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

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  • Riccardo Scarpa
  • Danny Campbell
  • W. George Hutchinson

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.

Suggested Citation

  • Riccardo Scarpa & Danny Campbell & W. George Hutchinson, 2007. "Benefit Estimates for Landscape Improvements: Sequential Bayesian Design and Respondents’ Rationality in a Choice Experiment," Land Economics, University of Wisconsin Press, vol. 83(4), pages 617-634.
  • Handle: RePEc:uwp:landec:v:83:y:2007:i:4:p:617-634
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    References listed on IDEAS

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    1. Danny Campbell & George Hutchinson & Riccardo Scarpa, 2006. "Using mixed logit models to derive individual-specific WTP estimates for landscape improvements under agri-environmental schemes: evidence from the Rural Environment Protection Scheme in Ireland," Working Papers 0607, Rural Economy and Development Programme,Teagasc.
    2. Pruckner, Gerald J, 1995. "Agricultural Landscape Cultivation in Austria: An Application of the CVM," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 22(2), pages 173-190.
    3. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
    4. Giles Atkinson & Brett Day & Susana Mourato & Charles Palmer, 2004. "'Amenity' or 'eyesore'? Negative willingness to pay for options to replace electricity transmission towers," Applied Economics Letters, Taylor & Francis Journals, vol. 11(4), pages 203-208.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    6. Bjorklund, Johanna & Limburg, Karin E. & Rydberg, Torbjorn, 1999. "Impact of production intensity on the ability of the agricultural landscape to generate ecosystem services: an example from Sweden," Ecological Economics, Elsevier, vol. 29(2), pages 269-291, May.
    7. 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.
    8. Coiner, Colette & Wu, JunJie & Polasky, Stephen, 2001. "Economic and environmental implications of alternative landscape designs in the Walnut Creek Watershed of Iowa," Ecological Economics, Elsevier, vol. 38(1), pages 119-139, July.
    9. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    10. Hellerstein, Daniel & Nickerson, Cynthia J. & Cooper, Joseph C. & Feather, Peter & Gadsby, Dwight M. & Mullarkey, Daniel J. & Tegene, Abebayehu & Barnard, Charles H., 2002. "Farmland Protection: The Role Of Public Preferences For Rural Amenities," Agricultural Economics Reports 33963, United States Department of Agriculture, Economic Research Service.
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    More about this item

    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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