Matching Traders in a Pollution Market: The Case of Cub River, Utah
Arthur J. Caplan
This paper applies two recently developed trading algorithms to a water quality trading (WQT) market located in the Cub River sub-basin of Utah; a market that includes both point and nonpoint sources. The algorithms account for three complications that naturally arise in WQT markets: (1) combinatorial matching of traders, (2) trader heterogeneity, and (3) discreteness in abatement technology. The algorithms enable a full characterization of the market’s performance by distinguishing a specific pattern of trade among market participants, which in turn results in as detailed a reduced- cost trading benchmark as possible for the basin. Contrary to the commonly held belief that relatively high point-source abatement costs necessitate nonpoint-source abatement effort, we find that in a WQT market where each source is required to reduce its pollution loadings it may be cheaper for point sources to sell abatement credits to nonpoint sources.
advancement algorithm, retreat algorithm, water quality trading
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