海洋生物多样性价值评估的不确定性偏差修正——以福建平潭为例

doi:10.18402/resci.2020.07.10

摘要/Abstract

摘要：

在面对条件价值评估法估值问题时,由于对待评估物品缺乏认知等原因,部分受访者将对支付意愿金额表现出不确定性,造成不确定性偏差。为识别并修正不确定性偏差,本文以平潭海洋生物多样性价值评估为例,通过增设题项,要求受访者给出支付意愿确切金额或区间范围,以支付意愿区间长度比例衡量受访者不确定性,在此基础上分析不确定性的影响因素,并以不确定性水平对支付意愿区间进行加权,将不确定性纳入支付意愿估值框架以减少偏误,提高条件价值评估法估值精度。结果表明：①不确定性的存在具有普遍性,近50%受访者对支付意愿表现出不确定性。②受访者在当地的居住年限、对海洋生物多样性的了解程度、收入水平均对不确定性具有显著影响。③将不确定性水平纳入支付意愿估计,运用参数估计方法测算福建平潭居民对于保护海洋生物多样性的支付意愿为200.24元/(人·年),平潭海洋生物多样性价值为8888.65万元/年。研究结论将加深对条件价值评估法中不确定性偏差来源及修正方法的理解,提高条件价值评估法估值有效性与准确性,并为海岛生态系统的海洋生物多样性保护与管理、海洋资源可持续利用提供支撑。

关键词: 条件价值评估法（CVM）, 不确定性偏差, 支付卡式, 支付意愿, 海洋生物多样性, 平潭

Abstract:

When responding to contingent valuation method (CVM) valuation questions, some respondents may show uncertainty in their willingness to pay (WTP) because of the lack of cognition of the goods to be estimated, which will cause uncertainty bias. This study took the valuation of marine biodiversity in Pingtan County, Fujian Province as an example, to identify and correct the uncertainty bias by adding follow-up questions and incorporate uncertainty into the framework of WTP estimation, which will reduce the bias and improve the validity of CVM. The results show that about 50% of the respondents were uncertain of their willingness to pay, which means that the uncertainty could be universal. Years of residency in the area, knowledge of marine biodiversity, and income had significant effects on the uncertainty. Incorporating uncertainty into the estimation of WTP, the parameter estimation results show that the estimated WTP to preserve marine biodiversity was RMB 200.24 yuan per person each year and the value of marine biodiversity in Pingtan was RMB 88.89 million yuan per year. The conclusion may deepen the understanding of the sources as well as the correction methods of uncertainty bias, and thus improve the validity of estimation results in CVM and provide data support for the protection and governance of marine biodiversity in island ecosystems.

Key words: contingent valuation method (CVM), uncertainty bias, payment cards, willingness to pay, marine biodiversity, Pingtan County

李京梅, 单菁竹, 邓云成, 许罕多. 海洋生物多样性价值评估的不确定性偏差修正——以福建平潭为例[J]. 资源科学, 2020, 42(7): 1338-1347.

LI Jingmei, SHAN Jingzhu, DENG Yuncheng, XU Handuo. 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): 1338-1347.

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选项A：确切金额		选项B：大致范围
选项A：确切金额		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：

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

变量	Probit模型		OLS模型		Ordered Probit模型
变量	系数	标准差	系数	标准差	系数	标准差
常数项	3.272***	0.700	0.883***	0.148
YEAR	-0.018**	0.008	-0.004**	0.002	-0.020***	0.007
FRE	0.037	0.130	0.026	0.029	0.048	0.114
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
CONTRI	0.006	0.115	0.008	0.025	0.039	0.098
SEX	-0.164	0.185	-0.043	0.041	-0.186	0.161
AGE	-0.188	0.135	-0.020	0.030	-0.039	0.117
EDU	-0.030	0.080	0.006	0.017	0.033	0.068
INC	-0.453***	0.095	-0.095***	0.019	-0.412***	0.084
Log likelihood	-140.673				-245.937
McFadden R²	0.206				0.125
F-statistic			8.077
Adjusted R²			0.199
N	258		258		258

变量	系数	标准差
C	-0.443	0.816
YEAR	-0.006	0.010
FRE	0.653***	0.167
KNOW	0.116	0.150
CONCERN	0.079	0.124
CONTRI	0.289**	0.127
SEX	-0.191	0.236
AGE	-0.249	0.175
EDU	0.135	0.106
INC	0.392***	0.122

变量	系数	标准差
C	-0.475	0.827
YEAR	-0.009	0.010
FRE	0.686***	0.162
KNOW	0.113	0.147
CONCERN	0.046	0.126
CONTRI	0.314**	0.140
SEX	-0.208	0.230
AGE	-0.214	0.167
EDU	0.154	0.097
INC	0.368***	0.109