Measuring the environmental efficiency of countries: a directional distance function metafrontier approach

International Environmental Efficiency Trends and the Impact of the Paris Agreement

This study estimates the environmental efficiency of 150 economies during the period of 2010–2017 to understand the environmental efficiency trend worldwide. This research adopts the meta-Malmquist approach to compare and capture the dynamic change in environmental efficiency among different income groups. The empirical results indicate that among the four income groups, only the low-income group suffers from regression in terms of environmental efficiency, while the high-income group achieves the greatest progress. For the high-income group, the source of improvement originates from the frontier shift rather than from efficiency change. By contrast, the improvement of the lower-income groups results from the catching-up effect. With regard to the effect of the Paris Agreement, only the lower middle-income group exhibits a statistical difference between the two periods, and environmental efficiency increases after the adoption of the Paris Agreement. The fight against global warming cannot succeed by relying only on specific countries. The whole world must cooperate and improve together, and thus, additional help must be devoted to the low-income group. The statistical results support that differences exist in terms of environmental efficiency among the four income groups. In particular, the low-income group is deteriorating.

Eco-efficiency convergence and technology spillovers of European industries

European policies regarding global warming have been outspread the last few decades with many initiatives focusing on industrial production process. In this paper we model eco-efficiency (ECOE) performance under a metafrontier (MF) framework for 14 industries of the manufacturing sector from 27 European countries over the 1995-2011 period. The utilization of NO_x, SO_x, CO₂, CH₄, N₂O, CO, NMVOC and NH₃ as undesirable outputs represent the impact of industrial activities on the environment. In a first stage, we estimate eco-efficiency using a conventional Directional Distance Function (DDF) as well as a non-radial slack-based DDF (DDFS) approach. In the second stage of our analysis, we investigate the existence of conditional and unconditional convergence by employing several methodologies. Our results point out that heavy industries perform eco-inefficiently. In addition, our results support the non-convergence hypothesis and the creation of discrete clubs with uneven characteristics when the distributional dynamics approach and the recent approach of Phillips and Sul (PS) come into play. Finally, the establishment of a catch-up index indicate that technological spillovers do exist but with a small effect.

Spatial-temporal characteristics and influencing factors of atmospheric environmental efficiency in China

This research constructs a super efficiency slack-based measure (SBM) model based on the Malmquist-Luenberger (ML) index to analyze the atmospheric environmental efficiency (AEE) of 30 provinces in China from 2000 to 2016 and explores the spatial and temporal differences of AEE by using the coefficient of variation method. This paper further analyzes the internal influencing factors of AEE via the ML index decomposition approach and establishes a panel data regression model to explore AEE's influencing factors in China. The results show some regional differences of the AEE level in China, with it the best in the eastern region and followed in order by the western and central region, and these differences exhibit an increasing trend year by year. During the study period, the development trend of AEE in China is similar to that in the eastern and western regions, showing a "W" shape, where in the central region it has a "U" pattern. The conclusion is that technical progress (TC) is the dominant factor affecting AEE, technical efficiency (EC) fails to effectively promote AEE improvement, and TC and EC present varying degrees of influence and different directions of action in the regions. The analysis results show that the influence effect of economic development on AEE presents a "U" pattern of first declining and then rising. The degree of China opening up to the outside world and its carbon dioxide emissions intensity have significant negative effects on AEE, whereas the increase of pollution control input effectively improves AEE.

Factors affecting eco-efficiency of municipal waste services in Tuscan municipalities: An empirical investigation of different management models

The efficient provision of municipal solid waste (MSW) services is essential from an economic and environmental perspective. This paper investigates the effect of ownership type on the eco-efficiency of MSW management in Tuscan municipalities. In the first stage of the analysis, the authors use a data envelopment analysis metafrontier approach with the integration of unsorted waste as an undesirable output. Three different clusters of municipalities are created based on the ownership type of the municipal waste operators: public, private, and mixed. In the second stage of analysis, the paper investigates factors affecting eco-efficiency in order to provide new knowledge that can be used by policy and decision makers to improve eco-efficiency. The results show that eco-efficiency is higher for municipalities that entrust the delivery of waste services to publicly owned firms compared to municipalities with delivery by mixed and private firms. Moreover, eco-efficiency in MSW management is higher for municipalities with younger residents, a larger population, and an overall higher population density. Smaller municipalities and those with less tourism manage their waste services more eco-efficiently than do bigger municipalities and those with more tourism. The results indicate that policy-makers should improve communication and engagement activities with older residents in smaller, less densely populated areas. In municipalities featuring heavy tourism, eco-taxes could be used to support these activities, avoiding any impact on residents.

Evaluating provincial eco-efficiency in China: an improved network data envelopment analysis model with undesirable output

In this study, an improved matrix-type network data envelopment analysis (NDEA) model with undesirable output was developed to evaluate the eco-efficiency of China's 30 provinces. The proposed model considered three linked but independent subsystems of the economy-society-environment cyclic system. Additionally, to allocate the weights of the NDEA model among the three subsystems (environment, economy, and society) of the eco-environment, a new relative reduction of the input-based method was proposed. The results show that, from 2003 to 2016, the average eco-efficiency of China's 30 provinces was low, ranging in [0.59, 0.73]. Qinghai and Hainan ranked first and second, respectively, in average eco-efficiencies, while both Shaanxi and Xinjiang had the lowest average eco-efficiencies. Affected by the low social subsystem efficiency, the eco-efficiency of 18 provinces decreased, but the range of the decrease was smaller than that of the increase in 11 other provinces in which the eco-efficiency improved. The average efficiency of the environmental subsystem is the highest among the three subsystems benefiting from reducing the emissions of "three industrial wastes," while economic subsystem owns the lowest average efficiency due to the input redundancy of total fixed assets and energy consumption. Compared with variables' projection, for most provinces, the undesirable output of the three industrial wastes should be reduced by more than 88.0%, while the positive outputs of atmospheric quality and per capita years of education should be increased by at least 61.0%.

Analysis of Environmental Productivity on Fossil Fuel Power Plants in the U.S

In 2007, the Clean Air Act officially included greenhouse gases, making fossil fuel power plants the first of key industries regulated by the Environmental Protection Agency. How do we measure the impact of the regulations on these power plants’ productivity? Previous studies that attempt to answer this question have provided inadequate answers because their samples cover the periods only up to 2007, and they often use greenhouse gases as the only proxy for the undesirable output. This paper collects data from 133 fossil fuel power plants in the United States and covers 2004 to 2013. These power plants are divided into Sun Belt and Frost Belt based on their geographical locations. To measure the undesirable outputs, we used both carbon dioxide and toxic emissions as the proxies. The estimation model includes the construction of a generalized common stochastic frontier (metafrontier) and a Malmquist productivity index. We used the index to measure the change in productivity for the power plants before and after the implementation of the regulation. The results indicate that, since regulation in 2007, the overall production efficiency of the power plants has declined incessantly while productivity has seen a sustained downward trend despite two surges in growth.