This paper examines formal wilderness designation and is presented in two parts. The first section offers a general classification and comprehensive review of the benefit and cost variables associated with wilderness designation and management. The second section investigates recreation use, which society has historically perceived to be the highest valued element in the network of wilderness benefits. Variables associated with the benefits of wilderness designation are presented under three major categories: 1) naturalness preservation, 2) solitude or primitive and unconfined types of recreation, and 3) special features of scientific, educational, scenic, or historic value. Costs attributed to wilderness designation are presented under two major categories: 1) administration/general management costs and 2) opportunity costs. The second section of this thesis establishes growth rate comparisons of wilderness and non-wilderness recreation use on United States Forest Service lands in Utah, the Intermountain Region, and the overall national Forest Service system from 1967 to 1986. The High Uintas Wilderness area was also analyzed for its use over the same twenty-year period. Data used to measure recreational use at these levels was obtained from United States Forest Service Recreation Information Management records and are measured in recreational visitor days. Growth rate comparisons are measured with respect to recreation use in general terms as well as on a per acre basis at all levels examined. Because of general trend discrepancies in recreation use over the twenty-year study period, growth rate estimates of recreation use at all levels are also measured with respect to two separate time periods--1967 to 1976 and 1977 to 1986. This analysis shows that non-wilderness/ primitive recreation use per acre increased during the last decade at all levels examined, whereas wilderness/primitive .recreation use per acre showed marked declines during the same period. Growth rate estimates established on a per acre basis provide a general indication of the marginal value of wilderness and non-wilderness recreation use. This thesis shows that, with respect to recreation use, marginal utility has diminished in designated wilderness since 1977. In contrast, this research also infers that the marginal value for non-wilderness recreation use has increased. These findings suggest that, from a recreation perspective, adding wilderness areas to the National Wilderness Predervation System is unwarranted.

The secondary or external benefits of increasing the availability of water for irrigation and changing the allocation of an existing water supply was analyzed from a theoretical point of view. " Input-output" models for Cache County, Utah, and for the stat e of Utah were us ed to indicate the intersectoral relationship of water used by agriculture and other sectors in each economy. The indirect value of water used by agriculture in Cache County was estimated. A method that extended the procedure used in this thesis was proposed that could be used to estimate the value of water in ether sectors. A "water matrix" was used to indicate reasons why large allocations of water to agriculture may be economically justified.

京都大学 / 0048 / 新制・課程博士 / 博士(社会健康医学) / 甲第19639号 / 社医博第72号 / 新制||社医||9(附属図書館) / 32675 / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 今中 雄一, 教授 佐藤 俊哉, 教授 木原 正博 / 学位規則第4条第1項該当 / Doctor of Public Health / Kyoto University / DFAM

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<p> This dissertation focuses on young people's and staffs discourses about, and participation in, day treatment mental health programs in Ontario. These experiences and perspectives are situated within broader structural contexts of power, policy and societal expectations. In doing so, I adapt and update Scheper-Hughes and Lock's (1987) Three Bodies model as an overarching structure for the thesis. I differ from their distinct division between the three bodies as my grounded theory approach to fieldwork data highlights the relational aspects of therapeutic practices, and in turn I draw attention to the interaction between and within Scheper-Hughes and Lock's individual-social-politic bodies. </p> <p> I completed fieldwork at two services, one for 13-18 and one for 5-12 year olds. These institutional settings are primarily concerned with (re)creating mental health and educational well-being. As such both they and my research are at the intersection of multiple academic disciplines, which means that my dissertation draws heavily on a variety of anthropological, sociological and childhood studies literatures and methodologies, as well as on influences from psychiatry and psychology, in addition to a broad range of post-structuralist I post-modem theorizing. </p> <p> In addition to this academic approach, my work has applicability, which was necessitated in part by the fieldwork sites' demand that they see benefits from research. My applied approach was also necessitated by my position that anthropological research can fruitfully combine both applied and academic approaches to research, known as praxis. </p> <p> Key issues addressed within my thesis are: the need for multiple qualitative methodologies, both to address questions around working with young people and questions arising from fieldwork sites primarily informed by quantitative research; the usefulness of combining aspects from the theoretical work of Bourdieu and Foucault in understanding how mental health therapies act to reenculturate young people; the importance of the role that the young people play in their own therapeutic recovery which I explore through my concept of con.fined agency; that (perhaps surprisingly) rites de passage and liminality can be useful conceptual frameworks to approach the sociality of individual bodies in the daily material activities at the fieldwork sites; and the negotiation by young people and staff of the ongoing negative impacts of stigma associated with mental illness. Within my ethnographic theorizing is the importance ofrelational interaction between individual-social-politic level bodies. </p> / Thesis / Doctor of Philosophy (PhD)

This dissertation introduces advanced statistical and econometric methods in two distinct areas of non-market valuation: benefit transfer (BT) and hedonic analysis. While the first and the third chapters address the challenge of estimating the societal benefits of prospective environmental policy changes by adopting locally weighted regression (LWR) technique in an environmental valuation context, the second chapter combines the output from traditional hedonic regression and matching estimators and provides guidance on the choice of model with low risk of bias in housing market studies. The economic and societal benefits associated with various environmental conservation programs, such as improvement in water quality, or increment in wetland acreages, can be directly estimated using primary studies. However, conducting primary studies can be highly resource-intensive and time-consuming as they typically involve extensive data collection, sophisticated models, and a considerable investment of financial and human resources. As a result, BT offers a practical alternative, which involves employing valuation estimates, functions, or models from prior primary studies to predict the societal benefit of conservation policies at a policy site. Existing studies typically fit one single regression model to all observations within the given metadata and generate a single set of coefficients to predict welfare (willingness-to-pay) in a prospective policy site. However, a single set of coefficients may not reflect the true relationship between dependent and independent variables, especially when multiple source studies/locations are involved in the data-generating process which, in turn, degrades the predictive accuracy of the given meta-regression model (MRM). To address this shortcoming, we employ the LWR technique in an environmental valuation context. LWR allows an estimation of a different set of coefficients for each location to be used for BT prediction. However, the empirical exercise carried out in the existing literature is rigorous from a computational perspective and is cumbersome for practical adaptation. In the first chapter, we simplify the experimental setup required for LWR-BT analysis by taking a closer look at the choice of weight variables for different window sizes and weight function settings. We propose a pragmatic solution by suggesting "universal weights" instead of striving to identify the best of thousands of different weight variable settings. We use the water quality metadata employed in the published literature and show that our universal weights generate more efficient and equally plausible BT estimates for policy sites than the best weight variable settings that emerge from a time-consuming cross-validation search over the entire universe of individual variable combinations. The third chapter expands the scope of LWR to wetland meta-data. We use a conceptually similar set of weight variables as in the first chapter and replicate the methodological approach of that chapter. We show that LWR, under our proposed weight settings, generates substantial gain in both predictive accuracy and efficiency compared to the one generated by standard globally-linear MRM. Our second chapter delves into a separate yet interrelated realm of non-market valuation, i.e., hedonic analysis. Here, we explore the combined inferential power of traditional hedonic regression and matching estimators to provide guidance on model choice for housing market studies where researchers aim to estimate an unbiased binary treatment effect in the presence of unobserved spatial and temporal effects. We examine the potential sources of bias within both hedonic regression and basic matching. We discuss the theoretical routes to mitigate these biases and assess their feasibility in practical contexts. We propose a novel route towards unbiasedness, i.e., the "cancellation effect" and illustrate its empirical feasibility while estimating the impact of flood hazards on housing prices. / Doctor of Philosophy / This dissertation introduces novel statistical and econometric methods to better understand the value of environmental resources that do not have an explicit market price, such as the benefits we get from the changes in water quality, size of wetlands, or the impact of flood risk zoning in the sales price of residential properties. The first and third chapters tackle the challenge of estimating the value of environmental changes, such as cleaner water or more wetlands. To figure out how much people benefit from these changes, we can look at how much they would be willing to pay for such improved water quality or increased wetland area. This typically requires conducting a primary survey, which is expensive and time-consuming. Instead, researchers can draw insights from prior studies to predict welfare in a new policy site. This approach is analogous to applying a methodology and/or findings from one research work to another. However, the direct application of findings from one context to another assumes uniformity across the different studies which is unlikely, especially when past studies are associated with different spatial locations. To address this, we propose a ``locally-weighting" technique. This places greater emphasis on the studies that closely align with the characteristics of the new (policy) context. Determining the weight variables/factors that dictate this alignment is a question that requires an empirical investigation. One recent study attempts this locally-weighting technique to estimate the benefits of improved water quality and suggests experimenting with different factors to find the similarity between the past and new studies. However, their approach is computationally intensive, making it impractical for adaptation. In our first chapter, we propose a more pragmatic solution---using a "universal weight" that does not require assessing multiple factors. With our proposed weights in an otherwise similar context, we find more efficient and equally plausible estimates of the benefits as previous studies. We expand the scope of the local weighting to the valuation of gains or losses in wetland areas in the third chapter. We use a conceptually similar set of weight variables and replicate the empirical exercise from the first chapter. We show that the local-weighting technique, under our proposed settings, substantially improves the accuracy and efficiency of estimated benefits associated with the change in wetland acreage. This highlights the diverse potential of the local weighting technique in an environmental valuation context. The second chapter of this dissertation attempts to understand the impact of flood risk on housing prices. We can use "hedonic regression" to understand how different features of a house, like its size, location, sales year, amenities, and flood zone location affect its price. However, if we do not correctly specify this function, then the estimates will be misleading. Alternatively, we can use "matching" technique where we pair the houses inside and outside of the flood zone in all observable characteristics, and differentiate their price to estimate the flood zone impact. However, finding identical houses in all aspects of household and neighborhood characteristics is practically impossible. We propose that any leftover differences in features of the matched houses can be balanced out by considering where the houses are located (school zone, for example) and when they were sold. We refer to this route as the "cancellation effect" and show that this can indeed be achieved in practice especially when we pair a single house in a flood zone with many houses outside that zone. This not only allows us to accurately estimate the effect of flood zones on housing prices but also reduces the uncertainty around our findings.

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