Thesis (Ph. D.)--George Mason University, 2007. / Title from PDF t.p. (viewed Jan. 22, 2008). Thesis director: Kevin A. McCabe. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Economics. Vita: p. 126. Includes bibliographical references (p. 119-125). Also available in print.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1967. / Typescript. Vita. Description based on print version record. Includes bibliographical references.

<p>This thesis investigates pubic policy actions and their spillovers to broader geographies.</p>

Not available / text

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Neoclassical economics assumes that consumers have stable, well-defined preferences. However, only 16% of subjects selected a chocolate bar when given a choice between it and a coffee cup, while 43% kept a chocolate bar previously given to them when offered a trade for a coffee cup. Instructional wording had no effect. These results support the hypothesis that people value losses more than gains. / Subjects were asked their willingness-to-pay (WTP) for twelve goods classified as either public or private, or as environmental or nonenvironmental. WTP tended to be lower for public goods when subjects previously ranked the personal importance or benefit they placed on the good. Importance was a weaker bias than benefit. Benefit appeared to induce free rider behaviour for public goods. The only environmental good affected by reading about sustainable development was one specifically mentioned in the article. Biases affecting WTP did not generally affect attributes correlated to WTP.

Economic systems analysis is a systems analysis technique of setting out the factors that have to be taken into account in making economic systems decisions. The inquiring and operational systems of the technique are almost exclusively designed for well-structured systems. In review of economic systems analysis against systems thinking, there is a growing tendency to discard the analytical approach as inappropriate for dealing with an ill-structured issue. Therefore, economic systems analysis needs both the inquiring and operational systems which are appropriate for ill-structured systems. The foregoing leads to the introduction of an extensive methodology. Mainly, the weakness of economic systems analysis methodology can be traced to the philosophical paradigm upon which the technique is based. In this study, four main aspects of both the inquiring and operational systems of economic systems analysis are being explored: (1) A new philosophical paradigm is proposed as the foundation of general methodology in place of the traditional Newtonian-Kantian inquiring system. (2) The new philosophical paradigm needs new problem formulation and analysis space; therefore, a multidimensional, synergetic, and autopoietic model is proposed for systems synthesis and systems analysis. (3) The new philosophical paradigm is characterized as a Singerian inquiry, and as a result, Marglin's multiobjective analysis is replaced by a Singerian multiobjective analysis. (4) Markov communication theory and fuzzy sets theory are proposed as tools for handling complexity. Markov communication theory and fuzzy sets theory are introduced for systems design and multiple objective analysis. This study reports on the first application of a Singerian fuzzy multiobjective mathematical algorithm in economic systems analysis, concluding that fuzzy systems theory, especially Markov communication theory, can realize approximate reasoning in economic systems analysis. Fuzzy modeling offers a deeper understanding of complexity and a means of expressing the insights that result from that understanding; moreover, it provides a means of incorporating subjectivity and adaptation. Therefore, fuzzy modeling increases the validity of the systems approach for dealing with ill-structured systems. The proposed method represents an important theoretical improvement of Marglin's approach. The results, however, also hold practical importance, for they are of practical interest to systems analysts who would improve systems design and multiobjective analysis.

No description available.

M.Comm.

In real-world settings, decision-making typically resembles a stepwise process in which one decides which information to sample before deciding to which decision option to commit. The former step is called instrumental information-seeking, and theoretical and empirical findings indicate that it is mediated by the value of information (VOI), the extent to which obtaining information increases the expected value of future actions and decisions. Economic theory predicts that to estimate VOI, decision-makers conduct a preposterior analysis in which they prospect what they would expect to know about the decision options after observing the information—or, in terms of Bayesian inference, they should prospect the future posterior probabilities. But the neural mechanisms underlying this early step of the computation of VOI remain an open question. Therefore, to further investigate the neural substrates of instrumental information-seeking, we used functional magnetic resonance imaging (fMRI) in conjunction with two interrelated behavioral tasks in humans. With one task, we examined the demand for instrumental information, but since preposterior analysis relies on the prospection of potential future posterior beliefs, we included another task to examine how people form posterior beliefs after receiving information. We found that regions of posterior parietal cortex and occipital fusiform gyrus appear to support a preposterior analysis through the prospection of expected posterior certainty. This aligned with our finding of a region of parieto-occipital cortex that appears to support Bayesian inference by integrating the prior probability of a hypothesis with the likelihood of observed information. These results imply that parietal cortex plays a key role in Bayesian inference, supporting preposterior analysis during information-seeking in addition to Bayesian inference during categorical decision-making.