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Benefit Estimates for Landscape Improvements: Sequential Bayesian Design and Respondents’ Rationality in a Choice Experiment

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Author Info
Riccardo Scarpa
Danny Campbell
W. George Hutchinson

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Abstract

A multi-attribute, stated-preference approach is used to value low and high impact actions on four major landscape components addressed by the Rural Environment Protection Scheme in Ireland. Several methodological issues are addressed: the use of prior beliefs on the relative magnitudes of parameters, standardized description of different levels of landscape improvements via image manipulation software, adoption of efficiency-increasing sequential experimental design, and sensitivity of benefit estimates to inclusion of responses from ‘‘irrational’’ respondents. Results suggest that Bayesian design updating delivers significant efficiency gains without loss in respondent efficiency, and estimates are upward-biased when irrational respondents are included.

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File URL: http://le.uwpress.org/cgi/reprint/83/4/617
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Publisher Info
Article provided by University of Wisconsin Press in its journal Land Economics.

Volume (Year): 83 (2007)
Issue (Month): 4 ()
Pages: 617-634
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Handle: RePEc:uwp:landec:v:83:y:2007:i:4:p:617-634

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Related research
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Find related papers by JEL classification:
Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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  1. Silvia Ferrini & Riccardo Scarpa, 2005. "Experimental Designs for Environmental Valuation with Choice-Experiments: A Monte-Carlo Investigation," Working Papers in Economics 05/08, University of Waikato, Department of Economics. [Downloadable!]
  2. Campbell, Danny, 2007. "Combining mixed logit models and random effects models to identify the determinants of willingness to pay for rural landscape improvements," 81st Annual Conference, April 2-4, 2007, Reading University 7975, Agricultural Economics Society. [Downloadable!]
  3. Danny Campbell & W. George Hutchinson & Riccardo Scarpa, 2006. "Using Discrete Choice Experiments to Derive Individual-Specific WTP Estimates for Landscape Improvements under Agri-Environmental Schemes: Evidence from the Rural Environment Protection Scheme in Irel," Working Papers 2006.26, Fondazione Eni Enrico Mattei. [Downloadable!]
  4. Stephane Hess & John Rose, 2009. "Should Reference Alternatives in Pivot Design SC Surveys be Treated Differently?," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 42(3), pages 297-317, March. [Downloadable!] (restricted)
  5. Danny Campbell & Riccardo Scarpa & W. Hutchinson, 2008. "Assessing the spatial dependence of welfare estimates obtained from discrete choice experiments," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer, vol. 1(2), pages 117-126, December. [Downloadable!] (restricted)
    Other versions:
  6. John M. Rose & Riccardo Scarpa, 2007. "Designs Efficiency for Non-market Valuation with Choice Modelling: How to Measure It, What to Report and Why," Working Papers in Economics 07/21, University of Waikato, Department of Economics. [Downloadable!]
  7. Danny Campbell & W. George Hutchinson & Riccardo Scarpa, 2006. "Lexicographic Preferences in Discrete Choice Experiments: Consequences on Individual-Specific Willingness to Pay Estimates," Working Papers 2006.128, Fondazione Eni Enrico Mattei. [Downloadable!]
  8. Marsh, Dan & Baskaran, Ramesh, 2009. "Valuation of Water Quality Improvements in the Karapiro Catchment: A Choice Modelling Approach," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47951, Australian Agricultural and Resource Economics Society. [Downloadable!]
  9. Marit E. Kragt & Jeff Bennett, 2008. "Developing a Questionnaire for Valuing Changes in Natural Resource Management in the George Catchment, Tasmania," Environmental Economics Research Hub Research Reports 0808, Environmental Economics Research Hub, Crawford School, Australian National University. [Downloadable!]
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