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Recreational Benefits from Improved Water Quality: A Random Utility Model of Swedish Seaside Recreation

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  • Sandström, Mikael

    (Department of Economics)

Abstract

In this paper, a random utility maximization (RUM) model of Swedish seaside recreation is used to estimate the benefits from reduced eutrophication of the seas around Sweden. Sight depth data from around the Swedish coast are used as a quality index related to eutrophication. The model is estimated using the nested multinomial logit (NMNL) and conditional logit (CL) specifications. In order to test the relationship between this quality variable and the nutrient concentration in the water, a regression of sight depth on the concentration of phosphorus and nitrogen has been run. The results are used to make policy simulations. Two sets of such simulations have been undertaken. One set assumes a uniform change of the nutrient load along the entire Swedish coastline. The consumer surplus from a reduction of the nutrient load by 50 percent is estimated to be around 140 mSEK if the NMNL model is used, and 540 mSEK if the CL model is used. The other set of policy simulations assumes a change in the nutrient load in the Laholm Bay in south-west Sweden. The consumer surplus for a 50 percent reduction in the nutrient load in the bay is estimated to be 12 mSEK if the NMNL model is used, and 32 mSEK if the CL model is used.

Suggested Citation

  • Sandström, Mikael, 1996. "Recreational Benefits from Improved Water Quality: A Random Utility Model of Swedish Seaside Recreation," SSE/EFI Working Paper Series in Economics and Finance 121, Stockholm School of Economics.
    • Handle: RePEc:hhs:hastef:0121
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    Cited by:

    1. Ahtiainen, Heini & Vanhatalo, Jarno, 2012. "The value of reducing eutrophication in European marine areas — A Bayesian meta-analysis," Ecological Economics, Elsevier, vol. 83(C), pages 1-10.
    2. Eric Nævdal, 2001. "Optimal Regulation of Eutrophying Lakes, Fjords, and Rivers in the Presence of Threshold Effects," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(4), pages 972-984.
    3. Bertram, Christine & Rehdanz, Katrin, 2013. "On the environmental effectiveness of the EU Marine Strategy Framework Directive," Marine Policy, Elsevier, vol. 38(C), pages 25-40.
    4. Turo Hjerppe & Elina Seppälä & Sari Väisänen & Mika Marttunen, 2017. "Monetary assessment of the recreational benefits of improved water quality – description of a new model and a case study," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 60(11), pages 1944-1966, November.
    5. Mikołaj Czajkowski & Wiktor Budziński & Marianne Zandersen & Wojciech Zawadzki & Uzma Aslam & Ioannis Angelidis & Katarzyna Zagórska, 2024. "The Recreational Value of the Baltic Sea Coast: A Spatially Explicit Site Choice Model Accounting for Environmental Conditions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(1), pages 135-166, January.
    6. Stina Hökby & Tore Söderqvist, 2003. "Elasticities of Demand and Willingness to Pay for Environmental Services in Sweden," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 26(3), pages 361-383, November.
    7. Mikołaj Czajkowski & Marianne Zandersen & Uzma Aslam & Ioannis Angelidis & Thomas Becker & Wiktor Budziński & Katarzyna Zagórska, 2018. "Recreational Value of the Baltic Sea: a Spatially Explicit Site Choice Model Accounting for Environmental Conditions," Working Papers 2018-11, Faculty of Economic Sciences, University of Warsaw.
    8. Catalina M. Torres Figuerola & Antoni Riera Font, 2009. "Defining environmental attributes as external costs in choice experiments: A discussion," CRE Working Papers (Documents de treball del CRE) 2009/1, Centre de Recerca Econòmica (UIB ·"Sa Nostra").

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    More about this item

    Keywords

    random utility; recreation; water; Baltic Sea; eutrophication; discrete choice;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water
    • Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources

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