Browsing by Subject "risk aversion"
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Item Learning and risk aversion(2009-06-02) Oyarzun, CarlosThis 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.Item Measurement to Intelligence: Feature Extraction, Modeling and Predictive Analysis of Asymmetric Conflict Events(2014-06-06) George, Stephen MThe conflict events that comprise asymmetric warfare are a primary killer of both combatants and civilians on the modern battlefield. Improvised explosive devices (IED) and direct fire (DF), the most common of these attacks, claim thousands of lives as conventional and unconventional forces clash. Computer-based predictive analysis can be used to identify locations that are useful for these events, potentially providing the awareness needed to disrupt or avoid attacks before they are launched. In this dissertation, I propose an analytical framework for predictive analysis of asymmetric conflict events. This framework incorporates a tactics-aware system model based on attacker roles that is populated with a set of geomorphometric and visibility-constrained features describing terrain and proximity to necessary supporting structures. Features that identify and assess the utility of terrain for use by risk-averse attackers are important contributors to the model. Statistical learning is used to extract spatially and temporally constrained tactical patterns. These patterns are then used to predict the utility of future or unvisited locations for conflict events. Major contributions of this dissertation include: (1) A concise, accurate feature representation of conflict events in non-urban environments; (2) A system model based on attacker roles that captures the tactical patterns of conflict events; (3) Accurate conflict event classification algorithms that support predictive analysis; and (4) A novel method for detecting and describing features that support risk-averse attackers. The framework has been implemented and tested on real-world IED and DF data collected from the conflict in Afghanistan in 2011-2012. Several learning techniques are assessed using two dimensionality reduction schemes under a variety of spatial, temporal and combined constraints. A resource-unconstrained version of the framework accurately predicts conflict events across a wide range of terrain types and over the 19 months covered by available data. A limited version of the framework that assumes less computational capability provides useful predictive analysis that can be performed in mobile and resource constrained environments.Item Three essays in labor economics: fertility expectations and career choice, specialization and the marriage premium, and estimating risk aversion using labor supply data(2009-05-15) Leonard, Megan de LindeWomen, 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.