A random utility model for total maximum daily loads: Estimating the benefits of watershed-based ambient water quality improvements

Water Resources Research

Volumn 38, Issue 11, 2002, Pages 36-1-36-11

  Phaneuf, Daniel J ^a  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

Author keywords

Random utility model; Recreation demand; TMDL; Water quality

Indexed keywords

CATCHMENTS; HYDROLOGY; WATERSHEDS;

WATER RECREATION;

WATER QUALITY;

ENVIRONMENTAL PROTECTION; NUMERICAL MODEL; POLLUTION CONTROL; WATER QUALITY;

NORTH CAROLINA; UNITED STATES;

EID: 0036880251     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2001wr000959     Document Type: Article

References (18)

1. Boyd, J., Unleashing the Clean Water Act: The promise and challenge of the TMDL approach to water quality, Resources, 139, 7-9, 2000a.
2. Boyd, J., The new face of the Clean Water Act: a critical review of the EPA's Proposed TMDL Rules, Resources for the Future discussion paper 00-12, 2000b.
3. Haab T., and R. Hicks, A survey of literature concerning choice set definition in recreation demand, Marin. Resour. Econ., 14, 271-281, 2000.
4. Hanemann, M., Welfare analysis with discrete choice models, in Valuing Recreation and the Environment, edited by J. Herriges and C. Kling, pp. 33-64, Edward Elgar, Northampton, 1999.
5. Kaoru, Y., V. K. Smith, and J. L. Liu, Using random utility models to estimate the recreation value of estuarine resources, Am. J. Agric. Econ., 77, 141-151, 1995.
6. Krinsky, I., and A. Robb, On approximating the statistical properties of elasticities, Rev. Econ. Stat., 68, 715-719, 1986.
7. Lyon, R. M., and S. Farrow, An economic analysis of Clean Water Act issues, Water Resour. Res., 31, 213-223, 1995.
8. McConnell, K., and I. Strand, Measuring the cost of time in recreation demand analysis: An application to sport fishing, Am. J. Agric. Econ., 63, 153-156, 1981.
9. McDaniels, T. L., L. J. Axelrod, and N. Cavanagh, Public perceptions regarding water quality and attitude toward water conservation in the Lower Fraser Basin, Water Resour. Res., 34, 1299-1306, 1998.
10. N.C. Department of Environment and Natural Resource, Total Maximum Daily Load for Total Nitrogen to the Neuse River Estuary, Raleigh, N.C., 1999. (Available at http://h2o.enr.state.nc.us/mtu/aboutTMDL.html)
11. N.C. Department of Environment and Natural Resource, Narrative Portion of N.C.'s Draft 2000 203(d) List, Raleigh, N.C., 2000. (Available at http://h2o.enr.state. nc.us/mtu/download.html)
12. Peters, T., W. L. Adamowicz, and P. C. Boxall, Influence of choice set considerations in modeling the benefits from improved water quality, Water Resour. Res., 31, 1781-1787, 1995.
13. Schwabe, K. A., Modeling state-level water quality management: The case of the Neuse River Basin, Resour. Energy Econ., 22, 37-62, 2000.
14. Spruill, T., et al.,Water quality in the Albermarle-Pamlico Drainage Basin: Virginia and North Carolina 1992-95, U.S. Geol. Surv. Circ., 1157, 1998.
15. U.S. Department of Interior, Fish and Wildlife Service, and U.S. Department of Commerce, Bureau of the Census, National Survey of Fishing, Hunting, and Wildlife-Associated Recreation, Fish and Wildlife Serv., Washington, D.C., 1996.
16. U.S. Environmental Protection Agency, Index of Watershed Indicators, 1999a. (Available at http://www.epa.gov/iwi/)
17. U.S. Environmental Protection Agency, 40 CFR 130 proposed revisions to the water quality planning and management regulation: Proposed rule, Fed. Regist., 64 (August 23), 46,012-46,055, 1999b.
18. U.S. Geological Survey, Geographic Names Information System, 2000. (Available at http://mapping.usgs.gov/www/gnis/)