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Valuing a Spatially Variable Environmental Resource: Reducing Non-Point-Source Pollution in Green Bay, Wisconsin

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  • Rebecca Moore
  • Bill Provencher
  • Richard C. Bishop

Abstract

This article investigates the value of reducing non-point-source pollution in Green Bay, Wisconsin. Using stated preference methods, we find the lower bound on the benefits of reducing runoff enough to universally increase water clarity by 4 ft is greater than $10 million annually. Using a unique survey design, we show that because current water clarity in Green Bay is spatially variable, the value that a household places on this universal improvement depends on the distance of the household’s residence from the bay and on the particular geospatial location of the residence. This has important implications for estimating aggregate benefits.

Suggested Citation

  • Rebecca Moore & Bill Provencher & Richard C. Bishop, 2011. "Valuing a Spatially Variable Environmental Resource: Reducing Non-Point-Source Pollution in Green Bay, Wisconsin," Land Economics, University of Wisconsin Press, vol. 87(1), pages 45-59.
    • Handle: RePEc:uwp:landec:v:87:y:2011:i:1:p:45-59
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    Cited by:

    1. He, Jie & Huang, Anping & Xu, Luodan, 2015. "Spatial heterogeneity and transboundary pollution: A contingent valuation (CV) study on the Xijiang River drainage basin in south China," China Economic Review, Elsevier, vol. 36(C), pages 101-130.
    2. Ladenburg, Jacob, 2014. "Dynamic properties of the preferences for renewable energy sources – A wind power experience-based approach," Energy, Elsevier, vol. 76(C), pages 542-551.
    3. Nielsen, Anne Sofie Elberg & Lundhede, Thomas Hedemark & Jacobsen, Jette Bredahl, 2016. "Local consequences of national policies - A spatial analysis of preferences for forest access reduction," Forest Policy and Economics, Elsevier, vol. 73(C), pages 68-77.
    4. George Parsons & Kelley Myers, 2017. "Fat tails and truncated bids in contingent valuation: an application to an endangered shorebird species," Chapters, in: Daniel McFadden & Kenneth Train (ed.), Contingent Valuation of Environmental Goods, chapter 2, pages 17-42, Edward Elgar Publishing.
    5. Ladenburg, Jacob & Lutzeyer, Sanja, 2012. "The economics of visual disamenity reductions of offshore wind farms—Review and suggestions from an emerging field," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(9), pages 6793-6802.
    6. Norton, Daniel & Hynes, Stephen, 2018. "Estimating the Benefits of the Marine Strategy Framework Directive in Atlantic Member States: A Spatial Value Transfer Approach," Ecological Economics, Elsevier, vol. 151(C), pages 82-94.
    7. Tagliafierro, C. & Boeri, M. & Longo, A. & Hutchinson, W.G., 2016. "Stated preference methods and landscape ecology indicators: An example of transdisciplinarity in landscape economic valuation," Ecological Economics, Elsevier, vol. 127(C), pages 11-22.
    8. Jørgensen, Sisse Liv & Olsen, Søren Bøye & Ladenburg, Jacob & Martinsen, Louise & Svenningsen, Stig Roar & Hasler, Berit, 2013. "Spatially induced disparities in users' and non-users' WTP for water quality improvements—Testing the effect of multiple substitutes and distance decay," Ecological Economics, Elsevier, vol. 92(C), pages 58-66.
    9. Lewis, David J. & Provencher, Bill & Beardmore, Ben, 2015. "Using an intervention framework to value salient ecosystem services in a stated preference experiment," Ecological Economics, Elsevier, vol. 114(C), pages 141-151.

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    More about this item

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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