Comparing Cars With Apples? Identifying the Appropriate Benchmark Countries for Relative Ecological Pollution Rankings and International Learning

Frontiers in Environmental Science

Diogo Ferraz³  Mayra Bezerra⁴  Dominik Hartmann⁴  Andreas Pyka⁵  Flávio L. Pinheiro⁶ 

[1] Department of Economics and International Relations, Federal University of Santa Catarina, Florianópolis, Brazil;Department of Economics, Federal University of Ouro Preto (UFOP), Ouro Preto, Brazil;Department of Production Engineering, São Paulo State University (UNESP), Bauru, Brazil;Fraunhofer Center for International Management and Knowledge Economy, Leipzig, Germany;Innovation Economics, Institute of Economics, University of Hohenheim, Stuttgart, Germany;Nova Information Management School (NOVA IMS), Universidade Nova de Lisboa, Lisbon, Portugal;

关键词: economic complexity;    cleaner production;    eco-efficiency;    country benchmark network;    international learning;   

DOI  :  10.3389/fenvs.2021.779378

来源: DOAJ

【 摘 要 】

One of the most difficult tasks that economies face is how to generate economic growth without causing environmental damage. Research in economic complexity has provided new methods to reveal structural constraints and opportunities for green economic diversification and sophistication, as well as the effects of economic complexity on environmental pollution indicators. However, no research so far has compared the ecological efficiency of countries with similar productive structures and levels of economic complexity, and used this information to identify the best learning partners. This matters, because there are substantial differences in the environmental damage caused by the same product in different countries, and green diversification needs to be complemented by substantial efficiency improvements of existing products. In this article, we use data on 774 different types of exports, CO2 emissions, and the ecological footprint of 99 countries to create first a relative ecological pollution ranking (REPR). Then, we use methods from network science to reveal a benchmark network of the best learning partners based on country pairs with a large extent of export similarity, yet significant differences in pollution values. This is important because it helps to reveal adequate benchmark countries for efficiency improvements and sustainable production, considering that countries may specialize in substantially different types of economic activities. Finally, the article i) illustrates large efficiency improvements within current global output levels, ii) helps to identify countries that can best learn from each other, and iii) improves the information base in international negotiations for the sake of a cleaner global production system.

【 授权许可】

Unknown