The economic and environmental efficiency assessment in EU cross-country: Evidence from DEA and quantile regression approach

Moutinho, Víctor; Madaleno, Mara; Robaina, Margarita

doi:10.1016/j.ecolind.2017.02.042

Cited by 130 publications

(87 citation statements)

References 34 publications

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“…The results showed that these European countries had improved eco-efficiency in the time period 2005-2011. Moutinho et al [36] used a hybrid approach combining the DEA model with the quantum regression technique to assess the economic and environmental efficiency for European countries in 2001-2012. First, DEA was used to measure the performance of the countries, and then the quantum regression technique was used to identify different efficiency points among the countries.…”

Section: Relevant Researchesmentioning

confidence: 99%

Eco-Efficiency Assessment for Some European Countries Using Slacks-Based Measure Data Envelopment Analysis

et al. 2020

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One problem raised by the lack of energy efficiency is the generation of more greenhouse gases (GHGs) that can cause air pollution and climate change. Ecological efficiency (eco-efficiency) means the efficiency of resources used. A poor performance from this efficiency can then be detected for further improvement. In this research, we conduct an assessment on the eco-efficiency for some European countries as they consume a large part of global energy annually. A total of 17 European countries were selected as decision making units (DMUs) and assessed by the Slacks-based measure (SBM) Data Envelopment Analysis (DEA) model. Indices including Catch-Up, Frontier-Shift, and Malmquist Productivity Index (MPI) have been used to evaluate eco-efficiency, as well as efficiency change, technological change, and productivity change, over 2013-2017. In the model, energy consumption and share of renewable energy are used as energy inputs, and labor productivity and gross capital formation are used as economy inputs. On the other hand, GDP is used as a desired output, and CO 2 emissions is used as one undesired output. The experimental results show that the 17 countries as a whole lacked eco-efficiency in 2013-2017, implying more efforts are required to improve their eco-efficiency.Eco-efficiency is measurable based on selected input and output variables. For example, the authors of reference [2] measured the co-efficiency as the ratio between the value of what has been produced (e.g., GDP) and the environment impacts of the product or service (e.g., SO 2 emissions). The purpose of eco-efficiency measurement is to best utilize inputs such as energy, water, soil, and raw materials so as to maximize the benefit to human beings [4] or minimize bad outputs such as pollution and CO 2 , which can damage our environment. For every country in the world, improving eco-efficiency is necessary, as the protection of the environment is everyone's responsibility. Problem DefinitionOne problem raised by the lack of eco-efficiency is the generation of more greenhouse gases (GHGs), which can further lead to the global warming effect. The global warming effect, in turn, can lead to climate change, which might result in disasters and threaten the lives of human beings. International organizations have developed some programs to deal with the global warming effect. For example, the Paris Agreement initiated at the COP21 meeting held in December 2015 has set an objective to keep the rise in average global temperature below 2 • C [5]. The achievement of this difficult objective requires collective efforts from all countries. To achieve this objective, eco-efficiency is considered one of the effective approaches [6,7]. This is why the assessment of eco-efficiency has become the focus of this research. Though every country in the world needs to improve eco-efficiency, in this research, we focused on European countries, as they consume a lot of global energy annually. In fact, energy consumption, especially the use of fossil fuels, is one of the main s...

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Section: Relevant Researchesmentioning

confidence: 99%

Eco-Efficiency Assessment for Some European Countries Using Slacks-Based Measure Data Envelopment Analysis

et al. 2020

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“…With the advantages of being free from the strict assumptions for the data distribution hypothesis, along with effectively eliminating the interference of outliers and heavy-tailed distributions, quantile regression method is widely used in the existing literature [30][31][32][33][34]. A quantile regression approach may be more efficient than the OLS method when the residual series is non-normal [32].…”

Section: Empirical Strategymentioning

confidence: 99%

Can More Environmental Information Disclosure Lead to Higher Eco-Efficiency? Evidence from China

Huang

Neng-sheng

2018

Sustainability

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The present paper investigates the impact of pollution information transparency index (PITI) on eco-efficiency using a novel panel dataset covering 109 key environmental protection prefecture-level cities in China over the period [2008][2009][2010][2011][2012][2013][2014][2015]. We apply an extended data envelopment analysis (DEA) model, simultaneously incorporating metafrontier, undesirable outputs and super efficiency into slack-based measure (Meta-US-SBM) to estimate eco-efficiency. Then, the bootstrap Granger causality approach is utilized to test the unidirectional Granger causal relationship running from PITI to eco-efficiency. Results of DEA model show that there exist significant spatiotemporal disparities of eco-efficiency, on average, the eco-efficiency in eastern region is relative higher than those of central/western region. Estimates of ordinary least square (OLS) method, quantile regression, and spatial Durbin model document that the evidence of an inverted-U-shaped relation between PITI and eco-efficiency is supported, and the turning points vary from 0.3370 to 0.4540 with different model specifications. Finally, supplementary analysis of panel threshold model also supports the robust findings. Policy implications are presented based on the empirical results.

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“…It is considered inefficient when a score below 100% is achieved. This comparison also allows to determine both input and output targets corresponding to an efficient operation (Moutinho, Madaleno, & Robaina, 2017).…”

Section: Variables and Measuresmentioning

confidence: 99%

Environmental sustainability and financial performance of the small‐scale tea processors in Kenya

et al. 2018

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In the light of global warming, natural resource depletion and increasing stakeholder demand for environmental sustainability; corporate entities are compelled to reexamine their impact on the biophysical environment. Although the debate on how investment in environmental sustainability impacts on the corporates themselves is inconclusive, it is clear that combating negative environmental impacts can be very expensive and may substantially reduce the profits. Thus, this study sought to establish the relationship between environmental efficiency and profitability of small‐scale tea processors in Kenya. Using a random effects model on a 5‐year panel data (2012–2016) on all the 54 small‐scale tea processors in Kenya, the study found a negative correlation between environmental efficiency and profitability. The tea processors, whose environmental efficiency score was above 80%, recorded a paltry profitability of not more than 1.23%. The policy implication is that the tea processors may require motivation to take up environment conserving innovations and technologies in their production processes. These motivations could take the form of government subsidies or tax waivers on such innovations and technologies.

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The economic and environmental efficiency assessment in EU cross-country: Evidence from DEA and quantile regression approach

Cited by 130 publications

References 34 publications

Eco-Efficiency Assessment for Some European Countries Using Slacks-Based Measure Data Envelopment Analysis

Eco-Efficiency Assessment for Some European Countries Using Slacks-Based Measure Data Envelopment Analysis

Can More Environmental Information Disclosure Lead to Higher Eco-Efficiency? Evidence from China

Environmental sustainability and financial performance of the small‐scale tea processors in Kenya

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