Presented at the Risk Theory Society Annual Seminar: The legal status of marijuana has transformed radically over the past two decades. Prior to 1996, marijuana was illegal across the country. Then, California started a trend that has seen marijuana legalized for medical purposes in 34 states and additionally for recreational purposes in 9 of those. While the public benefits of legalizing marijuana are well-documented, much of the potential public detriment remains under-studied. We focus on one potential detriment — the effect of marijuana legalization on automobile safety. Experimental studies show that marijuana negatively impacts driving ability. Given this, it is natural to assume that increasing access to marijuana would lead to an increase in car accidents, but the reality is unclear. Alcohol by itself is more detrimental to driving than the use of marijuana by itself. If marijuana and alcohol are substitutes, then lowering the absolute price of marijuana could lead people away from alcohol. Even with an increase in marijuana-related accidents, the total number of accidents could be reduced. We examine this question through the effect on the auto insurance market using localized, at the zip-code level, data on auto insurance premiums. We find that the legalization of medical marijuana leads to a decrease in auto insurance premiums of $5.20 per policy per year. This effect is stronger in areas close to a dispensary. We find limited evidence that the reduction is due to a decrease in drunk driving prior to legalization.

Presented at the Risk Theory Society Annual Seminar: We study preferences over lotteries that pay a fixed prize at an uncertain future date: what we call time lotteries. The standard model of risk and time preferences, Expected Discounted Utility, implies that individuals must be risk seeking towards such lotteries (RSTL). In contrast, we show experimentally that almost all subjects violate this property. Our main contributions are theoretical. First, we show that risk aversion over time lotteries can be captured by a generalization of Expected Discounted Utility that is obtained by keeping the behavioral postulates of Discounted Utility and Expected Utility. Second, we introduce a new property termed Stochastic Impatience, a risky counterpart of standard Impatience, and show that not only the model above, but also substantial generalizations that allow for non-Expected Utility and non-exponential discounting, cannot jointly accommodate it and even a single instance of risk aversion over time lotteries (or, equivalently, any violation of RSTL), showing a fundamental tension between the two.

Presented at the Risk Theory Society Annual Seminar: Why doesn’t the Modigliani-Miller theorem apply to the relationship between endowments (“firms”) and donors (“shareholders”), rendering an endowment’s investment policy neutral? We show that donor altruism (even if impure) breaks neutrality. Under a condition—which quickly converges to standard DARA preferences in the number of donors—endowment risk-taking reduces donor free-riding, is Pareto improving, and required by endowment competition. Contrary to asset-liability matching, large endowments optimally take substantial risk even if donors are very averse to changes in endowment-supported spending, reversing the standard moral hazard interpretation. Total giving grows unbounded in the number of donors even with pure altruism.