Most theories of risky choice postulate that a decision maker maximizes the expectationof a Bernoulli (or utility or similar) function. We tour 60 years of empirical search and concludethat no such functions have yet been found that are useful for out-of-sample prediction. Nor dowe find practical applications of Bernoulli functions in major risk-based industries such asfinance, insurance and gambling. We sketch an alternative approach to modeling risky choicethat focuses on potentially observable opportunities rather than on unobservable Bernoullifunctions.

We investigate the nature of continuous-time strategic interactions in public-goodsgames. In one set of treatments, four subjects make contribution decisions in continuous timewhile in another they make them only at discrete points of time. The effect of continuous timeis muted in public-goods games compared to simpler social dilemmas; the data suggest thatwidespread coordination problems are to blame. With a rich communication protocol, thesecoordination problems disappear and the median subject contributes fully to the public good,with no time decay. At the median, the same communication protocol is less than half aseffective in discrete time.