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Water quality indices and benefit-cost analysis

Author

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  • Walsh Patrick J.
  • Wheeler William J.

    (US EPA, National Center for Environmental Economics, 1200 Pennsylvania Avenue, Ariel Rios Bldg, MC1809T DC Washington 20460, USA)

Abstract

The water quality index (WQI) has emerged as a central way to convey water quality information to policy makers and the general public and is regularly used in US EPA regulatory impact analysis. It is a compound indicator that aggregates information from several water quality parameters. Several recent studies have criticized the aggregation function of the EPA WQI, arguing that it suffers from “eclipsing” and other problems. Although past papers have compared various aggregation functions in the WQI (usually looking at correlation), this is the first paper to examine these functions in the context of benefit-cost analysis. Using data from the 2003 EPA CAFO rule, the present paper examines four aggregation functions and their impact on estimated benefits. Results indicate that the aggregation method can have a profound effect on benefits, with total benefit estimates varying from $82 million to $504 million dollars. The net benefits of the rule vary from negative to positive over this range of estimates. Furthermore, a sensitivity analysis does not find convincing evidence to substitute the current aggregation function, although several changes to the underlying WQI methodology may be warranted.

Suggested Citation

  • Walsh Patrick J. & Wheeler William J., 2013. "Water quality indices and benefit-cost analysis," Journal of Benefit-Cost Analysis, De Gruyter, vol. 4(1), pages 81-105, March.
  • Handle: RePEc:bpj:jbcacn:v:4:y:2013:i:1:p:81-105:n:1
    DOI: 10.1515/jbca-2012-0005
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    2. Rolfe, John & Windle, Jill & McCosker, Kevin & Northey, Adam, 2018. "Assessing cost-effectiveness when environmental benefits are bundled: agricultural water management in Great Barrier Reef catchments," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(3), July.
    3. Wainger, L. & Loomis, J. & Johnston, R. & Hansen, L. & Carlisle, D. & Lawrence, D. & Gollehon, N. & Duriancik, L. & Schwartz, G. & Ribaudo, M. & Gala, C., 2017. "Ecosystem Service Benefits Generated by Improved Water Quality from Conservation Practices," C-FARE Reports 260679, Council on Food, Agricultural, and Resource Economics (C-FARE).
    4. John Rolfe & Jill Windle & Kevin McCosker & Adam Northey, 2018. "Assessing cost‐effectiveness when environmental benefits are bundled: agricultural water management in Great Barrier Reef catchments," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(3), pages 373-393, July.
    5. Zach Raff & Andrew Meyer, 2022. "CAFOs and Surface Water Quality: Evidence from Wisconsin," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(1), pages 161-189, January.
    6. Margaret W. Gitau & Jingqiu Chen & Zhao Ma, 2016. "Water Quality Indices as Tools for Decision Making and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2591-2610, June.
    7. Søren B. Olsen & Cathrine U. Jensen & Toke E. Panduro, 2020. "Modelling Strategies for Discontinuous Distance Decay in Willingness to Pay for Ecosystem Services," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(2), pages 351-386, February.
    8. Newbold, Stephen C. & Johnston, Robert J., 2020. "Valuing non-market valuation studies using meta-analysis: A demonstration using estimates of willingness-to-pay for water quality improvements," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
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