Valuing water quality as a function of water quality measures

Kevin J. Egan; Joseph A. Herriges; Catherine L. Kling; John A. Downing

doi:10.1111/j.1467-8276.2008.01182.x

Valuing water quality as a function of water quality measures

Kevin J. Egan, Joseph A. Herriges, Catherine L. Kling, John A. Downing

Research output: Contribution to journal › Article › peer-review

110 Scopus citations

Abstract

Employing a unique and rich data set of water quality attributes in conjunction with detailed household characteristics and trip information, we develop a mixed logit model of recreational lake usage and undertake thorough model specification and fitting procedures to identify the best set of explanatory variables, and their functional form for the estimated model. Our empirical analysis shows that individuals are responsive to the full set of water quality measures used by biologists to identify the impaired status of lakes. Thus, changes in these quality measures are not simply a scientific exercise, but they also translate into changes in the recreational usage patterns and well-being of individual households. Willingness-to-pay (WTP) estimates are reported based on improvements in these physical measures.

Original language	English (US)
Pages (from-to)	106-123
Number of pages	18
Journal	American Journal of Agricultural Economics
Volume	91
Issue number	1
DOIs	https://doi.org/10.1111/j.1467-8276.2008.01182.x
State	Published - 2009
Externally published	Yes

Bibliographical note

Funding Information:
The authors would like to thank participants in seminars at Resources for the Future, the University of Minnesota, and the Heartland Conference for helpful comments on earlier drafts of this paper. All remaining errors are, of course, our own. This journal paper of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, Project No. 5141, was supported by Hatch Act and State of Iowa funds. Funding for this project was also provided by the Iowa Department of Natural Resources and the U.S. Environmental Protection Agency’s Science to Achieve Results (STAR) program. Although the research described in the article has been funded in part by the U.S. Environmental Protection Agency’s STAR program through grant R830818, it has not been subjected to any EPA review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred.

Keywords

Nonmarket valuation
Recreation demand
Water quality

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1111/j.1467-8276.2008.01182.x

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abstract = "Employing a unique and rich data set of water quality attributes in conjunction with detailed household characteristics and trip information, we develop a mixed logit model of recreational lake usage and undertake thorough model specification and fitting procedures to identify the best set of explanatory variables, and their functional form for the estimated model. Our empirical analysis shows that individuals are responsive to the full set of water quality measures used by biologists to identify the impaired status of lakes. Thus, changes in these quality measures are not simply a scientific exercise, but they also translate into changes in the recreational usage patterns and well-being of individual households. Willingness-to-pay (WTP) estimates are reported based on improvements in these physical measures.",

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note = "Funding Information: The authors would like to thank participants in seminars at Resources for the Future, the University of Minnesota, and the Heartland Conference for helpful comments on earlier drafts of this paper. All remaining errors are, of course, our own. This journal paper of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, Project No. 5141, was supported by Hatch Act and State of Iowa funds. Funding for this project was also provided by the Iowa Department of Natural Resources and the U.S. Environmental Protection Agency{\textquoteright}s Science to Achieve Results (STAR) program. Although the research described in the article has been funded in part by the U.S. Environmental Protection Agency{\textquoteright}s STAR program through grant R830818, it has not been subjected to any EPA review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred.",

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AU - Kling, Catherine L.

AU - Downing, John A.

N1 - Funding Information: The authors would like to thank participants in seminars at Resources for the Future, the University of Minnesota, and the Heartland Conference for helpful comments on earlier drafts of this paper. All remaining errors are, of course, our own. This journal paper of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, Project No. 5141, was supported by Hatch Act and State of Iowa funds. Funding for this project was also provided by the Iowa Department of Natural Resources and the U.S. Environmental Protection Agency’s Science to Achieve Results (STAR) program. Although the research described in the article has been funded in part by the U.S. Environmental Protection Agency’s STAR program through grant R830818, it has not been subjected to any EPA review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred.

PY - 2009

Y1 - 2009

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AB - Employing a unique and rich data set of water quality attributes in conjunction with detailed household characteristics and trip information, we develop a mixed logit model of recreational lake usage and undertake thorough model specification and fitting procedures to identify the best set of explanatory variables, and their functional form for the estimated model. Our empirical analysis shows that individuals are responsive to the full set of water quality measures used by biologists to identify the impaired status of lakes. Thus, changes in these quality measures are not simply a scientific exercise, but they also translate into changes in the recreational usage patterns and well-being of individual households. Willingness-to-pay (WTP) estimates are reported based on improvements in these physical measures.

KW - Nonmarket valuation

KW - Recreation demand

KW - Water quality

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Valuing water quality as a function of water quality measures

Abstract

Bibliographical note

Keywords

UN SDGs

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