Level Of Environmental Efficiency Research Articles

Multi-directional efficiency analysis-based regional industrial environmental performance evaluation of China

This study evaluates the environmental efficiency of industrial sectors of Chinese major cities. The multi-directional efficiency analysis (MEA) approach is utilized for evaluation; thus, both the integrated MEA efficiency levels and the efficiency patterns, which are represented by the variable-specific MEA efficiency according to each type of the industrial pollutant emission or discharge, of Chinese major city are detected. In addition, the industrial energy conservation and pollutant reduction potentials are measured, and the relationship between environmental pressure and income is explored at the regional level of China. The main findings include the following: (1) The MEA environmental efficiency increases in the economically less developed cities were faster than the cities in the well-developed region, which indicates that the inequitable nationwide industrial developments of Chinese cities have started to alleviate. (2) Although some Chinese cities show similar environmental efficiency levels, the undesirable output variable-specific efficiency patterns of these cities are diversified, and according to the variable-specific efficiency, the most possible efficiency increase potential of each Chinese major city can be identified. (3) An N-shaped environmental Kuznets curve exists in the industrial sectors of Chinese major cities. (4) Different Chinese cities should have different industrial pollutant reduction priorities: East China cities should pay more attention to their industrial waste gas emissions and industrial waste water discharges, while west China cities should mainly focus on their industrial soot and dust emissions, and solid waste discharges.

Measuring the effect of Kyoto protocol agreement on countries’ environmental efficiency in CO2 emissions: an application of conditional full frontiers

This paper applies the probabilistic approach developed by Daraio and Simar (J Prod Anal 24:93–121, 2005, Advanced robust and nonparametric methods in efficiency analysis. Springer Science, New York, 2007a, J Prod Anal 28:13–32, 2007b) in order to develop conditional and unconditional data envelopment analysis (DEA) models for the measurement of countries’ environmental efficiency levels for a sample of 110 countries in 2007. In order to capture the effect of countries compliance with the Kyoto protocol agreement (KPA) policies, we condition first the years since a country has signed the KPA until 2007 and secondly the obliged percentage level of countries’ emission reductions. Particularly, various DEA models have been applied alongside with bootstrap techniques in order to determine the effect of KPA on countries’ environmental efficiencies. The study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating environmental performance issues. The results indicate a nonlinear relationship between countries’ obliged percentage levels of emission reductions and their environmental efficiency levels. Finally, a similar nonlinear relationship is also recorded between the duration which a country has signed the KPA and its environmental efficiency levels.

Environmental efficiency analysis of transportation system in China: A non-radial DEA approach

Many countries are worried about reducing energy consumption and environmental pollution while increasing the productivity and efficiency of their industries. This study intends to contribute to the literature by proposing a non-radial DEA model with the slacks-based measure (SBM) to analyze the environmental efficiency of China's transportation sector. The results show that most of the provinces in China do not have an eco-efficient transportation industry. The environmental efficiency levels in most of the provinces are lower than 50% of the ideal or target level. Therefore, China's transportation industry is environmentally very inefficient. China can reduce a great deal of carbon emissions in each province ranging from at least 1.6 million TOEs in Qinghai and at most 33 million TOEs in Guangdong and Shanghai.

A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from UK regions

This paper, by using conditional directional distance functions as introduced by Simar and Vanhems [J. Econometrics 166 (2012) 342–354] modifies the model by Färe and Grosskopf [Eur. J. Operat. Res. 157 (2004) 242–245] and examines the link between regional environmental efficiency and economic growth. The proposed model using conditional directional distance functions incorporates the effect of regional economic growth on regions’ environmental efficiency levels. The results from UK regional data reveal a negative relationship between regions’ GDP per capita and environmental inefficiency up to a certain GDP per capita level. After that level it appears that the relationship becomes positive. As an overall result the regional environmental inefficiency-GDP per capita relationship appears to have a ‘U’ shape form.

Do environmental characteristics influence foreign direct investment growth? A cross-national study, 1990-2000

The author engages several theoretical traditions in both economics and sociology to examine the impacts of levels of environmental efficiency and environmental institutions on foreign investment location in less-developed countries. Results from static score design panel OLS models of 52 countries provide mixed results. Less-developed countries with higher levels of carbon dioxide emissions per unit of gross domestic product attract higher levels of foreign investment, whereas less-developed countries with environmental ministries attract lower levels of foreign investment. Other independent variables - including sulfur dioxide emissions per unit of GDP, environmental treaty ratification, and environmental INGO presence/rate - show no statistically significant relationship with foreign investment location. The results underscore the continuing importance of the pollution havens hypothesis as well as the need for further research.

LINK BETWEEN ENVIRONMENTAL AND ECONOMIC EFFICIENCY

The study contains a theoretical and methodological examination of the relationship between the environmental and economic efficiency of firms. It reframes the crucial question, not whether, but when environmental efficiency improvements are profitable for firms? The paper develops the novel concept of eco profit and try to identifies three gaps in the previous knowledge: (1) the relationship may not be constant across environmental efficiency levels, which means that it needs to be considered a function of environmental efficiency; (2) the relationship may not be uniform across cases, which means that the determinants of environmental profit need to be identified; and (3) the relationship may not be static across time, which means that changes in the determinants of environmental profit over time need to be discussed.

Analysis of Environmental Efficiency Variation

AbstractIn this article, we develop and implement a methodology for analyzing the sources of variation in environmental efficiency across producers. We formulate a two‐stage model. In the first stage, we use stochastic frontier analysis to estimate both technical and environmental efficiency. In the second stage, we again use stochastic frontier analysis to regress estimated environmental efficiency scores against a variety of technology, physical environment, and management variables. In this stage we estimate the impact of each explanatory variable on environmental efficiency, and we derive conditional estimates of environmental efficiency from the one‐sided error component. We illustrate our methodology with an empirical application to a panel of Dutch dairy farms. We find evidence of relatively low levels of environmental efficiency, and we find that environmental efficiency can be improved through a number of policy options, including the provision of farmers with more insight into the nutrient balance of their farms.