GOVCOPP - Research Unit in Governance, Competitiveness and Public Policy, and DEGEIT - Department of Economics, Management, Industrial Engineering and Tourism, University of Aveiro, Aveiro, Portugal.
Centre for Power and Energy Systems, INESC TEC, Campus da FEUP, Rua Dr Roberto Frias, 4200-465, Porto, Portugal.
Environ Sci Pollut Res Int. 2020 Apr;27(11):12566-12578. doi: 10.1007/s11356-020-07847-9. Epub 2020 Jan 30.
The circular economy contrasts with the traditional linear economy since it presents a sustainable way both to produce goods and services and to contribute to the development of economies. This paper aims to contribute to a better knowledge of the efficiency of resources productivity, a common indicator to compare how circular economies are, through the estimation of the main determinants for the circular economy in Europe. A systematic analysis and comparison of the performance of all the European Union countries was performed to get further insight into their root causes and to help designing future policies towards a more circular European Union economy. With this purpose, a set of determinant factors for a circular economy in Europe were analysed, under the period between 2000 and 2016. A cluster analysis was applied and complemented with three econometric estimation methods: panel unit root tests, panel cointegration tests and vector autoregression model. The main findings allowed to cluster European countries into three different groups according to the growth rate of their resources productivity and to explain them according to the selected exploratory factors. Special efforts were made to explain the highest productivity growth group, as a way to find relevant drivers towards sustainable productivity growths.
循环经济与传统的线性经济形成对比,因为它为商品和服务的生产以及促进经济发展提供了一种可持续的方式。本文旨在通过估计欧洲循环经济的主要决定因素,为更好地了解资源生产力效率这一共同指标提供帮助,以便对循环经济进行比较。对所有欧盟国家的表现进行了系统的分析和比较,以深入了解其根本原因,并有助于制定未来的政策,以实现更具循环性的欧盟经济。为此,在 2000 年至 2016 年期间,分析了欧洲循环经济的一组决定因素。应用了聚类分析,并辅以三种计量经济学估计方法:面板单位根检验、面板协整检验和向量自回归模型。主要发现允许根据资源生产力增长率对欧洲国家进行聚类,并根据选定的探索性因素对其进行解释。特别努力解释生产力增长率最高的组,以找到可持续生产力增长的相关驱动因素。