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Genetic diversity is recognized as an important population attribute for both conservation and evolutionary purposes; however, the functional relationships between the environment, genetic diversity, and fitness-related traits are poorly understood. We examined relationships between selected lake parameters and population genetic diversity measures in 46 walleye ( Sander vitreus ) populations across the province of Ontario, Canada, and then tested for relationships between six life history traits (in three categories: growth, reproductive investment, and mortality) that are closely related to fitness, and genetic diversity measures (heterozygosity, d 2 , and Wright’s inbreeding coefficient). Positive relationships were observed between lake surface area, growing degree days, number of species, and hatchery supplementation versus genetic diversity. Walleye early growth rate was the only life history trait significantly correlated with population heterozygosity in both males and females. The relationship between F IS and male early growth rate was negative and significant ( P < 0.01) and marginally nonsignificant for females ( P = 0.06), consistent with inbreeding depression effects. Only one significant relationship was observed for d 2 : female early growth rate ( P < 0.05). Stepwise regression models showed that surface area and heterozygosity had a significant effect on female early growth rate, while hatchery supplementation, surface area and heterozygosity had a significant effect on male early growth rate. The strong relationship between lake parameters, such as surface area, and hatchery supplementation, versus genetic diversity suggests inbreeding and outbreeding in some of the populations; however, the weak relationships between genetic diversity and life history traits indicate that inbreeding and outbreeding depression are not yet seriously impacting Ontario walleye populations.

The 2008 financial crisis revealed systemic weaknesses in the global financial architecture, gave rise to the most severe economic collapse since the Great Depression and engendered a fundamental shift in the prevailing consensus on financial governance. It reminded us of the fragility of the international financial system and the politically unacceptable costs to society when it fails. This dissertation adds to the literature on the governance of private and public sector financial institutions. It presents a conceptual framework of linkage between the governance of financial institutions, systemic risk and financial crises. It is based on a review of the empirical and theoretical literature on the influence of financial regulation and governance on the stability of the international financial system. The dissertation examines the application of financial governance in three different contexts: (i) the introduction of a common regulatory framework for the European securities industry, known as MIFID; (ii) the introduction of a risk governance framework at a US federal agency, the US Export-Import Bank, and (iii) the introduction of performance metrics among Export Credit Agencies that operate within a common governance framework known as the Arrangement on Officially Supported Export Credits. In addition, the dissertation provides specific policy recommendations designed to enhance the portfolio risk management practices of the US Export Import Bank. By extension, these recommendations are relevant to a wider audience of federal agencies with similar portfolio credit risks and may help inform the design of a robust risk management framework that is critical to the government's ability to manage its burgeoning credit portfolio. Ph. D.

Researchers have consistently found that students and their parents have a distorted view of the costs of college attendance (Grodsky & Jones, 2004; Horn, Chen, & Chapman, 2003; Ikenberry & Hartle, 1998; Mumper, 1996). Those who are able to give an estimate of the tuition for various higher education alternatives often overestimate the actual price. When asked to estimate the tuition that in-state undergraduates would pay at four-year colleges in a given year, most students and their parents thought that the price was twice the actual amount (Horn et al., 2003b). Seventy-one percent of all individuals, and 83% of African-Americans believed that college was unaffordable for most families. The majority of individuals over-estimated the price by several thousands of dollars (Hartle, 1998). This study examined the literature on perceived price and used the theoretical construct based on the work of Nobel Prize winner Gary Becker to develop a methodology for studying whether students' perceived price of has a statistically significant impact on their plan to attend college and their actual matriculation. Applying Becker's theory, having faulty information on the price of attendance would result in people incorrectly weighting the cost-benefit equation and making what could be considered irrational decisions in the presence of complete information. Highlighting the problem of misperceived price is the contribution this study makes to the literature. Further study is warranted to determine the extent to which individuals use misperceived prices to make decisions on whether to plan to attend higher education. Ph. D.

Service discovery is a driving force in realizing pervasive computing. It provides a way for users and services to locate and interact with other services in a pervasive computing environment. Unfortunately, current service discovery solutions do not capture the effects of the human or physical world and do not deal well with diverse device populations; both of which are characteristics of pervasive computing environments. This research concentrates on the examination and fulfillment of the goals of two of the four components of service discovery, service description and dissemination. It begins with a review of and commentary on current service discovery solutions. Following this review, is the formulation of the problem statement, including a full explanation of the problems mentioned above. The problem formulation is followed by an explanation of the process followed to design and build solutions to these problems. These solutions include the Pervasive Service Description Language (PSDL), the Pervasive Service Query Language (PSQL), and the Multi-Assurance Delivery Protocol (MADEP). Prototype implementations of the components are used to validate feasibility and evaluate performance. Experimental results are presented and analyzed. This work concludes with a discussion of overall conclusions, directions for future work, and a list of contributions. Ph. D.

This research focuses on developing a cognitive radio that could operate reliably in unforeseen communications environments like those faced by the disaster and emergency response communities. Cognitive radios may also offer the potential to open up secondary or complimentary spectrum markets, effectively easing the perceived spectrum crunch while providing new competitive wireless services to the consumer. A structure and process for embedding cognition in a radio is presented, including discussion of how the mechanism was derived from the human learning process and mapped to a mathematical formalism called the BioCR. Results from the implementation and testing of the model in a hardware test bed and simulation test bench are presented, with a focus on rapidly deployable disaster communications. Research contributions include developing a biologically inspired model of cognition in a radio architecture, proposing that genetic algorithm operations could be used to realize this model, developing an algorithmic framework to realize the cognition mechanism, developing a cognitive radio simulation toolset for evaluating the behavior the cognitive engine, and using this toolset to analyze the cognitive engineà ­s performance in different operational scenarios. Specifically, this research proposes and details how the chaotic meta-knowledge search, optimization, and machine learning properties of distributed genetic algorithm operations could be used to map this model to a computable mathematical framework in conjunction with dynamic multi-stage distributed memories. The system formalism is contrasted with existing cognitive radio approaches, including traditionally brittle artificial intelligence approaches. The cognitive engine architecture and algorithmic framework is developed and introduced, including the Wireless Channel Genetic Algorithm (WCGA), Wireless System Genetic Algorithm (WSGA), and Cognitive System Monitor (CSM). Experimental results show that the cognitive engine finds the best tradeoff between a host radio's operational parameters in changing wireless conditions, while the baseline adaptive controller only increases or decreases its data rate based on a threshold, often wasting usable bandwidth or excess power when it is not needed due its inability to learn. Limitations of this approach include some situations where the engine did not respond properly due to sensitivity in algorithm parameters, exhibiting ghosting of answers, bouncing back and forth between solutions. Future research could be pursued to probe the limits of the engineà ­s operation and investigate opportunities for improvement, including how best to configure the genetic algorithms and engine mathematics to avoid engine solution errors. Future research also could include extending the cognitive engine to a cognitive radio network and investigating implications for secure communications. Ph. D.

Statistically significant prediction of stock price changes requires security returns' correlation with, or dependence upon, some variable(s) across time. Since a security's past return is commonly employed in forecasting, and because the lack of lower-order correlation does not guarantee higher-order independence, nonlinear testing that focuses on higher-order moments of stock return distributions may reveal exploitable stock return dependencies. This dissertation fits AR models to TAQ data sampled at ten-minute intervals for 20 small-capitalization, 20 mid-capitalization, and 20 large-capitalization NYSE securities, for the years 1993, 1995, 1997, 1999 and 2001. The Hinich Patterson Bicovariance statistic (to reveal nonlinear and linear autocorrelation) is computed for each of the 1243 trading days for each of the 60 securities. This statistic is examined to see if it is more or less likely to occur in securities with differing market capitalization, at various calendar periods, in conjunction with trading volume, or instances of changing investor sentiment, as evidenced by the put-call ratio. There is a statistically significant difference in the level and incidence of nonlinear behavior for the different-sized portfolios. Large-cap stocks exhibit the highest level and greatest incidence of nonlinear behavior, followed by mid-cap stocks, and then small-cap stocks. These differences are most pronounced at the beginning of decade and remain significant throughout the decade. For all size portfolios, nonlinear correlation increases throughout the decade, while linear correlation decreases. Statistical significance between the nonlinear or the linear test statistics and trading volume occur on a year-by-year basis only for small-cap stocks. There is sporadic seasonality significance for all portfolios over the decade, but only the small-cap portfolio consistently exhibits a notable "December effect". The average nonlinear statistic for small-cap stocks is larger in December than for other months of the year. The fourth quarter of the year for small-cap stocks also exhibits significantly higher levels of nonlinearity. An OLS regression of the put/call ratio to proxy for investor sentiment against the H and C statistic was run from October 1995 through December 2001. There are instances of sporadic correlations among the different portfolios, indicating this relationship is more dynamic than previously imagined. Ph. D.

Models of the term structure of interest rates play a central role in the modern theory of pricing bonds and other interest rate claims. Term structure models based on the principle of no-arbitrage, especially those of the Heath-Jarrow-Morton (1992) class, have become very popular recently, both with academics and practitioners. Surprisingly however, although the implied volatility function plays a crucial role in these no-arbitrage term structure models, there is little systematic evidence to guide optimal model specification within this broad class. We study the implied volatility in the Heath-Jarrow-Morton framework using Eurodollar futures options data. We estimate a daily time series of forward rates within the HJM framework such that, by construction, the predicted futures prices from our model exactly match the observed futures prices. Next, we estimate a daily time series of volatility parameters such that the sum of squared errors between futures options prices predicted by the model and observed futures options prices is minimized. We use the six different volatility specifications suggested by Amin and Morton (1994) within the HJM class of models to price interest rate claims. Since the volatilities are the only unobservables, we use these models to infer the volatilities from the market prices of Eurodollar futures options over the 1987-1998 periods. The minimized sum of squared errors in the option prices is used as the measure of accuracy of each specific model. Each model differs from the others in its ability to match the market option prices and the time required for the computation. We compare the performances of the six volatility specifications in the accuracy-versus-computation time tradeoff. We document the systematic biases between the model and market prices as a function of option type, maturity, and moneyness. We also examine alternative numerical implementations of HJM models using the six volatility specifications. In particular, we analyze the impact on accuracy and computation time of using different numbers of time-steps. We also examine the effect of using time-steps of varying lengths within the same estimation procedure, and of ordering the time-steps in different ways. Ph. D.

Rural telephony has historically been a recurring subject of concern for most large developing countries. It is generally considered that rural telephone users do not generate the same level of telephone traffic and, thus, revenue as urban users, lowering the incentives to invest in rural telecommunications. The financial implications of wiring a vast area for low telephone traffic causes most telephone service providers to ignore or delay offering telephone service to those regions. Still, it is known that telecommunications are essential to the economic development of a region, and that traffic increases rapidly as soon as the service is available. A satellite-based telephone network can provide efficient long distance telephone service to remote rural communities at a lower cost than land-based wired networks in most cases. Mobile satellite systems already provide this service, but are limited in capacity and charge high per- minute fees for the satellite link. Small earth stations and GEO satellites can provide this service more efficiently and at lower cost. A methodology to optimize the network performance has been developed. A set of economic models to evaluate different combinations of network topologies and multiple access techniques have been implemented, and a technical-economic assessment has been performed for the different technologies under different traffic scenarios. Traffic intensity, network size and per-minute user costs have been optimized to achieve the network's economic break-even point under different conditions and constraints. The general behavior of fixed-assignment Single Channel per Carrier SCPC), fixed-assignment Multiple Channel per Carrier (MCPC) and demand-assignment SCPC star networks, as well as demand-assignment SCPC mesh networks has been analyzed. Important parameters have been identified in order to improve the process of effective and cost-efficient satellite rural telephone network design. Ph. D.

Some firms allow their CEO to hold the position of Chair of the Board of Directors while other firms choose to split those two positions between two different individuals. This dissertation first examines whether agency control mechanisms, agency problems, and other firm characteristics are related to the observed choice of one or two individuals in the two positions. The empirical research is based on the hypothesis that having the positions split between two individuals is a means of controlling agency problems when used in concert with (either as a substitute for or as a complement to) other mechanisms for controlling agency problems. Firms are thus viewed as evaluating the costs and benefits of split positions as well as of other agency control mechanisms. They choose the most cost effective means of addressing the problems they face. If split positions are more cost effective, then the firm should choose to split positions other things equal. The very high predictive power of the estimated logistic model confirms the hypothesis that the probability of choosing split positions is related to control mechanisms and agency problems as well as to size and other factors. Some agency control mechanisms perform as complementary agency control mechanisms and some as substitutes for split positions. The results suggest that firms with higher agency costs of debt and equity are more likely to have chosen to split positions. The results are thus consistent with the view of the choice of split positions as a means of managing agency problems in concert with other mechanisms in an integrative decision framework. The second part of the dissertation examines the linkage between the CEO-Chair choice and the performance of the company (as measured by returns or operating efficiency). Shareholder activists argue that poor performance results when the CEO serves simultaneously as the Chair of the Board of Directors, so called "CEO duality." This dissertation examines whether firms that split these positions experience higher accounting performance than firms that do not split the positions. Several hypotheses are tested regarding the effects on firms with split positions. The empirical model indicates that firms that have split positions exhibit, on average, no lower or higher performance than other firms after integrating into the model industry effects, the role of other agency control mechanisms, the size of agency problems, and other firm characteristics. This is consistent with an irrelevance hypothesis as well as with the possibility that firms choose their policies optimally once other factors are accounted for. However, the firms with split positions do exhibit a different relationship between information asymmetry and performance as well as between other agency control mechanisms and performance. The use of agency control mechanisms, for example as measured by the proportion of the firm held by institutional investors, have a greater effect on performance for non-split than for split firms. Overall the results support the notion that firm and management characteristics (such as the level of agency problems, information asymmetry, ownership structure, and the existence of other agency control mechanisms) influence the choice to split positions and influence the role and effectiveness of split positions. The vast majority of firms' choice can be predicted by using such characteristics in an integrated model of the decision. The results imply that the benefits of split positions may be firm specific, that split positions are only appropriate for some firms, and that a net benefit will not be captured by all firms that simply enact a policy of split positions independent of their fundamental characteristics. Ph. D.

I examine two potential instances of rent-seeking in financial markets in the 1980s. In the first essay I test whether managers engage in political activity designed to influence federal regulation of the market for corporate control. In the second, I examine whether firms in the financial services sector attempt to affect bank deregulation. Using Federal Election Commission data, I find campaign contributions by corporate political action committees (PACs) are negatively related to levels of inside ownership, my main proxy for managerial vulnerability to hostile tender offers. Contribution patterns for firms with less than 20% insider ownership are relatively highly correlated, and differ from those of firms with greater than 20% inside ownership. Low inside ownership firms have slightly higher levels of contributions to legislators on particular House and Senate committees proposing relevant legislation. However, when I analyze the impact of contributions on legislator support for regulation I find no statistical support for a theory of vote-buying. I conclude that corporate political behavior is tied to levels of inside ownership, and comprises an alternate index of manager-shareholder conflict. Using a similar approach to analyse the financial services industry, I also find significant patterns in political action committee (PAC) campaign contributions for depository (commercial bank and thrift) and non-depository (brokerage and insurance) sectors of the financial services industry during the 98th Congress (1983-84). Contributions by depository firm PACs appear not only to purchase access to legislators serving on important banking committees crucial to their interests, but are also a significant determinant of votes for repealing sections of the Glass-Steagall Act. Nondepository contributions do not appear to influence votes directly, even though the brokerage and insurance sectors effectively lobbied House Banking Committee chairman Fernand St Germain to enforce the regulatory status quo. When I measure the rents at stake in the legislation using a two-factor market model event study approach, I find that the passage of legislation in the Senate had a positive affect on depository firm returns, implying the sector's lobbying effort was justified. However non-depository PACs lobbied just as extensively, and did not experience significant abnormal returns over the same event period, even though this round of deregulation should have been a zero-sum game between the affected sectors of the industry. I then measure the correlation between the market value impacts of new legislation and contribution amounts for individual firms within the sectors. I find rents are correlated with political activity, even for firms in the non-depository sectors. Ph. D.

Much of accounting research is predicated on the fact that the capital markets operate well because disclosures of annual earnings are verified. It is generally observed, however, that market responses to the unverified management forecasts may be as strong as responses to similar l verified information disclosures. This dissertation is concerned with the credibility of such unverified information. Three hypotheses are investigated in the study. The data includes managements' annual earnings forecasts gathered from the 1986 to 1992 editions of the Wall Street Journal. The first hypothesis concerns the timing of the disclosure of the forecasts by management. It is tested by comparing liquidity and leverage ratios at the event date to prior same-firm ratios. Evidence is found that supports the conclusion that the firm is preparing the market for a possible capital offering. The second hypothesis concerns the asymmetry of information between the firm and investors. This asymmetry affects the stock market reaction. It is tested using OLS regressions with the market reaction as the dependent variable and various asymmetry surrogates as independent variables. Evidence is found that supports the conclusion that as more investors follow the firm, there is less new information associated with the management forecast disclosure. Further, as fewer investors follow the firm, there is a lower tendency to disclose forecasts. The third hypothesis concerns the ability of the firm to provide credible communication. It is tested using OLS regressions with the market reaction as the dependent variable and various proprietary information surrogates as independent variables. Weak support is found for the conclusion that those firms releasing proprietary information through the forecast disclosure provide more credible communication. The support is restricted to the negative forecasts. For positive forecasts, it may be that reputation is most important to investor response. Ph. D.