新冠肺炎影响下居民环保支付意愿驱动因素及规模效应

Hongkun Zhao, Yaofeng Yang, Yajuan Chen, Huyang Yu, Zhuo Chen, Zhenwei Yang
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引用次数: 0

摘要

近年来,环境恶化和新冠肺炎疫情严重影响经济发展和社会稳定。研究重大公共卫生事件对居民环境保护支付意愿的影响,并分析其驱动因素,是改善人类福祉和环境可持续性的必要条件。基于环境库兹涅茨曲线(EKC)理论,设计问卷分析新冠肺炎前后居民WTPEP的变化,建立普通最小二乘法(OLS)、空间滞后模型(SLM)、空间误差模型(SEM)、地理加权回归模型(GWR)和多尺度GWR模型,探讨WTPEP的驱动因素和尺度效应。结果表明:(1)WTPEP在新冠肺炎前为0 ~ 2万元,新冠肺炎期间为0 ~ 5万元。居民WTPEP在新冠肺炎期间有所改善,表明居民对生态环境的需求在增加;(2)新冠肺炎发生前和发生期间,收入与WTPEP关系的形态和拐点均存在空间异质性,但北部WTPEP大于南部,说明WTPEP存在空间不平衡;(3)环境退化、健康、环境质量和教育是WTPEP的显著宏观驱动因素,而收入、年龄和性别是WTPEP的显著微观驱动因素。这些因素可以帮助决策者更好地了解哪些因素更适合宏观或微观环境决策,以及未来可以采取哪些有针对性的措施来解决居民日益增长的生态环境需求与WTPEP空间失衡之间的矛盾。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Driving Factors and Scale Effects of Residents' Willingness to Pay for Environmental Protection under the Impact of COVID-19
In recent years, environmental degradation and the COVID-19 pandemic have seriously affected economic development and social stability. Addressing the impact of major public health events on residents’ willingness to pay for environmental protection (WTPEP) and analyzing the drivers are necessary for improving human well-being and environmental sustainability. We designed a questionnaire to analyze the change in residents’ WTPEP before and during COVID-19 and an established ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), and multiscale GWR to explore driver factors and scale effects of WTPEP based on the theory of environment Kuznets curve (EKC). The results show that (1) WTPEP is 0–20,000 yuan before COVID-19 and 0–50,000 yuan during COVID-19. Residents’ WTPEP improved during COVID-19, which indicates that residents’ demand for an ecological environment is increasing; (2) The shapes and inflection points of the relationships between income and WTPEP are spatially heterogeneous before and during COVID-19, but the northern WTPEP is larger than southern, which indicates that there is a spatial imbalance in WTPEP; (3) Environmental degradation, health, environmental quality, and education are WTPEP’s significant macro-drivers, whereas income, age, and gender are significant micro-drivers. Those factors can help policymakers better understand which factors are more suitable for macro or micro environmental policy-making and what targeted measures could be taken to solve the contradiction between the growing ecological environment demand of residents and the spatial imbalance of WTPEP in the future.
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