资源环境科技发展态势分析平台

Technological change is key to understand the explanatory variables behind environmental impacts in the context of the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model. An adequate representation and analysis of the significance of the technology variable (T) in the STIRPAT model becomes crucial, even more if one aims to better understand underlying processes such as the (environmental) rebound effect (E)RE. A critical review of the application of the STIRPAT model has been conducted to understand the diversity and value of the variables, scopes, assumptions, statistical approaches, and the environmental impacts commonly studied. The findings highlight that, despite the multiple applications and the high potential of the STIRPAT model, inconclusive results and/or knowledge gaps remain, notably (1) a geographical imbalance in the scope of studies, (2) the almost exclusive focus on carbon emissions, (3) a lack of agreement on the choice of data, additional explanatory variables, and regression models, (4) a lack of consensus on how to approximate T, and (5) a lack of explicit analyses of the (E)RE. Our findings are useful to both policymakers and academics for method design, further research, and policy evaluation.