Li Zhengtao, Hu Bin
School of Economics, Zhejiang University of Finance & Economics, Xueyuan Street No. 18, Xiasha Higher Education Park, Hangzhou, 310018, China.
School of Public Finance and Public Policy, Central University of Finance and Economics, 39 South College Road, Haidian District, Beijing, 100081, China.
Econ Hum Biol. 2018 Sep;31:54-68. doi: 10.1016/j.ehb.2018.07.007. Epub 2018 Jul 27.
This study examined people's willingness to pay (WTP) for improving air quality obtained through contingent valuation method (CVM) in the context of the theory of planned behaviour. Following this theory, four indicators were developed to measure people's behavioural intentions for improving air quality; two of these indicators were correlated with contingent valuation survey. Structural equation modelling (SEM) was employed to estimate our Perception-based Behavioural Intention Model (PBIM) by using a cross-sectional data set of 759 residents of the Jinchuan mining area in Gansu Province, China. We found that Jinchuan residents' WTP for improving local air quality was significantly influenced by the perceived health risk of hazardous pollutants, environmental knowledge, socioeconomic status, current health condition, gender, work environment, and proximity to the pollution source. This study shows that SEM outperforms conventional CVM econometrically and in terms of the provision of relevant policy information.
本研究在计划行为理论的背景下，运用条件价值评估法（CVM）考察了人们为改善空气质量的支付意愿（WTP）。依据该理论，开发了四个指标来衡量人们改善空气质量的行为意图；其中两个指标与条件价值评估调查相关。通过使用中国甘肃省金川矿区759名居民的横截面数据集，采用结构方程模型（SEM）来估计我们基于感知的行为意图模型（PBIM）。我们发现，金川居民为改善当地空气质量的支付意愿受到有害污染物的感知健康风险、环境知识、社会经济地位、当前健康状况、性别、工作环境以及与污染源的距离的显著影响。本研究表明，在计量经济学和提供相关政策信息方面，SEM优于传统的CVM。
