| Summary: | Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, February 2007. === Includes bibliographical references. === This dissertation is composed of three chapters, the first demonstrates that natural gas violates many of the simplifying assumptions frequently used in modeling its behavior. Careful analysis of futures contracts written on gas suggests that gas prices are seasonal while returns are non-Gaussian and evidence stochastic volatility. In addition, examination of options prices indicates the intermittent presence of jumps. We find that models which disregard these properties struggle to recover options prices with any precision. Thus, we propose an alternative nonparametric approach to gas options pricing that captures these salient features while also shedding light on the nature of risk aversion embedded in gas markets. The second chapter presents new estimates and approaches to estimating the home bias puzzle. It uses micro-level data to calculate households' foreign equity exposure as a function of wealth. We find simple estimates have significant errors-in-variables problems and we construct an estimator using grouping to account for this issue. Our estimates still imply low aggregate investment in foreign equity. Finally, we disaggregate the investment decision by incorporating two step decisions that allow households to forgo participating in the market. === (cont.) As a result of the decoupling, we find foreign equity levels closer to that of standard portfolio theories. The final chapter considers principal-agent models in which the principal cannot measure the output nor the effort level of agents. To model this situation, we use utility models that include identity, justified partly by empirical results from peer-effects, and apply these extended utility functions. In the single agent case, introducing identity amounts to modifying the utility function and does not lead to dramatic results. In the multiple agent case, we find that the addition of identity can lead to more efficient outcomes than cases where identity is ignored. The addition of identity, however, can also lead to counter-intuitive results due to the interactions among agents and may produce second-best outcomes that are worse than the case without identity. Finally the addition of identity can help explain some empirical results that may be difficult to explain with standard models. === by Alan Michael Grant. === Ph.D.
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