Economic Valuation of the Aquatic Biodiversity Conservation in South Korea: Correcting for the Endogeneity Bias in Contingent Valuation
Hyun No Kim,
John Tenhunen and
Trung Thanh Nguyen
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Ik-Chang Choi: Bayreuth Center of Ecology and Environmental Research, University of Bayreuth, Bayreuth 95440, Germany
Hyun No Kim: Environmental Policy Research Group, Korea Environment Institute, Sejong 30147, Korea
Hio-Jung Shin: Department of Agricultural and Resource Economics, Kangwon National University, Chuncheon 24341, Korea
John Tenhunen: Bayreuth Center of Ecology and Environmental Research, University of Bayreuth, Bayreuth 95440, Germany
Sustainability, 2017, vol. 9, issue 6, 1-20
In this study, we use the Contingent Valuation (CV) method to estimate households’ willingness to pay (WTP) for the aquatic ecosystem health (biodiversity) improvement. This paper extends CV studies by dealing with the endogenous effect of a proxy variable, namely the subjective experience of negative environmental quality changes. The results show that the correction for the endogeneity bias facilitates the efficiency of parameter estimation in the empirical model. The mean WTP per household accounts for around 46.8% (KRW 79.6) of the current water use charge (KRW 170 per cubic meter). The total benefit from conserving the biodiversity is around KRW 198.62 billion. We found several factors that affect households’ WTP for fish biodiversity conservation, suggesting the importance of these factors in the formulation of water policies associated with aquatic biodiversity. In addition, the inefficient water management costs should be redistributed to other projects or new programs such as for the fish biodiversity conservation.
Keywords: contingent valuation method; willingness to pay; aquatic biodiversity; bivariate probit model; endogeneity bias; benefit calculation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:9:y:2017:i:6:p:930-:d:100351
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