The legacy environmental footprints of manufactured capital.

The foundations of today's societies are provided by manufactured capital accumulation driven by investment decisions through time. Reconceiving how the manufactured assets are harnessed in the production-consumption system is at the heart of the paradigm shifts necessary for long-term sustainability. Our research integrates 50 years of economic and environmental data to provide the global legacy environmental footprint (LEF) and unveil the historical material extractions, greenhouse gas emissions, and health impacts accrued in today's manufactured capital. We show that between 1995 and 2019, global LEF growth outpaced GDP and population growth, and the current high level of national capital stocks has been heavily relying on global supply chains in metals. The LEF shows a larger or growing gap between developed economies (DEs) and less-developed economies (LDEs) while economic returns from global asset supply chains disproportionately flow to DEs, resulting in a double burden for LDEs. Our results show that ensuring best practice in asset production while prioritizing well-being outcomes is essential in addressing global inequalities and protecting the environment. Achieving this requires a paradigm shift in sustainability science and policy, as well as in green finance decision-making, to move beyond the focus on the resource use and emissions of daily operations of the assets and instead take into account the long-term environmental footprints of capital accumulation.

Towards sustainable development goals: An analysis of environmental efficiency and the impacts of self-purification capacity across diverse income levels.

The increasing urgency of global environmental degradation, particularly across diverse economic development stages, underscores a critical need for nuanced understanding and targeted strategies to achieve Sustainable Development Goals. Our study examines environmental efficiency trends over 27 years in 163 countries, utilizing greenhouse gases and particulate matter 2.5 as indicators. We address the challenge by developing and applying a two-stage method that combines a hyperbolic distance function with a stochastic meta frontier approach to assess environmental meta-efficiency. The average meta efficiency of these countries is 0.464, which remains at a relatively low level. Our model indicates that the high-income country group needs to reduce greenhouse gas and pollutant emissions by 25% and increase non-fossil energy usage by 33% to improve environmental efficiency. This suggests these countries must transition towards more sustainable energy sources and practices. Moreover, recognizing that existing income grouping inadequately characterizes each country, we use k-means cluster analysis for regrouping, more accurately reflecting individual differences. The regrouping results show that some high-income countries are classified into inactive groups, implying serious environmental problems. Our findings advocate for collaborative and tailored strategies to address these disparities. We conclude that income levels cannot solely drive environmental efficiency but must also consider geographical and climatic factors, which are pivotal in shaping a country's environmental policies and efforts. This approach offers a clearer understanding of current inefficiencies and sets the stage for more informed policy-making that can better address the specific needs and capabilities of different countries.

Fintech and environmental efficiency: The dual role of foreign direct investment in G20 nations.

This study investigates the relationship between financial technology (fintech) and environmental efficiency across G20 countries, emphasizing the moderating effect of foreign direct investment (FDI) from 2010 to 2022. Employing Data Envelopment Analysis (DEA) through both Slack-Based Measure (SBM) and Epsilon-Based Measure (EBM), alongside Tobit regression and the Generalized Method of Moments (GMM) for analytical rigor, the research reveals that fintech exerts a positive influence on environmental efficiency within these countries. Furthermore, it demonstrates that FDI contributes to enhancing environmental efficiency. However, when FDI is combined with fintech investments, it yields a negative impact. This detrimental effect stems from FDI's emphasis on short-term gains, rapid expansion, and a globally oriented supply chain that favors cost efficiency at the expense of sustainability. The study highlights the necessity for investments in fintech that comply with environmental standards and offers policy recommendations to improve environmental efficiency. It urges policymakers to promote environmentally sustainable investment practices within the fintech sector to aid in achieving sustainable development goals.

Estimation of genetic parameters and single-step genome-wide association studies for milk urea nitrogen in Holstein cattle.

The main objectives of this study were to estimate genetic parameters for milk urea nitrogen (MUN) in Holstein cattle and to conduct a single-step (ss)GWAS to identify candidate genes associated with MUN. Phenotypic measurements from 24,435 Holstein cows were collected from March 2013 to July 2019 in 9 dairy farms located in the Beijing area, China. A total of 2,029 cows were genotyped using the Illumina 150K Bovine Bead Chip, containing 121,188 SNP. A single-trait repeatability model was used to evaluate the genetic background of MUN. We found that MUN is a trait with low heritability (0.06 ± 0.004) and repeatability (0.12). Considering similar milk production levels, a lower MUN concentration indicates higher nitrogen digestibility. The genetic correlations between MUN and milk yield, net energy concentration, fat percentage, protein percentage, and lactose percentage were positive and ranged from 0.02 to 0.26. The genetic correlation between MUN and somatic cell score (SCS) was negative (-0.18), indicating that animals with higher MUN levels tend to have lower SCS. Both ssGWAS and pathway enrichment analyses were used to explore the genetic mechanisms underlying MUN. A total of 18 SNP (located on BTA11, BTA12, BTA14, BTA17, and BTA18) were found to be significantly associated with MUN. The genes CFAP77, CAMSAP1, CACNA1B, ADGRB1, FARP1, and INTU are considered to be candidate genes for MUN. These candidate genes are associated with important biological processes such as protein and lipid metabolism and binding to specific proteins. This set of candidate genes, metabolic pathways, and their functions provide a better understanding of the genomic architecture and physiological mechanisms underlying MUN in Holstein cattle.

Unveiling the environmental efficiency puzzle: Insights from global green innovations.

The latest surge of global uncertainty and disruptions in global supply networks put policymakers under pressure to emprise green innovations as a vital tool to address environmental concerns. However, producing green innovations doesn't always help in achieving environment-related sustainable development goals. Therefore, in this study, we endeavour to investigate to what extent green innovations are efficient in improving environmental efficiency. To this end, a network bias-corrected data envelopment analysis and clustering analysis is applied. The data used in this study covers 42 countries from different regions, spanning from 2000 to 2020. The results reveal that most countries have not made major advancements in environmental efficiency signifying the low level of green innovations utilization to achieve environment-related sustainable development goals (SDGs). Additionally, the results demonstrate a U efficiency curve for inputs-oriented green innovations efficiency over time, indicating that the initial stages of green innovations production are associated with a decreased return. However, over time, the efficiency exhibits an upward trend. The benchmarking analysis reveals that South American and European Union nations set the bar for other countries in terms of efficiently leveraging green innovations to achieve SDGs. Our findings also suggest that environmental efficiency is more dependent on green-supporting policies such as green energy production and green taxes. As a result, we conclude that achieving environmental SDGs while utilizing green innovations does not always result in the development of other SDGs. Therefore, policymakers need to prioritize pursuing a green developmental approach and supporting policies to achieve environment-related SDGs and other SDGs.

Assessing the environmental efficiency of OECD countries through the lens of ecological footprint indices.

Environmental efficiency plays a crucial role in achieving sustainable economic development. This study aims to enhance the current understanding of dynamic environmental efficiency by using Data Envelopment Analysis (DEA) in conjunction with the ecological footprint index. This study evaluates 27 OECD countries' environmental performance from 2000 to 2017, employing net capital stock, labor force, and energy consumption as inputs, ecological footprint as undesirable output, and GDP as desirable output. We utilize 16 window Slack-Based Measurement DEA (SBM-DEA) models, each representing consecutive years within the observation period. Additionally, we adopt the Global Malmquist-Luenberger Index (GMLI) techniques to facilitate a simultaneous evaluation of the efficiency levels for each country. Our findings reveal that the United Kingdom and Lithuania were the most and least ecologically efficient countries among the 27 OECD countries, respectively. Over the 18-year observation period, all countries showed both progress and setbacks in environmental efficiency, with a modest overall improvement. Poland, Denmark, Slovakia, and Lithuania were the most improved countries in environmental performance, while Canada and Japan showed the most significant regressions in environmental efficiency. We highlight the need for policymakers to prioritize sustainable economic growth and consider ecological footprints when making economic decisions to enhance environmental efficiency in OECD countries. Our findings have can guide policymakers in designing effective policies and strategies to enhance environmental efficiency and promote sustainable economic development.

Human Capital, Trade Competitiveness and Environmental Efficiency Convergence Across Asia Pacific Countries.

This study mainly investigates 14 Asia Pacific economies' environmental efficiency. Departing from previous studies ignoring environmental technology heterogeneity, we evaluate environmental efficiency through metafrontier super epsilon based model (EBM). We compare environmental efficiency convergence across different regions via unit root test and truncated regressions. We analyze how trade competitiveness impact environmental efficiency. We also explore effect of green technology and human capital on environmental efficiency from the perspective of endogenous growth. Our findings indicate that stochastic and absolute ß-convergence tendencies were confirmed. Human capital can enhance environmental efficiency convergence. Trade competitiveness showed a mixed impact on environmental efficiency convergence, confirming scale, composition and technical effects. It is better to enhance human capital, strengthening environmental regulations under international competition as well as relentlessly pursuing green industrialization across Asia Pacific countries.

Manufacturing transfer and environmental efficiency: Evidence from the spatial agglomeration of manufacturing in China.

Manufacturing transfer is an important factor in optimizing the spatial distribution of resources and promoting regional environmental efficiency. Based on the manufacturing data of 30 provinces in China from 2005 to 2017, the spatial Durbin model is used to investigate the impact of three types of manufacturing transfer and spatial agglomeration effects on environmental efficiency under the spatial weight matrix of economic distance. The results show that the improvement of environmental efficiency is inhibited by the transfer of labor-intensive manufacturing but facilitated by the spatial agglomeration of such manufacturing. The transfer of capital and technology-intensive manufacturing has no significant impact on environmental efficiency. Environmental efficiency is significantly improved by the spatial agglomeration of technology-intensive manufacturing but significantly inhibited by that of capital-intensive manufacturing. Third, the impact of three types of manufacturing transfer on environmental efficiency is analyzed from the perspective of regional heterogeneity. This paper puts forward relevant policy suggestions from the perspectives of manufacturing transfer, the agglomeration effect, so as to further improve the environmental efficiency.

Policy, technical change, and environmental efficiency: Evidence of China's power system from dynamic and spatial perspective.

Feed-in tariff (FIT) and renewable portfolio standard (RPS) policies have been implemented to facilitate wind and solar power technologies with the aim of achieving sustainable development in power system. It is essential to study how efficient these policies are in accelerating technical progress and how efficient the power system is in balancing development and environmental protection. Dynamic network data envelopment analysis and the global Malmquist productivity index are first employed to study the environmental efficiency and technical progress, after which a dynamic spatial Durbin model is applied to analyze the impact of policies on technical progress. The results reveal that both FIT and RPS lead to technical progress which is the main driving force in environmental efficiency improvement, but that RPS performs better than FIT. From a spatial perspective, the adjacent regions usually show similar characteristics in technical progress. Therefore, future policy design should carefully consider the regional agglomeration effects and should effectively strengthen the implementation of RPS policy.

Does high-speed rail make firms cleaner in China?

With the firm level datasets from 2004 to 2014, this paper uses the difference in differences (DID) estimator to explore the effects of China's high-speed rail (HSR) on firms' environmental efficiency. We find that China's HSR lowered SO2 intensity (SO2 per unit output value) by approximately 7.9%. More importantly, firms reduce SO2 intensity mainly through innovation, productivity improvement, and the agglomeration of firms. Our additional analyses show that these observed effects of HSR are mainly driven by firms in core cities, while the environmental efficiency of firms in the peripheral cities seems to be unaffected. Heterogeneous effects indicate that the HSR has a more significant effect on dirty firms, state-owned firms, foreign firms, and large firms. Our results suggest that HSR construction could have contributed to the China's environmental governance.

Measuring energy and environmental efficiency interactions towards CO2 emissions reduction without slowing economic growth in central and western Europe.

Given the economic growth and energy consumption patterns, most countries are striving to solve the problems of CO2 emissions reduction to achieve sustainable development. This paper employs an improved DEA model to measure energy and environmental efficiency for some selected countries in central and western Europe. In addition, the DEA window evaluation technique is applied to measure cross-sectional efficiency using two inputs (energy consumption, labor force), a desirable output (gross domestic product), and an undesirable output (CO2 emission) for the period from 2010 to 2014. The study finds that the UK ranks the highest position in term of energy and environmental efficiency. This shows that the UK has more effective policies regarding energy efficiency, consumption, production, import and energy intensity measures for sustainable economic growth as well as environmental protection. Ireland is the second-best country after the United Kingdom. The efficiency scores of the two countries are 0.99 and 0.89 respectively. On the empirical outcomes, this study suggests effective reforms in energy sector for countries with less energy efficiency that are still facing the problem of environmental degradation.

Trade-off analysis of cost and nutrient efficiency of coffee farms in vietnam: A more generalised approach.

Literature has documented significant trade-offs between economic and environmental performance in many areas of agricultural production. However, while it has focused on the trade-off for technically efficient farms there are differing types of trade-offs that exist for differing types of farms. The present paper addresses these gaps in the literature by proposing a more generalised approach to analysing cost and environmental trade-offs. There is also a lack of research on the nature of the trade-off in coffee farming. This is especially so in Vietnam where there is both significant overuse of nutrients and increasing autonomous adaption through voluntary participation in sustainability certification schemes. The proposed framework is employed to investigate a data set of 679 Vietnamese coffee farms. This study delivers several important findings. First, the proposed approach indicates four distinct groups of farms facing differing types of trade-offs with some farms not facing any trade-offs. Second, empirical results show that the average levels of technical, cost and environmental efficiency are relatively low. Third, sustainability certified farms are found to perform better than non-certified farms although the differences in performance diminish over time. Overall, the empirical results favour a heterogeneous and more integrated policy approach to improving the technical, cost and environmental efficiency of coffee farmers in Vietnam.

Characteristics, exchange experience, and environmental efficiency of mayors: Evidence from 273 prefecture-level cities in China.

The existing literature on environmental efficiency focuses on economic and social factors, and rarely on the role of local leadership. Thus, this study aims to measure the environmental efficiency and analyze the impact of mayors' characteristics on environmental efficiency. By using the metafrontier-stochastic frontier analysis two-step estimate method, the average value of the overall environmental efficiency in China is only 0.523, which is high in the eastern region and low in the central and western regions. Empirical results show that mayors' tenure plays an inverted U-shaped effect on environmental efficiency. Mayors who are highly educated, young, and aware of environmental protection can improve environmental efficiency. Moreover, mayors' experience in official exchange can improve environmental efficiency; mayors with work experience in the central government are effective in terms of environmental governance. The policy implication is that improving the educational level of leaders, appointing young cadres, and strengthening official exchanges can effectively improve environmental efficiency.

Industrial policy, energy and environment efficiency: Evidence from Chinese firm-level data.

Based on a unique micro-level dataset of 30,689 mining enterprises from 2008 to 2011, this paper uses the non-radial directional distance function (NDDF) to calculate the unified efficiency index (UEI) and energy-environmental performance index (EEI) for China's mining enterprises. The double bootstrap method is then used to test how tax incentive policies affect the UEI and EEI of China's mining enterprises. The results show that: (1) the UEI and EEI of Chinese mining enterprises first decreased and then increased over the sample period; overall, Chinese mining enterprises had low energy and environmental efficiency, especially the coal mining enterprises, private mining enterprises and mining enterprises in the central and western regions. (2) Tax incentives positively affect the energy and environmental efficiency of mining enterprises, especially the efficiency of coal mining enterprises, non-state-owned mining enterprises and mining enterprises in the central and western regions. Our results remain robust after using the propensity score matching estimator (PSM). (3) There is a positive feedback between tax incentives and energy and environmental efficiency, more efficient mining enterprises receive more government incentives. Further analysis shows that although tax incentives do not reduce the total energy consumption of enterprises, reducing the energy consumption of enterprises can improve their UEI and EEI. In addition, R&D investment, profitability and resource taxes all contribute to improving the UEI and EEI of mining enterprises.

Does industrial agglomeration facilitate environmental performance: New evidence from urban China?

This paper presents new evidence on the impact of industrial agglomeration on environmental performance with a sample of prefectural-cities in China. When environmental performance is represented by pollution intensity, the impacts of industrial agglomeration on pollution intensity in terms of sulfur dioxide and soot show the heterogeneous pattern. The results support the existence of a non-linear pattern between agglomeration and emission intensity of sulfur dioxide, whereas the non-linear model could not hold for the emission intensity of soot. However, when we measure environmental performance with environmental efficiency estimated by a data envelopment analysis approach, it documents a U-shape relationship between industrial agglomeration and environmental efficiency. Specifically, environmental efficiency deteriorates in the early stage of industrial agglomeration and then improves as local industrial agglomeration proceeds. Different estimation strategies provide consistent evidence to verify such U-shape pattern.

How public environmental concern affects the sustainable development of Chinese cities: An empirical study using extended DEA models.

China is now facing the formidable tasks of saving energy and reducing emissions, so it is very important to analyze China's energy and environmental efficiency. However, previous studies have rarely paid attention to the cross-impacts that different forms of public environmental concern (PEC) have simultaneously on energy and environmental efficiency. To investigate how these two types of efficiency change along with PEC variations, this paper employs six extended programming models which are developed based upon the theory of Data Envelopment Analysis (DEA) and the directional distance function (DDF). An empirical analysis of data from 239 Chinese prefecture-level cities demonstrates the techniques. The empirical results show that PEC variations can significantly affect the environmental efficiency only if the city is experiencing unsustainable development. This work also shows that PEC about input resources may exaggerate the environmental efficiency, implying that the public may be more tolerant of resource over-consumption than of pollutant over-emission.

Energy and environmental efficiency of OECD countries in the context of the circular economy: Common weight analysis for malmquist productivity index.

Circular economy (CE) aims at sustainable development (SD) by focusing more on renewable sources of energy and precise management of waste to i) guarantee the secure access to resources, ii) combat climate change and global warming. Environmental issues arising from energy use and lack of policies to monitor them challenge sustainable development. Circular economy emphasizes the economic development with the least amount of undesirable environmental impacts. To evaluate the environmental performance of decision-making units (DMUs) with data envelopment analysis (DEA), this paper develops a common set of weights (CSW) model using the ideal point method. Therefore, energy and environmental efficiency of the organization for economic cooperation and development (OECD) countries is analyzed using the Malmquist productivity index (MPI) during 2012-2015. Although Switzerland has the highest energy and environmental efficiency during 2012-2014, findings indicate that Ireland and the USA have continuously improved their energy and environmental efficiency.

Does migration of pollution-intensive industries impact environmental efficiency? Evidence supporting "Pollution Haven Hypothesis".

The existence of Pollution Haven Hypothesis (PHH) is still being hot debated due to its importance in environmental and industrial policymaking. However, research concerning the PHH in relation to local areas and regions within country borders is limited. Therefore, this research focused on the relationship between the migration of pollution-intensive industries (PIIs) and environmental efficiency (EE) at the prefecture level throughout China's Guangdong Province from 2001 to 2014. Firstly, this research found that many PIIs migrated from the core industrial region of the Pearl River Delta (PRD) to peripheral Non-Pearl River Delta (NPRD) areas after 2006. A Data Envelopment Analysis (DEA) model was used to evaluate industrial EE of a range of different cities. Then, analysis using PMG/ARDL regression model shows that industrial EE maintained a negative long run equilibrium relationship with PII migration in the NPRD region where PIIs have moved out, but had little correlation with PII migration in the PRD where PIIs have moved in. The results show pollution transfer caused by migration of PIIs from the PRD to the NPRD region in Guangdong Province that supports the PHH. The NPRD had become a pollution haven for PIIs in the PRD. This study proposes that policymakers should build a series of environmental regulatory policies and industrial developing policies to avoid the creation of pollution havens in the developing area in China, instead of simply pollution emission control policies.

Sand dredging and environmental efficiency of artisanal fishermen in Lagos state, Nigeria.

Environmentally detrimental input (water turbidity) and conventional production inputs were considered within the framework of stochastic frontier analysis to estimate technical and environmental efficiencies of fishermen in sand dredging and non-dredging areas. Environmental efficiency was low among fishermen in the sand dredging areas. Educational status and experience in fishing and sand dredging were the factors influencing environmental efficiency in the sand dredging areas. Average quantity of fish caught per labour- hour was higher among fishermen in the non-dredging areas. Fishermen in the fishing community around the dredging areas travelled long distance in order to reduce the negative effect of sand dredging on their fishing activity. The study affirmed large household size among fishermen. The need to regulate the activities of sand dredgers by restricting license for sand dredging to non-fishing communities as well as intensifying family planning campaign in fishing communities to reduce the negative effect of high household size on fishing is imperative for the sustainability of artisanal fishing.

Environmental efficiency of energy, materials, and emissions.

This study estimates the environmental efficiency of international listed firms in 10 worldwide sectors from 2007 to 2013 by applying an order-m method, a non-parametric approach based on free disposal hull with subsampling bootstrapping. Using a conventional output of gross profit and two conventional inputs of labor and capital, this study examines the order-m environmental efficiency accounting for the presence of each of 10 undesirable inputs/outputs and measures the shadow prices of each undesirable input and output. The results show that there is greater potential for the reduction of undesirable inputs rather than bad outputs. On average, total energy, electricity, or water usage has the potential to be reduced by 50%. The median shadow prices of undesirable inputs, however, are much higher than the surveyed representative market prices. Approximately 10% of the firms in the sample appear to be potential sellers or production reducers in terms of undesirable inputs/outputs, which implies that the price of each item at the current level has little impact on most of the firms. Moreover, this study shows that the environmental, social, and governance activities of a firm do not considerably affect environmental efficiency.