Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.408720
Title: Essays on non-market valuation of environmental resources : policy and technical explorations
Author: Kontoleon, Andreas
Awarding Body: University of London
Current Institution: University College London (University of London)
Date of Award: 2003
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Abstract:
This thesis consists of a portfolio of research papers examining key contemporary technical, methodological and policy issues on the use of non-market valuation in environmental decision-making. The introductory chapter provides a short discussion of the structure and general aims of the thesis. The rest of the thesis is divided into two parts. Part A (consisting of Chapters 2,3, and 4) contributes to the literature on the analysis and design of the two most commonly used stated preference methods, Contingent Valuation (CV) and Choice Modelling (CM). Chapter 2 examines the impacts of using alternative opt-out formats in CM studies, Chapter 3 presents a latent segmentation model as an alternative means of accounting for preference heterogeneity in discrete choice random utility models, while Chapter 4 introduces a generalised limited dependent variable modelling approach to account for non-trivial number of zero responses in open-ended type willingness to pay CV data. Part B (consisting of Chapters 5 and 6) contributes to the literature on the role of stated preferences in environmental policy and legal decisionmaking. Chapter 5 uses the CV method to examine the nature of wildlife values in the face of the ongoing policy debate between ex situ and in situ conservation. Lastly Chapter 6 seeks to assess the US experience with using non-market valuation in courts with the aim of providing suggestions as European legislators formulate the direction of the new EU environmental liability regime.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.408720  DOI: Not available
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