An inquiry into the nature and causes of the Description - Experience gap

According to the Description-Experience gap (DE gap), people act as if overweighting rare events when information about those events is derived from descriptions but as if underweighting rare events when they experience them through a sampling process. Due to the variety of experimental designs and measures reported in previous literature, the nature, causes and implications of the phenomenon for economic theory remain unclear. We present a new experiment which examines in a unified design four distinct causal mechanisms that might drive the DE gap, attributing it respectively to information differences (sampling bias), to a feature of preferences (ambiguity sensitivity) or to aspects of cognition (likelihood representation and memory). Our design permits model-free and model-mediated tests for these mechanisms and for the DE gap itself. Using a model-free approach, we elicit a DE gap similar in direction and size to the literature’s average and find that, when each factor is considered in isolation, sampling bias stemming from under-represented rare events, is the only significant driver. Yet, model-mediated analysis shows that rare events are overweighted even in experience. Moreover, this level of analysis reveals the potential of a smaller DE gap, existing even without information differences.