Multi‐Level Modelling and Contingent Valuation

Ian H. Langford and Ian J. Bateman

in Valuing Environmental Preferences

Published in print November 2001 | ISBN: 9780199248919
Published online November 2003 | e-ISBN: 9780191595950 | DOI:
 Multi‐Level Modelling and Contingent Valuation

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This chapter explores, in an introductory manner, the potential advantages of using multi‐level modelling in a range of contingent valuation (CV) survey designs. Section 12.2 briefly reviews the theoretical basis of the generalized linear model (GLM) most often used to model dichotomous‐choice (DC) willingness‐to‐pay data, namely, the logistic regression model. The reasons this model may not provide an adequate description of the data are discussed in Sect. 12.3, while Sect. 12.4 describes the statistical basis of random coefficient models as an extension to GLMs. Section 12.5 systematically develops an example of a random coefficient model called a multi‐level model, using data from a survey undertaken on the Norfolk Broads (a wetland resource in eastern England); the implications of using a multi‐level model are discussed in Sect. 12.6, and other applications are suggested. A summary of the main conclusions is given in Sect. 12.7.

Keywords: contingent valuation; dichotomous‐choice; generalized linear models; logistic regression models; multi‐level models; random coefficient models; survey designs; willingness to pay

Chapter.  7364 words. 

Subjects: Economic Development and Growth

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