gets w$_{0}$ + w total; otherwise, one is left with w$_{0}$ − w . The utility of a winning bet is u ( w$_{0}$ + w ) and that of a losing bet u ( w$_{0}$ − w ). The outcomes are denoted by A and B and we assume that one’s subjective probability estimate of A occurring is p ≥ 1 / 2. We use the formalism of prospect theory which can then be used for the special case of expected utility result as well. We assume operation in the domain of gains. This is applicable to our experiment since subjects have not yet had time to psychologically adapt to the bonus w$_{0}$ and, furthermore, since the money is going to charity, any amount raised is viewed as a gain. In prospect theory, the function V ( w ) that one seeks to maximize is, for a two-outcome prospect in the domain of gains, given by where ω ( p ) is the decision weight for probability p (Wakker 2010:230). For the utility function, we choose the common exponential form where θ is the risk aversion ( θ > 0) (Wakker 2010:80). The derivative u $^{′}$( x ) → 1 as x → 0 so the exponential is well-behaved near zero and hence more suitable for small wagers than the power law form (with power less than one) whose derivative blows up at zero. The exponential utility function is plotted in Figure S1a for prospect theory and expected utility theory (using their respective θ values corresponding to Equation S5 below). The decision weights can be represented by the following form (Wakker 2010:207– 208): ω ( p ) = bp γ bp γ + (1 − p ) $_{γ}$, (S3) S2 u ( x ) = 1 − e − θx θ , (S2) V ( w ) = ω ( p ) u ( w$_{0}$ + w ) + (1 − ω ( p )) u ( w$_{0}$ − w ) , (S1)