed information can be sold to a third party whose reaction harms the agent. The market for information induces an adverse sorting effect, allocating the information to those types of third parties who harm the agent most. In equilibrium, this limits information transmission by the agent, but never fully deters it. Like in the experimental paper, here we also consider agents who naively provide information to the market. Their presence renders traded information more valuable and, thus, harms sophisticated agents by increasing the third party’s demand for information. Half-baked regulatory interventions may hurt naive agents without helping sophisticated agents.

Leave Comment

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

clear formSubmit

This site uses Akismet to reduce spam. Learn how your comment data is processed.