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Endogenous Risk and Point-Nonpoint Uncertainty Trading Ratios

Author

Listed:
  • Richard D. Horan
  • James S. Shortle

Abstract

Point-nonpoint trading enables highly uncertain nonpoint pollution abatement to be substituted for relatively certain point source pollution abatement. Market designers use uncertainty trade ratios to address imperfect substitution between these commodities. Guidance from government agencies and other entities recommends large ratios that penalize trades for nonpoint abatement, and extant programs universally implement this guidance. Previous research has shown that the standard guidance is based on an inappropriate framing of the risk effects of substituting nonpoint for point source pollution abatement, and has demonstrated that the trade ratios should be set to encourage or discourage substitution, depending on whether the substitution is risk-reducing or risk-increasing. However, the Pigouvian pricing approach used to develop this result obscures the underlying economic calculus because it does not recognize or characterize the tradeoffs between abatement costs savings and environmental risk that must be considered in an economic evaluation of alternative ratios, and that would be key to explaining why ratios recommended by economic analysis would be preferred to received wisdom. We develop a new approach that explicitly identifies and characterizes the tradeoffs associated with the choice of ratio. The approach is examined both in first-best settings where trade ratios and initial permit allocations are jointly determined, and in second-best settings where permit allocations are taken as given. We provide a numerical analysis of trading in the Susquehanna River Basin in Pennsylvania to illustrate theory. We find theoretical and numerical support suggesting that smaller ratios may be optimal.

Suggested Citation

  • Richard D. Horan & James S. Shortle, 2017. "Endogenous Risk and Point-Nonpoint Uncertainty Trading Ratios," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(2), pages 427-446.
  • Handle: RePEc:oup:ajagec:v:99:y:2017:i:2:p:427-446.
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    File URL: http://hdl.handle.net/10.1093/ajae/aaw088
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    Citations

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    Cited by:

    1. Reeling, Carson & Garnache, Cloé & Horan, Richard, 2018. "Efficiency gains from integrated multipollutant trading," Resource and Energy Economics, Elsevier, vol. 52(C), pages 124-136.
    2. Cook, Aaron & Shortle, James, 2018. "Intertemporal Trading Ratios for Nutrient Pollution Control," 2018 Annual Meeting, August 5-7, Washington, D.C. 274845, Agricultural and Applied Economics Association.
    3. Zhang, Junlong & Li, Yongping & You, Li & Huang, Guohe & Xu, Xiaomei & Wang, Xiaoya, 2022. "Optimizing effluent trading and risk management schemes considering dual risk aversion for an agricultural watershed," Agricultural Water Management, Elsevier, vol. 269(C).
    4. Aaron M. Cook & James S. Shortle, 2022. "Pollutant Trading with Transport Time Lags," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 82(2), pages 355-382, June.
    5. Carlos Mario Gómez Gómez & C. D. Pérez-Blanco & David Adamson & Adam Loch, 2018. "Managing Water Scarcity at a River Basin Scale with Economic Instruments," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-31, January.
    6. Hopkins, Alexander S. & Horan, Richard & Reeling, Carson & Shupp, Robert S., 2021. "Multipollutant Markets Increase the Efficiency of Managing Jointly Produced, Stochastic Emissions," 2021 Annual Meeting, August 1-3, Austin, Texas 314063, Agricultural and Applied Economics Association.

    More about this item

    Keywords

    Point-nonpoint trading; water quality; permit markets; emissions;
    All these keywords.

    JEL classification:

    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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