calculations.<sup>12</sup> Using data from the other five decision problems allows us to assign respondents to distinct risk preference categories. We classify a subject as **risk neutral** if she always chose the lottery with the highest expected value. We classify a subject as **risk loving** is she made risk neutral choices in all except in the last decision problem, and then chose the lottery which paid 10 and 200 shillings with equal probability over the lottery which paid 70 and 160 shillings with equal probability. We classify those subjects who always opted for the lowest variance, lowest expected value lottery as the **most risk averse** . The three categories most risk averse, risk neutral, and risk loving account for 22.5, 2.4, and 15.7 percent of subjects, respectively.

Offering subjects a series of choices also allows us to test whether individual decisions are consistent with a CRRA utility representation. There are 162 possible combinations of responses to the last 5 lottery choice problems, only 10 of which are consistent with a CRRA utility representation. 44.6 percent of subjects made choices which were consistent with the maximization of a CRRA utility function. If subjects were choosing lotteries at random, only 6.2 percent would make CRRA-consistent choices. However, only 4 percent of subjects made consistent choices that were not classified as either most risk averse, risk neutral, and risk loving. Figure 1 presents the fraction of respondents falling into each of five different categories: most risk averse, risk neutral, risk loving, other types of consistent choices (suggesting intermediate levels of risk aversion), and inconsistent choices. The figure demonstrates that patterns of choices which are inconsistent with the maximization of a CRRA utility function occur substantially less frequently than we would expect if subjects were selecting lotteries at random, but that only the first three types of consistent

> 12We also asked enumerators to indicate whether they believed that respondents fully understood the lottery choice questions; these responses suggest that 99.6 percent of subjects fully comprehended the choices that they were making. There are, of course, several reasons that subjects who understood the decision problem might prefer a degenerate lottery to a stochastically dominant one involving risk. One possibility is that some respondents have preferences which are not monotonic. Several non-expected utility models of risk preferences suggest that individuals may prefer to avoid increases in payoff variance, even when the higher variance lottery stochastically dominates the lower variance alternative. For example, specifications of the non-linear probability weighting component of prospect theory typically assume sub-additivity (Kahneman and Tversky 1979); the models of risk attitudes proposed by K ̋osegi and Rabin (2006) and Andreoni and Sprenger (2010) are also consistent with a preference for the riskfree Option A over the stochastically dominant Option B. We interpret the overwhelming tendency to choose the stochastically dominant lottery as evidence against strongly non-monotonic preferences. One plausible interpretation of the observed choice patterns is that respondents have monotonic preferences which they implement with error (Hey and Orme 1994, Loomes 2005, Von Gaudecker, van Soest, and Wengstr ̈om 2011, Choi, Kariv, M ̈uller, and Silverman 2014).

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