in the likelihood of choosing the highest variance, highest expected value lottery option in each of the five decision problems. Moreover, the effect is similar in magnitude across the four decision problems that include three lottery alternatives; the estimated effect of violence does not appear to be larger in decision problems that include a degenerate (i.e. risk-free) lottery as one of the alternatives. We interpret this as evidence that the impact of violence does not only operate through an increased preference for certainty.<sup>18</sup> Thus, our main result is robust to a wide range of alternative specifications.

Next, we employ a complementary identification strategy, exploiting the fact that KLPS2 respondents were randomly assigned to one of two waves of surveying to generate instrumental variables (IV) estimates of the impact of the post-election violence on measured risk aversion.<sup>19</sup> IV regression results are reported in Table 6. In Column 1, we include only controls for gender, age, education level, and marital status. Coefficient estimates indicate that the post-election crisis had a large and statistically significant impact on measured risk preferences, reducing the number of times (out of five) that respondents opted for the riskiest, highest expected value lottery by approximately one full question. Again, relative to a mean number of risky choices of about 2.5 in the pre-crisis period, this is an extremely large effect. In Columns 2 through 4 we include additional controls for the identity of the survey enumerator and the month in which the interview took place. Coefficient estimates are consistently negative and significant. Thus, our IV estimates are consistent with our un-instrumented results: Kenya’s post-election crisis appears to have made survey respondents substantially more risk averse.

display greater risk aversion when certainty is an option, but greater risk tolerance when no risk-free alternatives are available. They interpret this as evidence that subjects display a preference for certainty not consistent with expected utility maximization; their evidence suggests that violence impacts this preference for certainty. 18To further probe this issue, we examine the likelihood of choosing the _safest_ (i.e. lowest variance, lowest return) lottery alternative in each of the five decision problems. Results are reported in the Online Appendix. We find no evidence that the shift away from high-risk lotteries is stronger in decision problems that included options with purely certain outcomes.

> 19Before proceeding to our IV analysis, we check whether the random assignment of respondents to survey waves generated groups that were comparable in terms of observable characteristics at the start of the survey. We focus on fixed traits and outcomes that were recorded in the survey for specific points in time. For example, the survey collects detailed information about school participation in each year between 1998 and the moment of the interview; this allows us to generate a variable indicating the number of years of schooling that a respondent had completed at the start of 2007, regardless of the year in which a respondent was actually surveyed. Results are reported in the Online Appendix. We find no statistically significant differences between the survey waves in terms of proportion female, age in 2007, proportion from the local-majority Luhya ethnic group, years of schooling completed by 2007, and the proportion that were married by 2007. Thus, the randomization appears to have succeeded in creating groups of respondents that are similar in terms of observable characteristics.

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