Trust as a decision under ambiguity

Chen Li,Peter P Wakker,Uyanga Turmunkh

doi:10.1007/s10683-018-9582-3

Chen Li, Peter P Wakker + Show 1 more

Open Access

https://doi.org/10.1007/s10683-018-9582-3

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Abstract

Decisions to trust in strategic situations involve ambiguity (unknown probabilities). Despite many theoretical studies on ambiguity in game theory, empirical studies have lagged behind due to a lack of measurement methods, where separating ambiguity attitudes from beliefs is crucial. Baillon et al. (Econometrica, 2018b) introduced a method that allows for such a separation for individual choice. We extend this method to strategic situations and apply it to the trust game, providing new insights. People’s ambiguity attitudes and beliefs both matter for their trust decisions. People who are more ambiguity averse decide to trust less, and people with more optimistic beliefs about others’ trustworthiness decide to trust more. However, people who are more a-insensitive (insufficient discrimination between different likelihood levels) are less likely to act upon their beliefs. Our measurement of beliefs, free from contamination by ambiguity attitudes, shows that traditional introspective trust survey measures capture trust in the commonly accepted sense of belief in trustworthiness of others. Further, trustworthy people also decide to trust more due to their beliefs that others are similar to themselves. This paper shows that applications of ambiguity theories to game theory can bring useful new empirical insights.

Highlights

Keynes (1921) and Knight (1921) emphasized the importance of developing models for ambiguity
We show that insensitivity plays a significant role in the trust decision
The median trustor was ambiguity indifferent (b = 0; contrary to prediction 1a), a-insensitive, and believed that the trustee was likely to choose any of the three options

Summary

Introduction

Keynes (1921) and Knight (1921) emphasized the importance of developing models for ambiguity (unknown probabilities). Despite the importance of ambiguity, only at the end of the 1980s people succeeded in developing the first decision models for ambiguity (Gilboa 1987; Gilboa and Schmeidler 1989; Schmeidler 1989). Traditional game theory invariably assumed that all uncertainties could be expressed in terms of Bayesian probabilities (e.g., Crawford et al 2013). With the increased awareness of the importance of ambiguity in economics, many theoretical studies have applied ambiguity models to the analysis of games, producing more realistic predictions of people’s choices.. Many experimental studies measure subjective beliefs of players about strategy choices of others, but these studies commonly take beliefs to be Bayesian (ambiguity neutral) additive probabilities because no alternative tools were available yet.. Many experimental studies measure subjective beliefs of players about strategy choices of others, but these studies commonly take beliefs to be Bayesian (ambiguity neutral) additive probabilities because no alternative tools were available yet. Even if one assumes that using such probabilities is rational, this assumption still does not hold empirically

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