Abstract

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.

Highlights

  • Countries are facing challenges in promoting economic growth without negatively impacting the environment

  • We compare the ecological efficiency of countries, considering their levels of economic development

  • The low-income countries present the lowest levels of economic sophistication (ECI –1.19 on average), CO2 emissions (0.19) and ecological footprint (0.95)

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Summary

INTRODUCTION

Countries are facing challenges in promoting economic growth without negatively impacting the environment. This article makes use of methods from Data Envelopment Analysis (DEA) to create a relative ecological pollution ranking (REPR) that considers the level of economic complexity of countries, and use methods from network analysis to identify appropriate benchmark countries and learning partners for each country. Such a multimodal approach helps to create sustainability rankings that take productive specialization of countries into account and identify potentials for sustainability improvements within the current global export and production systems. We argue, it is a valid step forward to consider significant differences in productive structures when comparing their sustainability levels and identifying promising countries that could learn from one another for the sake of more efficient and cleaner production systems

LITERATURE REVIEW
RESULTS
CONCLUSION AND POLICY IMPLICATIONS
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