Walking tracks with provision for overnight stays exist in many countries. They are a tourism drawcard and some (e.g. the Milford Track in New Zealand) have icon status. In Australia, long-distance tracks exist in most states but had not until recently been developed in north Queensland. The working hypothesis for this thesis is that a new long-distance walking track in the tropical rainforest environment could be a valuable recreation asset for the region, and a major tourism attractor. Since a long-distance walking track in a natural environment would be situated in a rural region away from major cities, there is potential for tourism expenditure by long-distance hikers to contribute positively to the economy of remote towns. It is proposed that a walking track can be created relatively easily in the rainforests if disused former logging roads are used as the basis. The new walking track on a logging road base could be developed at moderate cost, and with minimal ecological and environmental disturbance. A new track created within a protected natural area is usually regarded as a public good and most associated costs may be considered to be appropriately funded through the taxation system. However, it may be argued that the recreational use of a long-distance walking track provides benefits to those who use it, and that hikers should contribute towards the recovery of managerial costs. An appropriate level of user fee may be obtained from a market model. In this thesis, an annual market model is estimated for the recreation service which provides a short-term efficient price. A long-distance walking track is an investment in recreation infrastructure the benefits of which are intergenerational. Thus efficiency in the long-term is also an important consideration. Both a static analysis and cost-benefit dynamic analysis are presented in this thesis. When a track does not exist (as was the case in north Queensland when this thesis commenced) or when it is under construction (as when the thesis was nearing completion), direct evaluation is not possible and so demand (consumer surplus) and supply (marginal cost of recreation service) estimates for a new track must be obtained from other sources. A key original contribution in this thesis is the application of economic transfer to derive a market model for a proposed recreation service infrastructure item, and a further application of economic transfer involves the use of the benefit level from the market model as an input into the cost-benefit analysis. Demand estimates have been obtained from surveys of visitors on two other walking tracks in north Queensland. Zonal travel cost methodology has been applied to the survey data to develop demand curves for these long-distance hiking opportunities and measures of value in terms of consumer surplus. Zonal rather than individual travel cost was necessary since most respondents were walking the particular track for the first time. Since the Centenary of Federation in Australia in 2001, when seed funding was made available, some new long-distance walking tracks have been developed in the Queensland Wet Tropics World Heritage Area. One of these has been selected as the case study developing track for this thesis. Demand and cost estimates for the new trail have been transferred, with appropriate adjustments, from the studies conducted on the two other trails. An interesting feature in this transfer process is that close substitutes exist for the target walking track but not for either of the two source walking tracks. An innovation in this thesis is the development of a market model for the new track. Two market models are derived, one from each of the source tracks, and are used to determine the socially efficient price and visitation levels. These may be used by management as a basis for the setting of user fees. The equilibrium values obtained from the static analysis have also been incorporated into the dynamic analysis together with the consumer surplus estimates from the travel cost demand curve. The equilibrium quantities provide the basis for an estimate of the visitation level expected for the new track on which many of the continuing management costs depend. Two scenarios (with and without hut infrastructure) have been investigated in cost-benefit analyses. Both scenarios were found to be economically worthwhile.

Researchers often invoke strong assumptions in empirical analyses to identify significant statistical outcomes. Invoking assumptions that do not sufficiently reflect the occurrence of true phenomenon reduces the credibility of inferences. Literature suggests that the potential effects of assumptions on credibility of inferences can be mitigated by comparing and combining insights from alternative econometric models. I use this recommendation to conduct robustness checks of commonly used methods in environmental and health economics. The first chapter proposes a novel nonparametric regression model to draw credible insights from meta-analyses. Existing literature on benefit-transfer validity is examined as an application. Nonparametric regression is found to be a viable approach for drawing robust policy insights. The second chapter proposes an alternative structural and simulations based framework to understand elicitation effects in survey response data. This analysis explains the structural mechanisms in which response anomalies occur and is important for building credible insights from survey data. The last chapter uses methods in program evaluation to investigate the impacts of institutional child deliveries on long-term maternal health in the context of developing countries. The outcomes of this analysis indicate that institutional deliveries positively affect maternal health in lower socio-economic states. Based on the findings of my three chapters, I recommend that researchers should combine insights from alternative models to mitigate the scope of specification bias in empirical outcomes and inform policy about the potential uncertainty that arises in uncovering the truth using statistical methods. / Ph. D.

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.

No description available.

Biofuel production-driven land-use change in agricultural land can have impacts on ecosystem services. Since there is no planned mandate after the Renewable Fuel Standard, there are questions about what implications will future land-use changes have on water quality and how do water quality changes, resulting from potential bioenergy scenarios, affect changes in people's well-being? To answer these questions, I will estimate the value of the predicted changes in water quality under biofuel policy scenarios in counties inside the Mississippi River Basin. From this study, I found that as the percent of land-use changes increase across each county, water quality decreased. I also found that for every unit increase for the change in water quality index, the percentage of individuals' willingness to pay for a change in water quality would increase. The predicted willingness to pay for a change in water quality for a given household varied from -$72 to $143.

Ziel der volkswirtschaftlichen Analyse des Precision Farming ist es, quantitativ untermauerte Aussagen bzgl. einer staatlichen Förderung der Precision Farming-Technologie zu treffen. So sind über die Methode der Nutzen-Kosten-Analyse alle relevanten Projektwirkungen identifiziert worden. Die Quantifizierung der direkten Wirkungen erfolgte am Beispiel der „Wulfen-Studie“ (Region Köthen, Sachsen-Anhalt). Für die indirekten Umweltwirkungen ist in einem ersten Schritt eine naturschutzfachliche Bewertung von Umweltgütern auf der Basis von Experteneinschätzungen erfolgt. Im zweiten Schritt wurden den einzelnen indirekten Umweltwirkungen monetäre Studienwerte aus der Literatur zugeordnet (benefit transfer). Nach Prüfen der Sensitivität und Erfassung der Intangibles zeigt die Gegenüberstellung der Nutzen und Kosten des Precision Farming, dass der Nettonutzen im Durchschnitt über die Untersuchungsjahre von +24,91 €/ha bis zu +244,80 €/ha variiert. Der Entwurf eines Heterogenitätsindikators zur Beschreibung der Beziehung zwischen Nettonutzen und Heterogenität eines Schlages führte zur Darstellung einer Heterogenitätsverteilung in Ostdeutschland. Unter der Annahme, dass die Ergebnisse der Fallstudie Wulfen auch repräsentativ für andere Regionen in Deutschland seien, erfolgte eine aussagekräftige Hochrechnung des Netto-nutzen/ha für Ostdeutschland mit einem durchschnittlichen Nettonutzen einer Einführung von Precision Farming von 45,6 Mio. €. Aufgrund der vielfältigen positiven Umweltwirkungen des Precision Farming kann eine staatliche Förderung des Precision Farming durchaus als legitim erachtet werden, besonders unter Berücksichtigung der hohen Investitionskosten für die Technik. Da unsere Aussagen aber auf vielen Annahmen beruhen, kann von dieser Stelle aus eine staatliche Förderung des Precision Farming nicht empfohlen werden. Dazu bedürfe es weiterer Forschungsarbeit. / The nationwide introduction of precision farming in Germany as a new technology in agriculture depends crucially on the incentives set by the government. Therefore, the economical analysis (cost benefit analysis) of the effects of precision farming is chosen to promote precision farming in Germany. One of the core elements of cost benefit analysis is the identification and quantification of the effects of precision farming in Germany. The direct quantification was carried out by the example of the "Wulfen study" (region Koethen, Saxonia-Anhalt). For the indirect environmental effects an experts estimation combined with a benefit analysis of those goods took place in a first step. In a second step monetary study values from literature were assigned to the individual indirect environmental effects (benefit transfer). After examining the sensitivity and the collection of the Intangibles, the net benefit of precision agriculture/ha was calculated. It varies from +24, 91 €/ha up to +244, 80 €/ha (average value over 3 years and two precision farming strategies). The regionalisation of the net benefit, calculated for the “Wulfen” region, was possible through the development of a heterogeneity indicator (HEI). This indicator describes the relationship between net benefit and site-specific heterogeneity. On the assumption that the results of the Wulfen case study are representative for other regions in Germany, the net benefit/ha was calculated to Eastern Germany. Thus does a net benefit of an introduction of precision farming on winter wheat in East Germany result of average 45,6 Mio €. Various positive environmental effects of precision agriculture appear, but with the high capital investment costs for the precision agriculture technology farmers won’t introduce this technology on their fields. Since our statements are based on many assumptions and restrictions, we cannot recommend however a national promotion of precision agriculture.

Decision making in environmental management is faced with uncertainties associated with related environmental variables and processes. Decision makers are inclined to use resources to acquire better information in one or more uncertain variable(s). Typically, with limited resources available, characterizing the feasibility of such investment is desirable yet complicated. In the context of reducing inherent uncertainty, decision makers need to tackle two difficult questions, first, the optimal selection of variable(s) and second, the optimal level of information collection which produces maximum gain in benefits. We develop a new framework to assess the socioeconomic value of potential decisions of collecting additional information for given variable(s) to reduce inherent uncertainty. The suggested framework employs advanced social welfare concepts to facilitate eliciting the social acceptability of decisions to collect better information. The framework produces estimates of changes in utility levels and willingness to pay for target population using the benefit transfer method. The practicality of the framework is established using the following common problems in the field of water resources: 1) the uncertainty in exposure to health risk due to drinking a groundwater source contaminated with a carcinogen, 2) the uncertainty in non point source pollution loadings due to unknown hydrologic processes variability, and 3) the equity level in allocating mitigation responsibilities among polluters. For the three applications, the social acceptability of potential decisions is expressed in monetary terms which represent an extension on typical cost benefit analysis by including the socioeconomic value of a decision. The specific contribution of this research is a theoretical framework for a detailed preliminary analysis to transform and represent the given problem in useable terms for the social welfare analysis. The practical framework is attractive because it avoids the need to employ prohibitively expensive survey-based contingent valuation methods. Instead, the framework utilizes benefit transfer method, which imposes a theoretical behavioral structure on population characteristics such as age and income and to produce empirical estimates for a new problem setting.

This study explicates Electronic Benefit Transfer (EBT) as a textually mediated discursive management tool. EBT is the mandatory method for food benefits and replaces the previous food stamp coupons, but the broad reaching significance is that this program is just a developmental infrastructure. The goal of the U.S. Treasury is for all government transactions, approximately $2.5 trillion a year, to be electronically conducted (National Performance Review 1993). To initiate the process, they set the first target as the 126 government benefit programs, including Social Security, Social Security, Veteran's Administration, Student Loans, Medicaid, Medicaid, Unemployment, even tax refunds. The food stamp program (now called SNAP) was selected to develop the foundational architecture of EBT. It is the forerunner of things to come. With every transaction, EBT collects data not about shopping activities or food purchases, but social and life activities that are used to construct an institutional hyperreality. EBT is to create invisible access to and uninterrupted use of data as hypertext to manufacture and orchestrate a discursive hyperreality and ideologically imagined users. These data are a social hypertext (Smith 1990, 1999). They are connected and arranged, and applied in very specific ways to communicate, activate, and articulate social and institutional relationships. They are used to represent not the lived experience but the institutional view. While they have meaning and use in their original form, hypertexts take on new proportion and significance in terms of social relations. Using institutional ethnography, I begin with the standpoint of the lived experiences of people with disabilities using EBT as the point of entry, then follow EBT's workings to reveal how it is shaping social relations and hegemonic restructuring. Topics covered include disability, age, welfare, privatization, data mining, data warehousing, and socio-technical systems and products. They lead to findings I conceptualize as hyperveillance: the use of data not just for surveillance and control, but to reify social constructs and orchestrate ruling relations. Hyperveillance is how data as hypertext are institutionally managed to invisibly insert and mediate power, mediate interdependent discursive linkages, and orchestrate social relations on both and individual and class level. To achieve this, I analytically explicate a five step Hyperveillance Circuit in terms of a digital dialectic. It begins with the swipe of the EBT card that generates the data (i.e., hypertext) and follows it through collection, analysis, ideological assemblage, and finally, its use to construct events in the institutional lens to reify hyperreality and sociological constructs. Along the hyperveillance circuit, I make analytical departure that informs broader social relations and hegemonic restructuring. This includes analytic indulgence to the fact that data as hypertext are mined, warehoused, and cross-matched with up to 2000 additional databases, and shared with other institutions and agencies for a virtually endless array of applications. At this point, I examine the implications of the ubiquitous and atemporal aspects of these practices of hyperveillance to include how they are changing social relations and how they contemporize foundational sociological concepts, especially objectification, interaction, and reification. Another analytical direction inculpates a hyperveillance industry: the government pays private companies to use the hypertext to manufacture socio-technical products that reify institutional ideology, then the companies further their profits and power by selling the products back to the government. These finding lead me to offer a Dynamic Model of Institutionalization as a research tool to explicate other digital discourses and socio-technical processes. It consists of three primary components - a target population, a dialectic of hypertext, and a legislated policy; ideology is used to unify and operationalize discursive workings. Throughout my work, the supporting analytical framework is digital discourse consisting of hypertext and what I conceptualize as hyperveillance. My research on EBT shows how hyperveillance is weaving itself into our social fabric as a way of life, and into ruling relations as an `improved' discursive approach. EBT has been uncontested and unrecognized as a discursive management tool and insertion of social and ruling relations. My research changes that, but what remains unanswered is the extent to which EBT, digital discourse, will ultimately change our social structure.

No description available.

Cooperative Extension produces public value through educational programming that benefits the greater community. Forests provide numerous valuable benefits to society through the provision of ecosystem services. Cooperative Extension educational programming positively impacts forest owners, who in turn conduct actions that enhance ecosystem services. A heretofore unrecognized relationship exists between Cooperative Extension and ecosystem services that provides opportunity for mutual benefit. Applying ecosystem services values to Extension natural resources-related programmatic outcomes through benefit transfer provides an avenue for Extension to make significant advancements in monetizing public value. Beyond serving simply as a source of financial justification, however, linkages with ecosystem services also provide Cooperative Extension with opportunities to improve the design and delivery of educational programs, do a better job articulating an array of public benefits resulting from agency accomplishments, and optimize allocation of sparse resources and Extension efforts. This dissertation thoroughly explores these concepts by providing an overview of: Cooperative Extension in general and Extension forestry more specifically; public value in an Extension context; ecosystem services; ecosystem services valuation; benefit transfer, and; connections between these diverse topics. In addition, benefit transfer principles are applied to an existing Extension evaluation data set in attempt to monetize Cooperative Extension's impact, lessons learned are explored, and the Cooperative Extension public value discussion is re-framed as one aspect of overall continuous organizational improvement. / Ph. D.