This dissertation contains three essays on learning and risk aversion. In the first essay we consider how learning may lead to risk averse behavior. A learning rule is said to be risk averse if it is expected to add more probability to an action which provides, with certainty, the expected value of a distribution rather than when it provides a randomly drawn payoff from this distribution, for every distribution. We characterize risk averse learning rules. The result reveals that the analysis of risk averse learning is isomorphic to that of risk averse expected utility maximizers. A learning rule is said to be monotonically risk averse if it is expected to increase the probability of choosing the actions whose distribution second-order stochastically dominates all others in every environment. We characterize monotonically risk averse learning rules. In the second essay we analyze risk attitudes for learning within the mean-variance paradigm. A learning rule is variance-averse if the expected reduced distribution of payoffs in the next period has a smaller variance than that of the current reduced distribution, in every set where all the actions provide the same expected payoff. A learning rule is monotonically variance-averse if it is expected to add probability to the set of actions that have the smallest variance in the set, when all the actions have the same expected payoff. A learning rule is monotonically mean-variance-averse if it is expected to add probability to the set of actions that have the highest expected payoff and smallest variance whenever this set is not empty. We characterize monotonically variance-averse and monotonically mean-variance-averse learning rules. In the last essay we analyze the social learning process of a group of individuals. We say that a learning rule is first-order monotone if the number of individuals that play actions with first-order stochastic dominant payoff distributions is expected to increase. We characterize these learning rules.

This dissertation is an investigation into the determinants of demand for service contracts on new vehicles. In the first chapter, I characterize the consumer decision to buy a service contract with a discrete choice model. Hypotheses and conjectures are tested empirically using survey data from new vehicle buyers. The second chapter consists of the development and testing of an instrument for measuring attitudes toward uncertainty. This tool is useful in gauging aversion toward weak ambiguity. Finally, in the third chapter, I use additional survey and experimental data from new vehicle buyers to further differentiate between the factors that significantly affect the service contract purchase decision. A variety of uncertainty measures and their predictive powers are discussed. I would like to thank the John D. and Catherine T. MacArthur Foundation, Network on Preferences and Norms, for their generous financial support, which was indispensable to the completion of this research. / Ph. D.

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Second order stochastic dominance is an optimal rule for portfolio selection of risk averse investors when we only know that the investors' utility function is increasing concave. The main advantage of SSD is that it makes no assumptions regarding the return distributions of investment assets and has been proven to lead to utility maximization for the class of increasing concave utility functions. A number of different SSD models have emerged in the literature for portfolio selection based on SSD. However, current SSD models produce the same SSD efficient portfolio for all risk averse investors, regardless of their risk aversion degree. In this thesis, we have developed a new SSD efficiency model, SSD-DP, which unlike existing SSD efficiency models in the literature, provides an SSD efficient portfolio as a function of investors' risk aversion degrees. The SSD-DP model is based on the linear programming technique and finds an SSD efficient portfolio by minimizing the dual power transform (DP) of a weighted portfolio of assets for a given risk aversion degree. We show that the optimal portfolio of the proposed model is SSD efficient, i.e. it is not dominated by SSD by any other portfolio, and, through empirical studies of historical data, we show that the method is a promising tool for constructing trading strategies.

Second order stochastic dominance is an optimal rule for portfolio selection of risk averse investors when we only know that the investors' utility function is increasing concave. The main advantage of SSD is that it makes no assumptions regarding the return distributions of investment assets and has been proven to lead to utility maximization for the class of increasing concave utility functions. A number of different SSD models have emerged in the literature for portfolio selection based on SSD. However, current SSD models produce the same SSD efficient portfolio for all risk averse investors, regardless of their risk aversion degree. In this thesis, we have developed a new SSD efficiency model, SSD-DP, which unlike existing SSD efficiency models in the literature, provides an SSD efficient portfolio as a function of investors' risk aversion degrees. The SSD-DP model is based on the linear programming technique and finds an SSD efficient portfolio by minimizing the dual power transform (DP) of a weighted portfolio of assets for a given risk aversion degree. We show that the optimal portfolio of the proposed model is SSD efficient, i.e. it is not dominated by SSD by any other portfolio, and, through empirical studies of historical data, we show that the method is a promising tool for constructing trading strategies.

My dissertation consists of three essays. The central theme of these essays is the psychological factors and biases that affect the portfolio allocation decision. The first essay entitled, “Are women more risk-averse than men?” examines the gender difference in risk aversion as revealed by actual investment choices. Using a sample that controls for biases in the level of education and finance knowledge, there is evidence that when individuals have the same level of education, irrespective of their knowledge of finance, women are no more risk-averse than their male counterparts. However, the gender-risk aversion relation is also a function of age, income, wealth, marital status, race/ethnicity and the number of children in the household. The second essay entitled, “Can diversification be learned?” investigates if investors who have superior investment knowledge are more likely to actively seek diversification benefits and are less prone to allocation biases. Results of cross-sectional analyses suggest that knowledge of finance increases the likelihood that an investor will efficiently allocate his direct investments across the major asset classes; invest in foreign assets; and hold a diversified equity portfolio. However, there is no evidence that investors who are more financially sophisticated make superior allocation decisions in their retirement savings. The final essay entitled, “The demographics of non-participation”, examines the factors that affect the decision not to hold stocks. The results of probit regression models indicate that when individuals are highly educated, the decision to not participate in the stock market is less related to demographic factors. In particular, when individuals have attained at least a college degree and have advanced knowledge of finance, they are significantly more likely to invest in equities either directly or indirectly through mutual funds or their retirement savings. There is also evidence that the decision not to hold stocks is motivated by short-term market expectations and the most recent investment experience. The findings of these essays should increase the body of research that seeks to reconcile what investors actually do (positive theory) with what traditional theories of finance predict that investors should do (normative theory).

I collect data on subjects' information acquisition during real and hypothetical risky choices using process-tracing software called Mouselab. I also measure subjects' cognitive ability using the cognitive reflective test (CRT). On average, measured risk preferences are not significantly different across real and hypothetical settings. However, cognitive ability is inversely related to risk aversion when choices are hypothetical, but it is unrelated when the choices are real. This interaction between cognitive ability and hypothetical setting is consistent with the notion that some individuals, specifically higher-ability individuals, treat hypothetical choices as "puzzles" and may help explain why some studies find that subjects indicate that they are more tolerant of risk when they make hypothetical choices than when they make real choices. On average, subjects demonstrate a similar degree of consistency across settings, and there are also no significant differences across settings in the amount of time subjects take to make a choice, the amount of information they acquire, or how they distribute their attention. I also find evidence to suggest that subjects acquire information in a manner consistent with the implicit calculation of expected utility. Specifically, individuals do not merely make choices "as if" they are integrating probabilities and outcomes, it appears that they actually are. Moreover, as they progress through a series of choices in a commonly used risk preference elicitation method, their information acquisition becomes progressively more consistent with integration models. Finally, on average, individuals appear to acquire information in real and hypothetical settings in similar ways.

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Women, on average, are found in systematically different careers than men. The reason for this phenomenon is not fully understood, in part because expectations play a vital role in the process of career choice. Different religious groups have different beliefs on the importance of child bearing, so fertility expectations should differ by religious group. I include a woman's religious denomination in regressions on mea- sures of occupational flexibility. Jehovah's Witnesses choose the most flexible careers followed by Pentecostal, Catholic, Baptist, and Mainline Protestant women. Jewish women generally choose the least flexible careers. This is consistent with the human capital notion that women are choosing different careers than men rather than being forced into different job paths. If women are choosing jobs that allow them to take responsibility for home pro- duction, how does this affect their husbands? Male wage regressions that include marital status dummy variables find a marriage wage premium of 10 to 40%. This premium may occur because wives are taking responsibility for home production and husbands are free to focus their attention on productivity at work. It may also be that factors unobserved to the researcher may make a man more productive and more likely to marry. I use religious denomination as a proxy for specialization within the home. Men in more traditional religious denominations enjoy a higher marriage wage premium, which is evidence that household specialization of labor is an important cause of the wage premium. The choice of a career, whether to marry, and most other important life decisions are dependent on one's risk tolerance. The role of risk preferences in such choices is not fully understood, largely because relative risk aversion (y) is hard to empirically quantify. Chetty (2006) derives a formula for ° based on the link between utility and labor supply decisions. I estimate y at the micro level using the 1996 Panel Study of Income Dynamics. I compare y to an estimate based on hypothetical gambles and find the measures substantially different. This supports Chetty's claim that ex- pected utility theory cannot suffciently explain choices under uncertainty in different domains.

Foot and Mouth Disease (FMD) could have a significant impact on the U.S. agriculture industry and the welfare of U.S. producers and U.S. consumers. In order to address the potential impact from animal disease outbreaks, this project is designed to utilize a combined epidemic and economic modeling framework to evaluate animal disease management strategies which can be used to reduce the potential losses in an unusual event such as FMD outbreaks. In this study, we compare the welfare changes among three different parties with different strategies using, 1) ANOVA analysis; 2) cost benefit analysis; and 3) Risk Aversion Coefficient (RAC) analysis. Four types of index feedlots are selected in the study including, Feedlot Type 1 (> 50,000 heads of animals), Feedlot Type 4 (backgrounder feedlot), Large Beef Grazing (>100 heads of animals), and Backyard (<10 heads of animals). Results suggest that early detection of FMD events has the advantage in reducing risk as shown in the epidemiological impacts. Enhanced surveillance is found to be a preferred mitigation strategy for U.S. consumers in the scenario of smaller feedlot disease introductions (e.g. Large Beef Grazing and Backyard) and for U.S. producers in the larger feedlot disease introduction scenarios (e.g. Feedlot Type 1 and Feedlot Type 4). Adequate vaccination is not cost effective when seeking to minimize average loss but becomes a preferred strategy when the risk aversion rises. Risk modeling with stochastic programming adopted in this study also confirms the importance of incorporating risk evaluation into decision making process. It offers another option for us to evaluate the mitigation strategies. Two portfolio models are adopted in this study including, E-V model (mean variance portfolio choice model) and Unified model. The results show that the preference for control strategies depends on risk attitude. Early detection proves to be preferable for U.S. consumers and is also preferred by U.S. processors and producers as Risk Aversion Parameters (RAP) rises. Adequate vaccination strategy can benefit U.S. consumers but does not give U.S. processors a better outcome. Adequate vaccination provides a better choice for U.S. producers when the RAP rises. Enhanced surveillance is preferred for U.S. consumers. For U.S. processors, enhanced surveillance does not give a better risk/return outcome. U.S. producers are likely to switch their preferences from regular surveillance to enhanced surveillance as their RAP rises.