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by Christos Makriyannis
Institution: | Clark University |
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Year: | 2017 |
Keywords: | Climate change; Environmental economics; Economics |
Posted: | 02/01/2018 |
Record ID: | 2155264 |
Full text PDF: | http://pqdtopen.proquest.com/#viewpdf?dispub=10256024 |
This dissertation comprises of three papers that address the use of stated preference (SP) choice experiment techniques to better understand how people value the methods and consequences of alternative climate change adaptation strategies. Specifically, it addresses two fundamental issues coastal communities face when making adaptation decisions: 1) tradeoffs between natural systems and built assets and 2) uncertainty regarding future climatic conditions. These issues pose methodological challenges for SP research, with potentially significant welfare and policy implications. The first chapter explores how survey choice scenarios should be designed to generate valid and well-defined welfare estimates given the causally related biophysical processes underlying the tradeoffs between natural systems and built assets. The second chapter explores whether and how the provision of numerical probabilities associated with future climatic conditions helps respondents make more informed choices. The final chapter investigates the implications for welfare estimation of using choice scenarios that provide multiple outcomes of the risk-related attribute compared to the two-outcome approach currently standard in the literature. Chapter 1 first presents a theoretical model that clarifies why valuation scenarios must include information on all primary ecological and protection outcomes to generate unbiased welfare estimate for coastal adaptation methods. I subsequently use valuation scenarios consistent with this theoretical model to generate welfare estimates for adaptation methods in two coastal New England towns (Old Saybrook and Waterford). This work therefore makes use of advances in the ecosystem service valuation literature to contribute to the growing SP literature that generates willingness-to-pay (WTP) estimates for climate change adaptation. I find that residents are willing to pay relatively large amounts for the protection of natural systems, even in the absence of any additional flood protection to private homes. In contrast, I find no evidence that residents are willing to pay for increased hard defenses alone, even in the absence of negative effects on natural systems. Chapter 2 contributes to a small but growing literature which finds that embedding numerical probabilities in valuation scenarios influences welfare estimates. I argue that it is not clear whether this influence is due to numerical probabilities per se or due to increased choice task complexity. To explore whether numerical probabilities alone influence welfare estimates, presumably helping respondents make more informed choices, I compare the results of one survey which provides numerical probabilities prior to valuation scenarios to those of an otherwise identical survey that altogether omits numerical probabilities. I find that the two surveys yield statistically indistinguishable WTP values. This suggests that lay individuals may not process numerical probabilities as expected by researchers, a result consistent with numerous
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