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A method for predicting participation in a performance-based water quality trading program

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Listed:
  • Duke, Joshua M.
  • Liu, Hongxing
  • Monteith, Tyler
  • McGrath, Joshua
  • Fiorellino, Nicole M.

Abstract

One innovative way to solve water pollution problems is through water quality trading programs. However, participation levels and the price of offsets/credits tend to be low, which raises questions about the effectiveness of the policy. To offer more tools for policymakers, this paper provides a method for predicting participation in performance-based water quality trading programs, which accounts for field-level heterogeneity. We frame the economic problem in terms of derived demand, i.e., as a farmer Best Management Practice (BMP) input decision rather than a farmer output decision about supplying offsets. Specifically, this approach offers a straightforward way for farmers and policymakers to frame the decision to add a marginal unit of BMP—rather than a marginal unit of abatement—and take advantage of existing performance-based scientific models of nutrient loading. The paper uses actual market and field data in Maryland to illustrate the method and demonstrate the heterogeneity within and among BMPs. We also run sensitivity analyses to test the effects of different levels of farmer subsidies and transaction costs. The application results find, first, the extensive field-level heterogeneity in BMP abatement productivity. Second, the results show that far more farmers will adopt the high-abatement, medium-cost buffer BMPs than low-abatement, low-cost and high-abatement, high-cost BMPs.

Suggested Citation

  • Duke, Joshua M. & Liu, Hongxing & Monteith, Tyler & McGrath, Joshua & Fiorellino, Nicole M., 2020. "A method for predicting participation in a performance-based water quality trading program," Ecological Economics, Elsevier, vol. 177(C).
  • Handle: RePEc:eee:ecolec:v:177:y:2020:i:c:s0921800919313072
    DOI: 10.1016/j.ecolecon.2020.106762
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    References listed on IDEAS

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