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Spatial heterogeneity of willingness to pay for forest management

Author

Listed:
  • Mikołaj Czajkowski

    (Faculty of Economic Sciences, University of Warsaw)

  • Wiktor Budziński

    (Faculty of Economic Sciences, University of Warsaw)

  • Danny Campbell

    (University of Stirling, Stirling Management School, Economics Division)

  • Marek Giergiczny

    (Faculty of Economic Sciences, University of Warsaw)

  • Nick Hanley

    (University of St Andrews, School of Geography and Sustainable Development)

Abstract

The paper investigates spatial heterogeneity of the public’s preferences for the implementation of a new country-wide forest management and protection program in Poland. Spatial econometric methods and high resolution geographical information system (GIS) data related to forest characteristics are used to explain individual-specific willingness to pay (WTP) values, derived from a discrete choice experiment (DCE) study. We find that respondents’ WTP is higher the closer they live to their nearest forest, and the scarcer forests are in the area where they live. Interestingly, the more highly ecologically valuable forests in respondents’ area, the more they prefer extending areas of national forest protection. In addition, we investigate spatial patterns in individual-specific WTP scores and in latent class membership probabilities, finding that preferences are indeed spatially clustered. We argue that this clustering should be taken into account in both benefits analysis and policy-making.

Suggested Citation

  • Mikołaj Czajkowski & Wiktor Budziński & Danny Campbell & Marek Giergiczny & Nick Hanley, 2015. "Spatial heterogeneity of willingness to pay for forest management," Working Papers 2015-06, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2015-06
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    More about this item

    Keywords

    discrete choice experiment; contingent valuation; willingness to pay; spatial heterogeneity of preferences; forest management; passive protection; litter; tourist infrastructure; mixed logit; Kriging; spatial-lag;
    All these keywords.

    JEL classification:

    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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