Location: 

360 Heady Hall

Time: 

4 Oct 2012, 3:40 pm - 5:00 pm

Contact Person: 

Orazem, Peter F.

Description: 

"Trust between Strangers: Belief Updating from Noisy Feedback," with Fanzheng Yang, Iowa State University

Abstract: We study how trust between strangers evolves in a setting with noisy feedback on actions of others. We first examine how players choose to optimally manage their trust in others in a theoretical model where trustors process noisy feedback about the "trustworthiness" type of trustees. We discuss whether trustors use Bayesian updating to calculate their degree of trust or whether they process information in a biased manner. To study this empirically, we design a laboratory experiment using a two-player sequential trust game with several rounds of subsequent noisy feedback on the action of the trustee. We track the evolution of trustors' individual beliefs about trustworthiness types of trustees to document that subjects process information in an asymmetric way compared to a perfect Bayesian: they react more to negative feedback rather than positive. Trust is therefore much easier to destroy than to build.

We then use this setting to study how social identity information affects information processing. We match participants from two different universities (in Hong Kong and Beijing, respectively) and prime them on the social identity of their counterpart. We first document that players exhibit in-group favoritism by having higher degree of trust in the in-group members. We then show that trustors are more asymmetric compared to anonymous matching baseline in reacting to feedback about in-group trustees: they overreact to negative feedback and underreact to positive feedback about in-group members. Consequently, while degree of trust in ingroup members is initially higher, trust maintenance in ingroup matches is more fragile.