Information asymmetry in decision from description versus decision from experience

Abstract

In this paper we investigate the claim that decisions from experience (in which the features of lotteries are learned through a sampling process) differ from decisions from description (in which features of lotteries are explicitly described). We find that the experience-description gap is not as robust as has been previously assumed. We argue that when this gap appears it is driven to a large extent by asymmetries in information concerning which events are possible and which are certain. First, we find that, when experience-based decision makers sample events without error and then are told what outcomes are associated with each possible event, they are risk seeking for low-probability gains and risk averse for high-probability gains, as in description-based decision making. Second, we find that the experience-description gap for low-probability outcomes appears when rare outcomes are never experienced but disappears when: 1) all distinct outcomes are experienced at least once or 2) never-experienced outcomes are described as possibilities. Third, we find that the experience-description gap for high-probability outcomes is pronounced when decision makers previously experience lotteries that both offered the possibility of a zero outcome (which presumably makes them doubt that an always-experienced outcome is certain), but disappears when they have not previously experienced such lotteries.

Keywords

• decision from experience
• experience-description gap
• uncertainty
• risk
• information asymmetry