 There is some debate among economists, political scientists, and philosophers over the precise way to calculate the probability that a vote will be decisive. Nevertheless, they generally agree that the probability that the modal individual voter in a typical election will break a tie is small. Binomial models of voting estimate the probability of a vote being decisive by modeling voters as if they were weighted coins and then asking what the probability is that a weighted coin will come up heads exactly 50% of the time. These models generally imply that the probability of being decisive, if any candidate has a lead, is vanishingly small, which in turn implies that the expected benefit of voting (i.e., \(p[V(D) - V(R)]\)) for a good candidate is worth far less than a millionth of a penny (G. Brennan and Lomasky 1993: 56–7, 119). A more optimistic estimate in the literature, which uses statistical estimate techniques based on past elections, claims that in a typical presidential election, American voters have widely varying chances of being decisive depending on which state they vote in. This model still predicts that a typical vote in a “safe” states, like California, has a vanishingly small chance of making a difference, but suggests that that a vote in very close states could have on the order of a 1 in 10 million chance of breaking a tie (Edlin, Gelman, and Kaplan 2007). Thus, on both of these popular models, whether voting for the purpose of changing the outcome is rational depends upon the facts on the ground, including how close the election is and how significant the value difference is between the candidates. The binomial model suggests it will almost never be rational to vote, while the statistical model suggests it will be rational for voters to vote in sufficiently close elections or in swing states.