This dissertation consists of three chapters focusing on behaviour under risk and ambiguity. The first chapter analysed the best method to communicate risk information to weather forecast users whilst the last two analysed smallholder farmers’ and students’ decision making on crop selection when presented with uncertainty information of drought. In the first chapter, experimental economics methods were used to assess forecast user understanding of information in temperature forecast. We tested whether undergraduate students presented with uncertainty information (90th percent confidence intervals) in a table and bar graph format were able to correctly understand the forecast and use the extra information to choose the “correct" (most probable) outcome than if they are presented with a deterministic forecast. Participants from the University of Exeter were asked to choose the most probable temperature outcome between a set of “lotteries” based on the temperature up to five days ahead. If they chose a true statement, participants were rewarded with a cash payment. Results indicate that on average participants provided with uncertainty information performed better than those without. Statistical analysis indicates a possible learning effect as the experiment progressed. The second chapter assesses if there are gender differences in the behaviour of smallholder Zimbabwean farmers when faced with risk and ambiguity. The risk and ambiguity preferences of male and female farmers were elicited using a modified Holt and Laury (2002) field experiment. Farmers were asked to choose whether or not to adopt a new drought tolerant variety under different probabilities of a drought occurring. Subjects in one group were presented with known probabilities whilst another group was presented with ambiguous probabilities (range). Most of the farmers’ exhibited extreme ambiguity and risk aversion and female farmers were more averse. Results indicate heterogeneity and the need to disaggregate samples when analysing research results as there maybe underlying factors affecting different groups. The third chapter elicited the risk and ambiguity attitudes of vocational college students in Zimbabwe. Results indicate that in general, students were both risk averse and ambiguity averse. Those presented with the risk treatment were less risk averse compared with those shown the ambiguity treatment. Participants who were presented with the ambiguity treatment behaved as pessimists and perhaps made decisions based on probability of drought that was higher than the provided centre of the range. We found gender differences in risk attitudes: contrary to the norm, female participants were less risk averse compared to their male counterparts. This is however when all subjects are pooled together. Results also indicate that a higher certain payoff perhaps incentivises consistency and increases risk aversion. The data seems to indicate anchoring effects from varying the order the probability of drought was presented.

A large body of literature studies the issues of the option price and other ex-ante welfare measures under the microeconomic theory to valuate reductions of risks inherent in environment and human health. However, it does not offer a careful discussion of how to estimate risk reduction values using data, especially the modeling and estimating individual perceptions of risks present in the econometric models. The central theme of my dissertation is the approaches taken for the empirical estimation of probabilistic risks under alternative assumptions about individual perceptions of risk involved: the objective probability, the Savage subjective probability, and the subjective distributions of probability. Each of these three types of risk specifications is covered in one of the three essays. The first essay addresses the problem of empirical estimation of individual willingness to pay for recreation access to public land under uncertainty. In this essay I developed an econometric model and applied it to the case of lottery-rationed hunting permits. The empirical result finds that the model correctly predicts the responses of 84% of the respondents in the Maine moose hunting survey. The second essay addresses the estimation of a logit model for individual binary choices that involve heterogeneity in subjective probabilities. For this problem, I introduce the use of the hierarchical Bayes to estimate, among others, the parameters of distribution of subjective probabilities. The Monte Carlo study finds the estimator asymptotically unbiased and efficient. The third essay addresses the problem of modeling perceived mortality risks from arsenic concentrations in drinking water. I estimated a formal model that allows for ambiguity about risk. The empirical findings revealed that perceived risk was positively associated with exposure levels and also related individuating factors, in particular smoking habits and one’s current health status. Further evidence was found that the variance of the perceived risk distribution is non-zero. In all, the three essays contribute methodological approaches and provide empirical examples for developing empirical models and estimating value of risk reductions in environment and human health, given the assumption about the individual’s perceptions of risk, and accordingly, the reasonable specifications of risks involved in the models.