Global Patterns in the Implementation of Payments for Environmental Services

Assessing global tendencies and impacts of conditional payments for environmental services (PES) programs is challenging because of their heterogeneity, and scarcity of comparative studies. This meta-study systematizes 55 PES schemes worldwide in a quantitative database. Using categorical principal component analysis to highlight clustering patterns, we reconfirm frequently hypothesized differences between public and private PES schemes, but also identify diverging patterns between commercial and non-commercial private PES vis-à-vis their service focus, area size, and market orientation. When do these PES schemes likely achieve significant environmental additionality? Using binary logistical regression, we find additionality to be positively influenced by three theoretically recommended PES ‘best design’ features: spatial targeting, payment differentiation, and strong conditionality, alongside some contextual controls (activity paid for and implementation time elapsed). Our results thus stress the preeminence of customized design over operational characteristics when assessing what determines the outcomes of PES implementation.

对条件型环境服务付费（Conditional Payments for Environmental Services）项目的全球发展趋势与影响开展评估颇具挑战，原因在于此类项目存在异质性，且相关比较研究较为匮乏。本元研究将全球范围内的55项PES项目系统化收录至量化数据库中。本研究采用分类主成分分析以凸显聚类模式，不仅验证了学界常提出的公共与私营PES项目间的差异假说，还发现商业性与非商业性私营PES项目在服务重点、实施规模与市场导向方面存在分化特征。那么此类PES项目在何种条件下可实现显著的环境额外性？本研究采用二元逻辑回归分析发现，环境额外性受到三项理论层面推荐的PES‘最优设计’特征的正向影响：空间精准定位、支付差异化设置与严格的条件约束，同时还受部分情境控制变量（付费活动类型与项目实施时长）的调控。因此，本研究结果强调，在评估PES项目实施成效的决定因素时，定制化设计相较于项目运营特征具有更为核心的地位。