Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Many of the most significant risks that people face in their lives are left-skewed, i.e., imply large losses with only small probability. I characterize skewness in binary risks, which are widely applied in both economic models and experiments. Moreover, I provide an explicit re-parametrization of binary risks in terms of their first three moments. These results allow for the conducting of comparative statics analysis with regard to skewness, and provide a useful tool for the calibration of lotteries in experiments. I apply them to show that left-skewed background risks give rise to a very strong precautionary saving motive, and to collect additional laboratory evidence on skewness preference and risk-seeking behavior.