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Benchmarking an optimal pattern of pollution trading: The case of Cub River, Utah
Economic Modelling (2014)
  • Arthur Caplan, Utah State University
  • Yuya Sasaki, Johns Hopkins University
This paper employs a recently developed, dynamic trading algorithm to establish a benchmark pattern of trade for a potential water quality trading (WQT) market in the Cub River sub-basin of Utah; a market that would ultimately include both point and nonpoint sources. The algorithm accounts for three complications that naturally arise in trading scenarios: (1) combinatorial matching of traders, (2) trader heterogeneity, and (3) discreteness in abatement technology. The algorithm establishes as detailed a reduced-cost benchmark as possible for the sub-basin by distinguishing a specific pattern of trade among would-be market participants. As such, the algorithm provides a benchmark against which an actual pollution market's performance could conceivably be compared. We find that a benchmarked trading pattern for a potential Cub RiverWQT market – where each source, point or nonpoint, would be required to reduce its pollution loadings – may entail some point sources selling abatement credits to nonpoint sources.
  • Advancement Algorithm,
  • Retreat Algorithm,
  • water quality trading
Publication Date
Citation Information
Arthur Caplan and Yuya Sasaki. "Benchmarking an optimal pattern of pollution trading: The case of Cub River, Utah" Economic Modelling Vol. 36 Iss. 1 (2014)
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