(2.中国人民大学农业与农村发展学院, Beijing , China 100872)
【摘要】嵌入效应会显著地影响经济学家对环境政策的成本效益分析, 但目前国内鲜有研究在评估环境政策效益时对嵌入效应进行识别和讨论。本文首先在一个扩展的健康生产函数基础上分析了环境政策之间存在嵌入效应的原因, 进而以北京市雾霾和沙尘治理政策为例, 设计了三个选择实验组来验证嵌入效应。随后, 本文采用随机参数Logit模型对各组样本进行了估计, 污染物边际价值在组间的显著差异证实了嵌入效应的存在。如果忽略嵌入效应, 降低雾霾和沙尘的平均边际价值分别会被高估36.87%和67.62%。在模型中控制调查对象的偏好异质性以后, 高估程度有所下降, 但嵌入效应仍不能完全消除。本文的研究结论意味着政策制定者和研究者在评估环境政策的效益之前, 需要谨慎地处理嵌入效应, 虽然不同的环境政策可能在技术目标上指向相互独立的不同污染物, 但污染物之间的价值相关性仍然会导致嵌入效应, 进而影响评估结果。
【基金资助】 中央高校基本科研业务费专项资金资助项目“基于选择实验的北京市雾霾治理公共政策研究” (批准号16XNB023) ;
Embedding effects in evaluation of multiple environmental policies: evidences from Beijing’s haze and sand control policies
(2.School of Agricultural Economics and Rural Development, Renmin University of China, Beijing , China 100872)
【Abstract】This paper first, in theory, explores the causes of embedding effects among multiple environmental policies on the basis of an extended health production function. And then taking haze and sand control policies in Beijing as example, we design a sub sample choice experiment in order to verify embedding effects. Random parameter Logit model is adopted to conduct the estimation, and we simulate 2000 marginal values according to the estimates in each sub sample. Results of mean tests confirm the significant and steady embedding effects, and if the effect is ignored, marginal values of reducing haze and sand would be overestimated by 36.87% and 67.62%, respectively. The results indicate that before conducting cost and benefit analysis of an environmental policy, the policy makers or researchers should carefully examine the possible embedding effects in multiple policies, especially those targeting different pollutants but economic values of the pollutants are correlated or integrated.
【Keywords】 environmental policy; embedding effect; air quality; choice experiment; valuation;
【Funds】 Fundamental Research Funds for the Central Universities (16XNB023);
. ① These three main biases are as follows: the first is the hypothetical bias, namely, the respondents tend to overestimate their willingness to pay in the virtual decision-making scenario; the second is the separation of the willingness to pay and the willingness to be compensated; and the third is embedding effect concerned by this paper. [^Back]
. ① The function, known as the “intervention function,” reflects the impact of intervention policies or measures on the level of pollutants at the technical level. Certainly, in the study of environmental economics, the intervention function itself is a research target, which is the basis of evaluating the benefit of environmental policy. For example, Cao et al. discussed the impact of traffic restriction based on the last digit of license plate numbers of motor vehicles in Beijing on the improvement of air quality; and Xi and Liang  discussed the impact of the oil price changes on the air pollution. Since the intervention function is not the object of this paper, this paper assumes that the technical effect reflected by this function is given in advance. [^Back]
. ② Another case is that there is an overlap in the objectives or the effects of multiple environmental policies, that is, . In this case, the substitution relationship between the two policies will directly lead to embedding effect. [^Back]
. ① Before the formal choice, this paper also designed a description of the situation of air pollution in Beijing, and in the process, the contrast map of the good air quality and the air pollution is shown to the respondents. [^Back]
. ② According to the Environmental Air Quality Index (AQI) Technical Stipulation (Trial Implementation) (HJ633-2012) promulgated by the Ministry of Environmental Protection, when AQI is the mild pollution, the corresponding concentration of PM2.5 is 75ug/m3, and the corresponding concentration of PM10 is 150ug/m3. [^Back]
. ① In the third test H03, it was unable to add w11 and w22 directly because the samples in the first and second experimental groups did not match one by one. However, the test is based on the simulation of the marginal value data in the following context. Since w11 and w22 both obey the normal distribution, the random w11+w22 also obeys the normal distribution. And w31+w32 may not obey the normal distribution due to the preference correlation of w31 and w32. In the following context, the estimated result does not verify that the preference of individual to the haze and sand has a significant correlation. [^Back]
. ② The scope insensitivity means that the respondents are not concerned with the defined “scope” (or “unit of measure”) of the evaluation objects, focusing only on the relative strength of the objects, which may cause a significant decrease in the validity of the valuation results. The difference between haze and sand in the experimental design is only reflected in the difference of the days of occurrence (see Table 3). Thus, if the conclusions of this paper support the argument of scope insensitivity, there should be w2/w1 ≈ 1.8. However, the estimated results show that w1 is significantly higher than w2, and it can be considered that there is no scope insensitivity in the investigation process. [^Back]
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