Search Results (13)

As pivotal nodes in maritime logistics networks, ports face mounting pressure to reconcile economic growth with environmental sustainability. Although the SBM-Undesirable model has been extensively applied to assess port environmental efficiency (PEE), most applications assume strong disposability and disregard heterogeneity in technological capacities across different port scales, potentially biasing the assessments. To overcome these limitations, coastal ports are initially categorized into three subgroups based on operational scale criteria. A meta-frontier SBM-Undesirable model incorporating weak disposability is then developed to evaluate PEE. Dynamic characteristics are further explored via the Global Malmquist Index. Results indicate substantial disparities between subgroup frontiers and the meta-frontier. The average group PEE (0.732) exceeded the meta PEE (0.570), implying potential overestimation under homogeneity assumptions. Large-sized ports, with a mean technology gap ratio (TGR) of 0.956, operated near the meta-frontier, whereas medium-sized and small-sized ports, with TGRs of 0.770 and 0.600 respectively, exhibited substantial technological gaps. Total factor productivity (TFP) demonstrated a volatile upward trend, averaging 6.8% annual growth. In large-sized and medium-sized ports, TFP growth was primarily driven by technological innovation, whereas in small-sized ports, it stemmed from combined improvements in technical efficiency and technological level. These insights underscore the necessity of differentiated decarbonization strategies for port management. Full article

Improving agricultural green total factor productivity (AGTFP) is the key to achieving sustainable agricultural development and empowering agricultural modernization. Based on the panel data of 30 provincial levels in China from 2011 to 2021, AGTFP is measured using the non-expected MinDS super-efficiency—MetaFrontier Malmquist model, and the impact of environmental regulation (ER) and digital finance on AGTFP is analyzed using the spatial Durbin model (SDM). The results show the following: (1) ER can increase local AGTFP and has a positive spatial spillover effect. Command-based ER has the highest impact on AGTFP, followed by market-incentive and public-voluntary ER. (2) Digital finance has a direct promotional effect on local AGTFP, while it has an inhibitory effect on AGTFP in neighboring regions due to the siphon effect. (3) Digital finance is an important regulatory variable affecting AGTFP concerning command-based, market-incentive and public-voluntary ER. Digital finance plays a significantly moderating role in the effectiveness of the three ERs on AGTFP, with the market-incentive ER being the highest in eastern China. Nonetheless, digital finance has a significantly moderating effect on the effectiveness of command-based and public-voluntary ER on AGTFP, with command-based ER being higher in central China. Meanwhile, digital finance only plays a significantly moderating role in the effectiveness of command-based environment regulation on AGTFP in western China. This study provides valuable reference for policymakers concerning agriculture green production in varied regions. Full article

The efficient and sustainable management of forestry resources is crucial in ensuring economic and societal sustainability. The Chinese government has invested significantly in regulations, afforestation, and technology to enhance the forest resource efficiency, reduce technological disparities, and boost productivity growth. However, the success level of this undertaking is unclear and worth exploring. To this end, this study applied DEA-SBM, meta-frontier analysis, and the Malmquist productivity index to gauge the forest resource efficiency (FRE), regional technology heterogeneity (TGR), and total factor productivity growth (MI) in 31 Chinese provinces for a study period of 2001–2020. Results revealed that the average FRE was 0.5430, with potential growth of 45.70%, to enhance the efficiency level in forestry resource utilization. Anhui, Tibet, Fujian, Shanghai, and Hainan were found to be the top performers in forestry utilization during the study period. The southern forest region was ranked highest, with the highest TGR of 0.915, indicating advanced production technologies. The average MI score was 0.9644, signifying a 3.56% decline in forestry resource productivity. This deterioration is primarily attributed to technological change (TC), which decreased by 5.2%, while efficiency change (EC) witnessed 1.74% growth over the study period. The Southern Chinese forest region, indicating an average 3.06% increase in total factor productivity, ranked highest in all four regions. Guangxi, Tianjin, Shandong, Chongqing, and Jiangxi were the top performers, with prominent growth in MI. Finally, the Kruskal–Wallis test found a significant statistical difference among all four regions for FRE and TGR. Full article

Faced with the challenges of increasing demand and expanding emissions, China’s mining industry is at a crucial stage of sustainable development. In the context of the new technological revolution and industrial transformation, researching how the digital economy can promote the growth of green total factor productivity (GTFP) in China’s mining industry, particularly against the backdrop of technological diversity, is vital for achieving sustainable development and carbon neutrality goals. This study utilizes the meta-frontier Malmquist–Luenberger (MML) index to analyze the dynamics of GTFP in China’s mining industry under technological heterogeneity. It thoroughly examines the direct and indirect impacts of the digital economy (DE) on GTFP and delves into the underlying mechanisms of these effects using the spatial Durbin model. The empirical results reveal a significant positive relationship between DE and GTFP, particularly pronounced in the areas of technical efficiency and technological catch-up. Notably, this study identifies the mediating role of industrial structural upgrading in linking DE and GTFP. Additionally, the observed spatial spillover effect of DE on local mining GTFP suggests that the influence of DE extends beyond the immediate regions within the mining sector. Based on these findings, the study presents policy recommendations, emphasizing the need to integrate cutting-edge digital technologies in mining to enhance environmental sustainability. Full article

This research evaluates the effects of the Three Red Lines policy on water usage efficiency (WUE), production technology heterogeneity, and water productivity change in 31 Chinese provinces between 2006 and 2020. SMB-DEA, Meta-frontier analysis, and Malmquist–Luenberger index (MLI) techniques were employed for estimation. Results revealed that the mean WUE (2006–2020) in all Chinese provinces was 0.52, with an improvement potential of 48%. Shanghai, Beijing, Shaanxi, and Tianjin were the best performers. The WUE scores before (2006–2011) and after (2012–2020) water policy implementation were 0.58 and 0.48, respectively; on average, there was more than a 9% decline in WUE after the implementation of the water policy. The eastern region has the most advanced water utilization technology as its technology gap ratio (TGR) is nearly 1. The average MLI (2006–2020) score was 1.13, suggesting that the MLI has increased by 12.57% over the study period. Further technology change (TC) is the key predictor of MLI growth, whereas efficiency change (EC) diminished from 2006 to 2020. The mean MLI score for 2006–2011 was 1.16, whereas the MLI Score for the period 2012–2020 was 1.10, indicating a modest decline following the implementation of the water policy. All three Chinese regions experienced MLI growth during 2006–2020, with TC the main change factor. Full article

The improvement of grain processing capacity is crucial to the realization of grain security. Enterprises are important grain processing bodies and their productivity directly determines grain processing capacity. Chinese grain processing enterprises still have difficulties, and how to further improve grain processing capacity and the total factor productivity of grain processing enterprises may be an important aspect. We used the meta-frontier Malmquist index to measure the total factor productivity of grain enterprises as well as judge the change trend and regional gap, applying the classical regression model to test the convergence of China’s overall and regional grain enterprises’ total factor productivity. This research finds that the total factor productivity of grain processing enterprises increased by 1.18% annually during the sample period, and that of the central region rose more quickly than the other areas of China. Technical progress contributes more to enterprises’ total factor productivity, but technical efficiency may become a key factor in determining it. The difference in the growth rate of the grain processing enterprises’ total factor productivity among different ones in the eastern and western regions is gradually narrowing, while that of the central region is gradually expanding; there is an obvious technological catch-up effect between and within the regions, especially in the central area of China. Full article

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. Full article

Since thermal power generation is still one of the main sources of carbon emissions in China, the economic benefits and productivity of the thermal power generation industry have been seriously affected in recent years with the increasingly strict environmental regulations and restrictions on carbon emissions, as well as by the sharp fluctuations of coal prices. Therefore, it has been an important issue to improve the productivity performance of the thermal power industry. Due to the regional heterogeneity among different regions of China, we introduced a meta-frontier framework into the energy cost productivity model to develop a meta-energy cost productivity model. The energy cost gap between the group-specific and meta-frontiers was also utilized to assess the convergence rate of the group-specific frontier to the meta-frontier. The estimated results present that the energy cost efficiency of the eastern region outperformed that of the other two regions, and the cost Malmquist (CM) productivity of these three regions all showed positive growth, in which the progress of allocative efficiency and price effect were the main driving factors. Additionally, the central and western regions displayed the convergence of group-specific CM productivity towards the meta-frontier. Full article

Accurate assessment of the efficiency of securities companies is of great significance to improve the competitiveness of companies, due to their increasingly important role in supporting economic development. As the main contribution, this paper proposes a novel efficiency estimation framework for securities companies based on data envelopment analysis (DEA), which takes into account operational risks and technical heterogeneity. First, the risk variable is incorporated in the evaluation system as an undesirable output through the setting of weak disposability. Subsequently, the meta-frontier model is introduced to consider the impact of the technical heterogeneity of different companies to improve the accuracy of the assessment. Furthermore, this article also provides the meta-frontier Malmquist model, which can be utilized to analyze in detail technological progress. Finally, the securities companies listed in the Chinese stock market were selected as samples for empirical analysis. The efficiency evaluation model for securities companies proposed in this paper will provide a reference for related evaluation issues. Full article

Since air pollution is an important factor hindering China’s economic development, China has passed a series of bills to control air pollution. However, we still lack an understanding of the status of environmental efficiency in regard to air pollution, especially PM_2.5 (diameter of fine particulate matter less than 2.5 μm) pollution. Using panel data on ten major Chinese city groups from 2004 to 2016, we first estimate the environmental efficiency of PM_2.5 by epsilon-based measure (EBM) meta-frontier model. The results show that there are large differences in PM_2.5 environmental efficiency between cities and city groups. The cities with the highest environmental efficiency are the most economically developed cities and the city group with the highest environmental efficiency is mainly the eastern city group. Then, we use the meta-frontier Malmquist EBM model to measure the meta-frontier Malmquist total factor productivity index (MMPI) in each city group. The results indicate that, overall, China’s environmental total factor productivity declined by 3.68% and 3.49% when considering or not the influence of outside sources, respectively. Finally, we decompose the MMPI into four indexes, namely, the efficiency change (EC) index, the best practice gap change (BPC) index, the pure technological catch-up (PTCU) index, and the frontier catch-up (FCU) index. We find that the trend of the MMPI is consistent with those of the BPC and PTCU indexes, which indicates that the innovation effect of the BPC and PTCU indexes are the main driving forces for productivity growth. The EC and FCU effect are the main forces hindering productivity growth. Full article

Drawing on a perspective of technology heterogeneity, this study advances the analytical framework for evaluation of environmental efficiency (EE) across diverse economies. To improve the continuity and robustness of efficiency estimation, we construct a Hybrid Malmquist–Luenberger index under the meta-frontier (MHML) technique to allow a dynamic evaluation of environmental efficiency and to probe the underlying sources of inefficiency. Decomposition of the MHML index into component factors of efficiency change (EC), Best Practice Change (BPC) and Technological Gap Change (TPC) allows an improved understanding of causality and enhanced guidance for decision-making units (DMUs). Empirical tests based on panel data of the Group 20 countries spanning 2000–2014 reveal an upward improving trend in environmental efficiency but is also characterized by notable evidence of technological heterogeneity. Whereas technical progress was the main cause of environmental efficiency improvements in the G20 countries, for the BRICS (i.e., Brazil, Russia, India, China, South Africa), economic growth rates played a more significant in contrast to the role of technical change and allocation efficiency. The lagging growth rates of environmental efficiency for the G20 countries compared to the BRICS is a reflection of the fact that room for optimization in G20 countries was not as high as it was for BRICS and, China, in particular. China has been catching up with frontier technology whereas developing countries were shifting away from benchmark technology frontier. The developed economies remain the best performers and leaders in environmental technology. However, the BRICS countries, represented by China, remain on an upward trajectory of improvements’ in EE with gains from managerial sufficiency and technological advancement. The MHML index developed here provides a robust quantitative measure for policy interventions to support overall national environmental performance. Context-specific suggestions are proposed to foster efficiency gains and green transition for Chinese development scenarios against best performing economies. Full article

With the contradiction between energy supply and demand around the world, urbanization formed with high-investment, high-consumption, and high-emission has significantly impaired the ecological environment of China. The evaluation of environmental impact is a must for decision-makings related to sustainable urbanization. This paper assessed the dynamic environmental performance of 285 cities in China from 2005 to 2013 based on the Malmquist-Luenberger index, an expanded data envelopment analysis (DEA) model. To ensure comparability among cities, a two-step clustering method was used to classify all cities into three types. From the results, we found (1) 166 and 185 cities’ environmental conditions remained the improvement during the research period under the meta-frontier and group frontier respectively. (2) Low and Medium energy intensity cities performed better than high energy intensity cities. (3) The environmental performance under the group frontier was overestimated compared with the meta-frontier. (4) The trends of environmental improvement and economic growth are significantly inconsistent. Overall, all ways to decrease undesirable outputs and increase desirable outputs, such as technological innovation, industrial structure optimization and regional cooperation, should be encouraged to achieve urban, regional and country sustainability. Full article

Resource depletion and environmental degradation have become serious challenges for China’s sustainable development. This paper constructs indicators to assess China’s green economy performance and green productivity growth, in which economic expansion, resource conservation and environmental protection need to be incorporated simultaneously. For this purpose, we combine non-radial directional distance function and meta-frontier Malmquist productivity to develop the indicators. The methodology also allows for the decomposition of driving forces of China’s green economy. Moreover, the dataset employed in this paper allows for the evaluation of 275 cities in China during the period 2003–2012. The main findings are as follows. First, most of China’s cities did not perform efficiently in terms of the green economy, with an average score of only 0.233. Second, the growth rate of green productivity is slower than real GDP, and the green productivity growth in China is only moderate. Third, innovation is the main driving force of China’s green productivity growth, but the central region lags behind when it comes to green innovation. Fourth, artificial local protectionism and transport limitations impede the progress of cities that perform ineffectively in the green economy. Based on our empirical findings, we provide policy implications and suggestions for enhancing China’s green economy performance and productivity growth. Full article