SkewPref SIGNED

Project "SkewPref" data sheet

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 Partnership

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 Project objective

“Penny-picking in front of a steamroller” describes the behavior of repeatedly taking risks with an unlikely but extreme downside in order to secure a small but likely benefit. Examples of penny-picking include risking one’s life by driving too fast or blowing up financial bubbles by speculating that they will not burst just yet. Penny-picking suggests that people underweight rare, high-impact events when making their decisions. On the other hand, individuals overpay for lottery gambles and insurances alike, suggesting just the opposite—that people overweight rare, high-impact events.

The goal of this project is to provide a fundamental understanding of humans’ skewness preferences—our attitudes toward rare, high-impact risks. I show that skewness preferences are much more influential on behavior than previously realized and thus must take a central place in the economic analysis of risk. The reason is that skewness preferences have unexpected and far-reaching implications in dynamic decision situations, and I will study their complex interaction with time.

I pursue this research agenda in three steps. First, I focus on static, one-time decision situations and define skewness preferences formally. I show that the leading economic theories—often implicitly—assign first-order importance to skewness preferences and that this observation explains much of these theories’ success. Second, I study skewness preferences in dynamic settings and analyze their complex interaction with time preferences. I propose a new model that identifies the role of skewness for repeated risk-taking. Third, I test my theoretical contributions through experiments on rare, high-impact risks in static and repeated decision situations, using a relatively novel experimental technique to implement rare, high-impact events. Out of the theoretical explanations established, I seek to identify the fundamental reasons behind phenomena such as penny-picking or the underweighting-overweighting paradox.