﻿ 高温热浪支付意愿人群分异及其影响因素——以福州市为例

 气候变化研究进展   2017, Vol. 13 Issue (2): 172-180.  DOI: 10.12006/j.issn.1673-1719.2016.134 0

### 引用本文 [复制中英文]

[复制中文]
Wang Yi, Liu Guanqiu, Qi Xi, et al. A Study on the Willingness to Pay for Heatwaves Between Different Groups and Its Influence Factors: A Case of Fuzhou[J]. Climate Change Research, 2017, 13(2): 172-180. DOI: 10.12006/j.issn.1673-1719.2016.134.
[复制英文]

### 文章历史

1. 福建师范大学地理科学学院，福建 350007;
2. 福建师范大学地理研究所，福建 350007;
3. 福建省湿润亚热带山地生态国家重点实验室培育基地，福建 350007

1 区域概况、研究方法与样本属性 1.1 区域概况

 图 1 1964—2014年福州市年最高气温变化趋势 Figure 1 The trend of annual maximum temperature in Fuzhou during 1964-2014
1.2 研究方法

(1) 问卷调查与深度访谈

(2) 条件价值评估法

 $E{\left( {{\rm{WTP}}} \right)_{{\rm{正}}}} = \sum\limits_{i = 1}^n {{b_i}{p_i}。}$ (1)

(3) 二元逻辑回归模型

 $\ln \frac{{{W_i}}}{{1-{W_i}}} = {\beta _0} + \sum\limits_{i = 1}^n {{\beta _i}{X_i}。}$ (2)

1.3 问卷调查与样本属性

2 高温热浪支付意愿分析 2.1 支付意愿比例与分布

 图 2 正支付意愿分布图 Figure 2 The distribution of positive WTP
2.2 支付值计算及其结果

 $E{\left( {{\rm{WTP}}} \right)_{{\rm{非负}}}} = E{\left( {{\rm{WTP}}} \right)_{{\rm{ 正}}}} \cdot {\rm{ }}(1-{\rm{WTP}}{{\rm{R}}_{{\rm{零}}}})。$ (3)

3 支付意愿的影响因素分析

3.1 居民类型

3.2 性别

3.3 受教育水平

3.4 职业与在福州时间

3.5 月收入与月支出

4 结论与讨论

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A Study on the Willingness to Pay for Heatwaves Between Different Groups and Its Influence Factors: A Case of Fuzhou
Wang Yi1, Liu Guanqiu1, Qi Xi1, Pan Danlin1, Qi Xinhua1,2,3
1. College of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China;
2. Institute of Geography, Fujian Normal University, Fuzhou 350007, China;
3. State Key Laboratory of Subtropical Mountain Ecology, Fuzhou 350007, China
Abstract: Fuzhou city was deliberately chosen as the study area because of prominent heatwaves. Face-to-face interviews were conducted by means of the simple random sampling method, and 962 valid questionnaires were obtained. The depth interviews for some samples were also conducted, and the questionnaires covered some contents: social economy, the willingness to pay (WTP), its influence factors of heatwaves, etc. Contingent Valuation Method (CVM) and the modified Spike model were used to explore the differences between local residents and floating population on the WTP and its influencing factors. The results showed that: 1) Totally, the willingness payment of local residents and floating population for heatwaves is high, and the former is higher than the latter. 2) The willingness payment of local residents is 68.78 RMB per month, and that of floating population is 46.78 RMB per month. Obviously, there are differences between them. 3) The influencing factors of the WTP for heat waves include the type of residents, gender, education level, occupation, the time that stay in Fuzhou and the economic capacity. The differences of the WTP and the amount of payment for heatwaves between the local residents and the floating population and its influence factors will provide references for Fuzhou and other regions with similar weather to make relevant policies.
Key words: heat waves    willingness to pay (WTP)    influence factors    group differences    Fuzhou city