Problems of uncertainty, learning, and welfare measurement in resource and environmental economics

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2011-01-01
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Evans, Keith
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Joseph A. Herriges
Quinn Weninger
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Economics

The Department of Economic Science was founded in 1898 to teach economic theory as a truth of industrial life, and was very much concerned with applying economics to business and industry, particularly agriculture. Between 1910 and 1967 it showed the growing influence of other social studies, such as sociology, history, and political science. Today it encompasses the majors of Agricultural Business (preparing for agricultural finance and management), Business Economics, and Economics (for advanced studies in business or economics or for careers in financing, management, insurance, etc).

History
The Department of Economic Science was founded in 1898 under the Division of Industrial Science (later College of Liberal Arts and Sciences); it became co-directed by the Division of Agriculture in 1919. In 1910 it became the Department of Economics and Political Science. In 1913 it became the Department of Applied Economics and Social Science; in 1924 it became the Department of Economics, History, and Sociology; in 1931 it became the Department of Economics and Sociology. In 1967 it became the Department of Economics, and in 2007 it became co-directed by the Colleges of Agriculture and Life Sciences, Liberal Arts and Sciences, and Business.

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1898–present

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  • Department of Economic Science (1898–1910)
  • Department of Economics and Political Science (1910-1913)
  • Department of Applied Economics and Social Science (1913–1924)
  • Department of Economics, History and Sociology (1924–1931)
  • Department of Economics and Sociology (1931–1967)

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Abstract

This dissertation is a collection of three essays that focus on problems concerning uncertainty, learning, and welfare measurement in resource and environmental economics. Each essay focuses on a separate aspect of these problems. The first essay analyzes search, learning, and economic performance in a dynamic fishing game played by independent fishermen and by members of a stylized fishing cooperative. This paper extends our understanding of the behavior of fishermen operating in a fishing cooperative and highlights the importance of the design of fishing policy to promote their use. Devising contracts that result in optimal investment in information may be particularly challenging in fisheries, due to the club good characteristic of information, its costly acquisition, and the common property nature of the fishery resource. Contracts commonly used to prevent effort-shirking introduce a free-riding problem on the costly information investments of other members. The second essay presents a dynamic transition model to study the economic fundamentals that determine the path from an initially over-capitalized fishery to the long run cost-efficient fleet structure after the introduction of an individual transferable quota (ITQ) program. The results suggest that beliefs play a strong role on the transition. Uncertainty by fishermen over their relative cost-efficiency translates into uncertainty over quota trading prices. As such, a component of the ITQ asset's market price is speculation over future trading prices. Heterogeneous uncertainty and learning also provide insight into the observed pattern of vessel exit, generating new insight into the slow transition observed in U.S. fisheries. These results should be of interest to policy makers. The near universal practice of allocating the initial endowment of quota based on historic catch promotes delayed-exit strategies on cost-inefficient vessels and thereby prolongs the transition period during which the fully efficiency benefits of ITQ management are unrealized. The third essay uses the cleanup of Luke Air Force Base (a deleted Superfund site in Maricopa County, AZ) as a quasi-experiment to perform inside sample and outside sample validation exercises on the pure-characteristics vertical sorting model. Based on these validation exercises, the average bias (absolute deviation) on housing expenditures is approximately 20% and nearly 25% for income. In this setting, the model appears to predict the movement of population shares, but tends to under-predict the housing prices in response to remediation of the Superfund site. The spatial distribution of welfare is also a feature of the structure of the vertical sorting model.

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Sat Jan 01 00:00:00 UTC 2011