Resources Science, Volume. 42, Issue 7, 1338(2020)

Uncertainty bias and its correction in contingent valuation method: A case study of marine biodiversity valuation in Pingtan County

Jingmei LI1,2, Jingzhu SHAN1、*, Yuncheng DENG3, and Handuo XU1,2
Author Affiliations
  • 1School of Economics, Ocean University of China, Qingdao 266100, China
  • 2Marine Development Institute, Ocean University of China, Qingdao 266100, China
  • 3Island Research Center, Ministry of Natural Resources, Pingtan 350400, China
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    Figures & Tables(6)
    A illustration of correction of uncertainty
    • Table 1. An example of contingent valuation method (CVM) valuation questions

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      Table 1. An example of contingent valuation method (CVM) valuation questions

      选项A:确切金额选项B:大致范围
      最低值最高值
      □0元□50元□0元□50元□0元□50元
      □5元□100元□5元□100元□5元□100元
      □10元□200元□10元□200元□10元□200元
      □15元□300元□15元□300元□15元□300元
      □20元□400元□20元□400元□20元□400元
      □30元□500元□30元□500元□30元□500元
      □40元□其他金额:□40元□其他金额:□40元□其他金额:
    • Table 2. Definition of variables and description

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      Table 2. Definition of variables and description

      变量名变量含义赋值方法
      YEAR在平潭当地居住年限/年YEAR=居住年限
      FRE去海边频率经常=4,偶尔=3,很少=2,从不=1
      KNOW对海洋生物多样性了解程度非常了解=5,比较了解=4,一般=3,不太了解=2,完全不了解=1
      CONCERN对海洋生物多样性保护关注程度非常关心=5,比较关心=4,一般=3,不太关心=2,完全不关心=1
      CONTRI是否同意居民应当为保护生物多样性贡献力量,如支付一定费用非常同意=5,比较同意=4,一般=3,不太同意=2,完全不同意=1
      SEX性别男=1,女=0
      AGE年龄/岁20以下=1,20~30=2,31~45=3,46~60=4,61以上=5
      EDU受教育情况初中及以下=1,职高/高中=2,大专=3,本科=4,研究生及以上=5
      INC年收入/万元2以下=1,2~5=2,5~10=3,10~20=4,20以上=5
    • Table 3. Parameter estimation of the determinants of uncertainty

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      Table 3. Parameter estimation of the determinants of uncertainty

      变量Probit模型OLS模型Ordered Probit模型
      系数标准差系数标准差系数标准差
      常数项3.272***0.7000.883***0.148
      YEAR-0.018**0.008-0.004**0.002-0.020***0.007
      FRE0.0370.1300.0260.0290.0480.114
      KNOW-0.368***0.128-0.063**0.026-0.281**0.112
      CONCERN-0.170*0.101-0.050**0.022-0.213**0.088
      CONTRI0.0060.1150.0080.0250.0390.098
      SEX-0.1640.185-0.0430.041-0.1860.161
      AGE-0.1880.135-0.0200.030-0.0390.117
      EDU-0.0300.0800.0060.0170.0330.068
      INC-0.453***0.095-0.095***0.019-0.412***0.084
      Log likelihood-140.673-245.937
      McFadden R20.2060.125
      F-statistic8.077
      Adjusted R20.199
      N258258258
    • Table 4. Parameter estimation of the determinants of willingness to pay (WTP)

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      Table 4. Parameter estimation of the determinants of willingness to pay (WTP)

      变量系数标准差
      C-0.4430.816
      YEAR-0.0060.010
      FRE0.653***0.167
      KNOW0.1160.150
      CONCERN0.0790.124
      CONTRI0.289**0.127
      SEX-0.1910.236
      AGE-0.2490.175
      EDU0.1350.106
      INC0.392***0.122
    • Table 5. Parameter estimation of interval regression

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      Table 5. Parameter estimation of interval regression

      变量系数标准差
      C-0.4750.827
      YEAR-0.0090.010
      FRE0.686***0.162
      KNOW0.1130.147
      CONCERN0.0460.126
      CONTRI0.314**0.140
      SEX-0.2080.230
      AGE-0.2140.167
      EDU0.1540.097
      INC0.368***0.109
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    Jingmei LI, Jingzhu SHAN, Yuncheng DENG, Handuo XU. Uncertainty bias and its correction in contingent valuation method: A case study of marine biodiversity valuation in Pingtan County[J]. Resources Science, 2020, 42(7): 1338

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    Paper Information

    Received: Apr. 25, 2019

    Accepted: --

    Published Online: Apr. 23, 2021

    The Author Email: SHAN Jingzhu (oucshanjingzhu@126.com)

    DOI:10.18402/resci.2020.07.10

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