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    Willingness-to-pay for water quality improvements in Chinese rivers: An empirical test on the ordering effects of multiple-bounded discrete choices2013

    HE J., KAMATA T., KIM Y., WANG H.Journaux et Revues (scientifiques)

    analyse conjointe / dichotomique, consentement à payer, coûts / mesures de prévention / protection, évaluation contingente, pêche / chasse, valeur d'usage, valeurs récréatives ou d'agrément

    Journal of Environmental Management
    Volume 131, 15 December 2013, Pages 256–269


    • This paper estimates the WTP for water quality improvement in China.
    • The study is based on a multiple-bounded discrete choice (MBDC) WTP questionnaire
    • We explicitly recognize potential respondent uncertainty in our estimation model.
    • The ordering effects associated with the MBDC approach are empirically tested.
    • We find significant impact of presentation order of bid value in MBDC matrix.


    This paper presents a study of the willingness-to-pay (WTP) for surface water quality improvement in China. In the Huaping County of Yunnan Province, we found that people are willing to pay 74 Yuan (or US$12.33 in 2012 prices) per household per month (or 5% of household income) continuously for five years to achieve an improvement of water quality in the two major local rivers from the current Grade IV to Grade III, which denotes a level suitable for swimming and fishing and matches the water quality level from 10 years ago. This WTP study is based on an actual investment project that was under serious consideration by the government and is based on the multiple-bounded discrete choice (MBDC) approach, which explicitly recognizes the potential uncertainties involved in the study. The potential ordering effects associated with the MBDC approach are empirically tested, and the results indicate that although the presentation order of the polychotomous likelihood choices may not have a significant impact on the WTP estimation, the presentation order of bid levels may have a significant impact.

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