Evaluating environmental performance using data envelopment analysis: The case of European countries

Matsumoto, Kousuke; Makridou, Georgia; Doumpos, Michael

doi:10.1016/j.jclepro.2020.122637

Cited by 85 publications

(32 citation statements)

References 76 publications

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“…Second, Zanella et al (2013) did not discuss the importance of the productive structure for the environmental performance. Finally, Matsumoto (2020) found that Western European countries achieved higher environmental performance than Eastern European countries. The authors argued that Eastern European countries have lower levels of technology by using two economic inputs (labor and capital).…”

Section: Resultsmentioning

confidence: 98%

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

Hartmann

Ferraz

Bezerra

et al. 2021

Front. Environ. Sci.

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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.

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Section: Resultsmentioning

confidence: 98%

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

Hartmann

Ferraz

Bezerra

et al. 2021

Front. Environ. Sci.

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“…Furthermore, ref. [ 46 ] evaluated environmental performance in the EU through DEA during 2000–2017 and the global Malmquist–Luenberger index [ 46 ]. Similar to [ 36 ] the authors’ main contribution was to consider different types of undesirable outputs and using long-term panel data on EU countries.…”

Section: Brief and Recent Literature Reviewmentioning

confidence: 99%

“…Moreover, ref. [ 45 ] follows [ 46 ] and only includes CO 2 , PM 2.5 and waste emissions as outputs and uses panel data analysis. Our selection of gases and pollutants included as explanatory variables of DEA computed eco-efficiency scores rely on their significant and heterogeneous impact on countries’ environmental efficiency.…”

Section: Brief and Recent Literature Reviewmentioning

confidence: 99%

“…Our selection of gases and pollutants included as explanatory variables of DEA computed eco-efficiency scores rely on their significant and heterogeneous impact on countries’ environmental efficiency. In the present article, we do not use the Malmquist index (MPI) as [ 46 , 47 ] to assess eco-efficiency, as in the studies that served as the basis for the DEA two-stage method, as it was not our concern to analyze eco-efficiency intertemporal productivity performance in EU-27, in the 2008–2018 period. Therefore, we were not concerned with explaining the inducing factors that are associated with changes in technical efficiency and changes in technology efficiency, but only to analyze the eco-efficiency rankings evidenced each year for the cross-section of European countries, and to understand if in the time horizon considered there were changes in positioning in each of the sample’s European countries, to afterward evaluate, which factors affect these rankings the most (gases or pollutants).…”

Section: Brief and Recent Literature Reviewmentioning

confidence: 99%

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A Two-Stage DEA Model to Evaluate the Technical Eco-Efficiency Indicator in the EU Countries

Moutinho

Madaleno

2021

IJERPH

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This paper evaluates the evolution of eco-efficiency for the 27 European Union (EU) countries over the period 2008–2018, provided the traditional high concerns of the EU concerning the economic growth-environmental performance relationship. The EU has triggered several initiatives and regulations regarding environmental protection over the years, but as well the Sustainable Development Goals demand it. Under this setting, we conduct a two-stage analysis, which computes eco-efficiency scores in the first stage for each of the pairs EU 27-year, through the nonparametric method data envelopment analysis (DEA), considering the ratio GDP per capita and greenhouse gas emissions (GHG). In the second stage, scores are used as a dependent variable in the proposed fractional regression model (FRM), whose determinants considered were eight pollutants (three greenhouse gases and five atmospheric pollutants). CO2/area and N2O/area effects are negative and significant, improving the eco-efficiency of the EU 27 countries. When the efficient European countries are excluded from the estimations, the results evidence that CO2/area and CH4/area decrease the DEA score. The country with the lowest GHG emissions and pollutant gases was Ireland, being the country within the considered period that mostly reduced emissions, particularly SOx and PM10, increasing its score.

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“…This view has been strongly challenged by another stream of researchers who opined that foreign direct investment has a positive impact on economic growth (Galaye Ndiaye & Helian Xu,2016;Hasibul & John 2017;Sokang,2018;, they further argued that foreign investment is key to solving the problem of low productivity, and scarce local capital in developing economies through efficient exploitation and utilisation. On the other hand, another group of researchers (Ayub et al, 2019;Matsumoto, 2020) believe that the benefits of FDI depend on the absorptive capacity of the host country. They thereby emphasised that the growth effect of foreign direct growth is induced by its interaction with other moderating factors in the host countries, such as the host country's institutional, economic, political, social, and cultural state.…”

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confidence: 99%

Moderating Effect of Institution in FDI-Growth Relationship in Developing Countries: A Case of Nigeria

Oyefabi¹,

Abdul²,

Oladipupo³

et al. 2021

JESD

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This paper employed the good governance index as a proxy for institutional quality to examine its moderating effect on the FDI-growth relationship in Nigeria from 2006 to 2020. The ARDL bounds testing approach was employed as the technique of analysis to ascertain the direct impact of FDI on economic growth and the indirect impact through the moderating effect of institutional quality (good governance). The paper provides evidence of a long term relationship between FDI and economic growth as well as a significant unconditional positive impact of FDI on economic growth. Regarding the interactive effect of institutional quality (good governance) on the FDIgrowth effect, we find convincing evidence that institutional quality (good governance) alters the effect of FDI on economic growth favourably. Therefore, it is recommended that Nigeria strengthen its governance quality to benefit more from FDI and achieve better economic growth results.

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Evaluating environmental performance using data envelopment analysis: The case of European countries

Cited by 85 publications

References 76 publications

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

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

A Two-Stage DEA Model to Evaluate the Technical Eco-Efficiency Indicator in the EU Countries

Moderating Effect of Institution in FDI-Growth Relationship in Developing Countries: A Case of Nigeria

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