Cost-Benefit Analysis Based on Referendum CV: Dealing with Uncertainty
Publication: Journal of Water Resources Planning and Management
Volume 126, Issue 6
Abstract
An interesting and potentially important, but little appreciated, result of the use of dichotomous-choice contingent valuation (CV) techniques is that there are about a dozen ways to deal econometrically with the data on bid acceptance to construct a mean or median estimate of willingness-to-pay benefits, none of which is clearly the correct choice. They produce measures of central tendency that can differ, from lowest to highest, by factors ranging from 5 to 15. This is a source of uncertainty in benefit or damage estimation that can easily dominate the more traditionally recognized statistical uncertainty based on noise in the response (and respondent) data. It potentially can introduce ambiguity into a cost-benefit test of economic feasibility if a prospective investment either passes the test based on some willingness-to-pay measures or fails it based on others. These points are illustrated using actual data from a well-designed dichotomous-choice CV survey administered to residents of São Paulo, Brazil, as part of the application process for a loan to cover a multiphase project to improve the quality of the Tietê River.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Ardila, S. ( 1993). “Guía para la utilizacíon de modelos econométricos en aplicaciones del método de valoracíon contingente.” Envir. Div. Working Paper ENP-101, Inter-American Development Bank, Washington, D.C. (in Spanish).
2.
Ardila, S., Quiroga, R., and Vaughan, W. J. ( 1998a). “A review of the use of contingent valuation methods in project analysis at the Inter-American Development Bank.” Working Paper ENV-126, Inter-American Development Bank, Washington, D.C.
3.
Ardila, S., Quiroga, R., and Vaughan, W. J. ( 1998b). “A review of the use of contingent valuation methods in project analysis at the Inter-American Development Bank.” Environment Div., Inter-American Development Bank, 〈http://www.iadb.org/sds/utility.cfm/488/english/pub/178〉 (December 1998).
4.
Bowman, M., Bostedt, G., and Kriström, B. ( 1999). “Obtaining welfare bounds in discrete-response valuation studies: A non-parametric approach.” Land Economics, 75(2), 284–94.
5.
Haab, T. C., and McConnell, K. E. ( 1997). “Referendum models and negative willingness to pay: Alternative solutions.” J. Envir. Economics and Mgmt., 32, February, 251–270.
6.
Haab, T. C., and McConnell, K. E. ( 1998). “Referendum models and economic values: Theoretical, intuitive, and practical bounds on willingness to pay.” Land Economics, 74(2), 216–229.
7.
Hanemann, W. M. ( 1984). “Welfare evaluations in contingent valuation experiments with discrete responses.” Am. J. Agric. Economics, 66, August, 332–341.
8.
Hanemann, W. M. ( 1989). “Welfare evaluations in contingent valuation experiments with discrete response data: Reply.” Am. J. Agric. Economics, 71, November, 1057–1061.
9.
Hanley, N. ( 1992). “Are there environmental limits to cost benefit analysis?” Envir. and Resour. Economics, 2, 33–59.
10.
Kriström, B. ( 1990). “A non-parametric approach to the estimation of welfare measures in discrete response valuation studies.” Land Economics, 66(2), 135–39.
11.
Mitchell, R. C., and Carson, R. ( 1989). Using surveys to value public goods, Resources for the Future, Washington, D.C.
12.
Morgan, M. G., and Henrion, M. ( 1990). Uncertainty: A guide to dealing with uncertainty in quantitative risk and policy analysis, Cambridge University Press, New York.
13.
National Oceanic and Atmospheric Administration (NOAA). ( 1993). “Natural resource damage assessments under the Oil Pollution Act of 1990.” Federal Register, 58(No. 10; Jan. 15), 4601–4614.
14.
Office of Policy Planning and Evaluation (OPPE). ( 1987). “EPA's use of benefit-cost analysis: 1981–1986.” Rep. EPA-230-05-87-028, U.S. EPA, Washington, D.C.
15.
Pearce, D., Whittington, D., Georgiou, S., and Moran, D. ( 1994). “Economic values and the environment in the developing world.” Envir. Economics Ser. Paper No. 14, United Nations Environment Programme, Nairobi, Kenya.
16.
Russell, C. S., and Vaughan, W. J. ( 1982). Freshwater recreational fishing: The national benefits of water pollution control, Resources for the Future, Washington, D.C.
17.
Vaughan, W. J., Russell, C. S., Rodriquez, D. J., and Darling, A. C. ( 1999a). “Willingness to pay: Referendum contingent valuation and uncertain project benefits.” Working Paper ENV-130, Inter-American Development Bank, Washington, D.C.
18.
Vaughan, W. J., Russell, C. S., Rodriquez, D. J., and Darling, A. C. ( 1999b). “Willingness to pay: Referendum contingent valuation and uncertain project benefits.” Environment Div., Inter-American Development Bank, 〈http://www.iadb.org/sds/utility.cfm/488/english/pub/1059〉 (June 1999).
19.
Vose, D. ( 1996). Quantitative risk analysis: A guide to Monte Carlo simulation modeling, Wiley, New York.
20.
Winpenny, J. ( 1996). “Economic valuation of environmental impacts: The temptations of EVE.” Proj. Appraisal, 11(4), 247–253.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 126 • Issue 6 • December 2000
Pages: 351 - 357
History
Received: Jun 14, 2000
Published online: Dec 1, 2000
Published in print: Dec 2000
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.