Global Malmquist-Luenberger Productivity Index Research Articles

Carbon productivity growth in China’s transportation industry: empirical analysis using a global Malmquist-Luenberger productivity index based on an endogenous directional distance function

In China, transportation is one of the fastest-growing industries for CO2 emissions, so scientifically measuring the carbon total factor productivity growth of this industry could provide accurate guidance to achieve sustainable development. To this end, this study proposes an endogenous directional distance function (DDF) approach using a common directional vector based on satisfaction degree, and then integrates it with the global Malmquist-Luenberger productivity index (GMLPI) to measure the carbon total factor productivity growth. We employ this novel endogenous DDF-based GMLPI approach to evaluate and decompose the carbon total factor productivity growth of China’s 30 provincial-level transportation industries from 2010 to 2020. The empirical results show that the carbon total factor productivity of 14 provinces improved during 2010–2020, and 28 provinces from 2015 to 2020. Efficiency improvement and technological progress have become the joint drivers for the carbon total factor productivity growth. Targeted policy implications are provided.

Quantitative analysis of spatiotemporal disparity of urban water use efficiency and its driving factors in the Yangtze River Economic Belt, China

Study regionYangtze River Economic Belt, China Study focusAs the major national strategic development area of China, there have always been vital problems about imbalance of the water resources distribution and the disparity of economic levels in YREB. Quantitative analysis of water use efficiency (WUE) is essential to the rational use of water resources, as well as the sustainable development. In this study, a WUE evaluation index system for prefecture-level cities in the YREB was constructed, and Super-Efficiency Data envelopment analysis Slacks-Based Measure (DEA-SBM) model, Global Malmquist-Luenberger productivity index, combined with geographically weighted regression model were utilized to measure and identify the spatiotemporal evolution characteristics of WUE and its influencing factors. New hydrological insights for the regionFrom the temporal perspective, the WUE manifests a significant upward trend from 2005 to 2020, and the growth presents lower reach > middle reach > upper reach; in the spatial pattern, the WUE has significant spatial divergence characteristics, high WUE mainly occurred in developed leading cities, while developing cities in the midstream and upstream tended to be inefficient; various effects on WUE were also analyzed, highlighting that technical advancement was the key driver of WUE evolution. Then the negative effects of industrial structure and urban environment was becoming more and more significant. Finally, effective measures for upstream, middle and downstream cities in the YREB were discussed.

Analysis of transportation CO2 emission efficiency in the Yangtze River Economic Belt in China

ABSTRACT The transportation industry’s CO2 emissions and its main drivers are important for achieving sustainable development. With data from the Yangtze River Economic Belt (YEB) between 2004 and 2020, the efficiency of CO2 emissions is investigated by the super efficiency epsilon-based measurement method (super-EBM) and the Global Malmquist Luenberger Productivity Index (GML). The influencing factors on the different efficiency levels are explored by the panel quantile regression. This study shows that the overall CO2 emissions efficiency is not high, and the efficiency in different regions is largely consistent with the regional economy level. COVID-19 may reduce urban transport carbon emissions in the Yangtze River Economic Belt in 2020, as reflected by the reductions in average emissions and emissions efficiency. Findings also suggest that the influence of the number of private vehicles per 10,000 people on efficiency is positive at low and middle quantiles, and negative at high quantiles. Besides, the per-capita GDP, energy intensity, and transportation service structure negatively influence the efficiency at all quantiles, whereas urbanization and transportation intensity are positively related to the emissions efficiency.

Interplay of Urbanization and Ecological Environment: Coordinated Development and Drivers

The interplay between urbanization and ecological environmental efficiency has gained increasing significance in the context of sustainable development, as rapid urban growth poses challenges to resource consumption, greenhouse gas emissions, and the overall ecological well-being of urban areas. Understanding and analyzing the coordinated development of urbanization and ecological environmental efficiency, as well as assessing the influence of drivers on this relationship, is crucial for developing effective policies and strategies that promote environmentally sustainable urban development. This study establishes an urbanization index based on four key aspects: economy, society, population, and ecology. This investigation focuses on 30 provinces in China spanning from 2011 to 2020. The following methods are applied: global Malmquist–Luenberger productivity index, entropy method, TOPSIS model, coupled coordination degree model, panel-corrected standard error (PCSE), and feasible generalized least squares (FGLS) models. The empirical results demonstrate a favorable level of coordinated development between urbanization and the ecological environment overall, with more pronounced regional evolution trends. The trade openness, energy structure, and digitalization level play significant roles in effectively promoting the coordinated development of urbanization and the ecological environment to varying extents. The growth of trade openness and digitalization level promote coordinated development between urbanization and the ecological environment by 0.125 and 0.049, respectively. However, the increase in the energy structure decreases it by 0.509. These results have significant implications for policymakers, urban planners, and stakeholders, emphasizing the need for a balanced approach that prioritizes ecological environmental protection in urbanization efforts. This study underscores the importance of sustainable urban development strategies to ensure long-term ecological and environmental sustainability.

Environmental assessment of hydrogen: does hydrogen matter for environmental efficiency improvement?

ABSTRACT This paper first measures the level of environmental efficiency (EE) in 72 countries between 2001 and 2019 by adopting the Global Malmquist-Luenberger productivity index in the framework of the super slack-based-measure model. Then, by using the instrument variable-generalized method of moments (IV-GMM) approach, we examine the role of hydrogen development in increasing EE. We also pay attention to the asymmetric effect, the moderating effect, and the mediating effect in the hydrogen development-EE nexus. Several findings are highlighted as follows: (1) Hydrogen development can significantly increase EE. (2) The marginal impact of hydrogen development on EE is significantly positive in countries with a high level of EE, while it is insignificant in countries with a low level of EE, which shows the asymmetric EE enhancement effect of hydrogen development. (3) Foreign direct investment is a key moderating variable in the nexus between hydrogen development and EE, which can strengthen this positive nexus. And (4) mediating effect analysis documents that technological progress is an effective mediating variable through which hydrogen development affects EE. According to these results, we propose several policy implications for the acceleration of hydrogen development and EE.

The Role of Environmental Regulations, Renewable Energy, and Energy Efficiency in Finding the Path to Green Economic Growth

European Union (EU) countries pay meticulous attention to environmental issues and achieve carbon-free development. In this direction, reducing greenhouse gas emissions and extending renewable energy are the primary goals. At the same time, the energy price and declining energy efficiency increase countries’ environmental expenditures and hinder their capabilities for economic growth. Against this backdrop, this research aims to examine the influence of environmental regulations, renewable energy, and energy efficiency on green economic growth. The originality of the study is twofold: first, it evaluates the green economic growth of a country, which simultaneously reveals the options for economic growth and the capability to eliminate its negative effect on the environment by applying the Global Malmquist–Luenberger productivity index; second, it develops an econometric model based on panel data for EU countries for 2000–2020 to investigate the nonlinear impact of environmental regulations, the effect of extending renewable energies, and the growth of energy efficiency on a country’s green economic growth. The study applies the following methodology: a system generalized method of moments (GMM) analysis. The empirical results confirm the U-shape, nonlinear impact of environmental regulations on a country’s green economic growth along with a gradual increase in energy efficiency. In addition, the findings indicate that renewable energy is crucial for furthering a country’s green economic growth. At the same time, environmental regulation has a significant role in extending renewable energy. The study results could be used as the basis for implementing green economic growth for EU countries and improving the policy of carbon-free development of these countries.

The Effects of Urbanisation on Green Growth within Sustainable Development Goals

The Green Deal policy and Sustainable Development Goals require that the economic development of a country should be reoriented towards ‘green‘ economic development. Currently, the globalisation and intensification of production boosts urbanisation in many countries, which may stimulate economic growth and improve citizen well-being, but may also lead to excessive consumption of resources and negative environmental impacts. Against the backdrop of these challenges, it is expedient to estimate the effects of urbanisation on the green growth of a country and define the relevant changes and instruments for achieving green growth in a country in view of urbanisation. The research covers the EU countries and Ukraine (as an official candidate for European Union membership) in the period of 2005–2020. Applying the Global Malmquist–Luenberger productivity index (to estimate green economic growth); a fixed and random effects model, GMM modelling (to evaluate the impact of urbanisation on green economic growth), this study aimed to contribute to the theoretical framework of green economic growth by extending input and undesirable output parameters of a country’s productivity. The findings revealed that, in 2020, as compared to 2005, green economic growth went into a decline in all countries analysed, this decline stemmed from accelerated urbanisation. However, industrial structure and research and development appeared to be conducive to green economic growth, which justifies the idea that countries should focus on implementing structural reforms for the technological modernisation of infrastructure and industrial complexes to dispose of the shortcomings caused by urbanisation. To compensate for this negative impact, the findings of this research prompt a set of policy implications concerning dissemination of the green knowledge and technologies, green project implementation, reinforcement of incentive instruments and achievement of a synergistic balance of economic and ecological targets underlying the SDGs.

Assessing the effects of the influencing factors on industrial green competitiveness fusing fuzzy C-means, rough set and fuzzy artificial neural network methods

Improving the industrial green competitiveness is of great significance to handle the issues of resource shortage and environmental degradation in the process of ecological civilization construction. The existing literatures on the influencing factors of the industrial green competitiveness mostly examine the linear relationship using econometric models but rarely investigate the nonlinear effect between them. To address this research gap, this study firstly adopts the direction distance function and the global Malmquist-Luenberger productivity index to evaluate the green competitiveness of 33 industrial sub-sectors in China from 2002 to 2017, and employs the fuzzy C-means algorithm to classify these sectors into three categories with high-, medium- and low-levels of green competitiveness, respectively. Furthermore, this study identifies the critical factors influencing the industrial green competitiveness using the rough set theory, and more specifically explores how these critical factors differently impact the green competitiveness of three categories of industrial sub-sectors using the fuzzy artificial neural network. The results indicate that, the green competitiveness of the overall industrial sector in China shows an upward trend during 2002 to 2017, but there exist significant disparities among industrial sub-sectors. Research and development intensity, environmental regulation and enterprise scale are three critical factors influencing industrial green competitiveness. In the sub-industries with high-, medium- and low-levels of green competitiveness, the most significant factor is enterprise scale, research and development intensity, and environmental regulation, respectively.

Green development of the country: Role of macroeconomic stability

The intensification of ecological issues provokes to search for the appropriate mechanism and resources to solve them without declining the economic growth. This requires moving from resources oriented to green economic development. It could be realised through two goals: achieving macroeconomic stability – core driver of economic growth; declining environmental degradation and increasing efficiency of resources using – core requirements for green development. The paper aims to check the hypothesis on macroeconomic stability's impact on the green development of the countries. The object of investigation is European Union countries from 2000 to 2020. The study applied the following methods: the Global Malmquist-Luenberger productivity index – to estimate the green development of the countries; Macroeconomic Stabilisation Pentagon model – to estimate macroeconomic stability; Kernel density estimation and Tobit model – to check the macroeconomic stability impact on the green development of the countries. The empirical findings show that Malta from the ‘Green Group’ and Estonia from the ‘Yellow group’ have the highest value of green development, and Sweden and Greece have the highest value of macroeconomic stability. Besides, the findings allow confirming the research hypothesis. Thus, the growth of external dimensions of macroeconomic stability by 1 point led to the growth of green economic development by 0.085 (among ‘Green group’) and 0.195 (among ‘Yellow group’). It confirms that harmonising macroeconomic stability among all EU members allows for achieving the synergy effect.

How does digital finance affect environmental total factor productivity: A comprehensive analysis based on econometric model

The promotion of environmental total factor productivity (ETFP) is the key to ensure the sustainable development. As an important way of resource allocation, digital finance plays a significant role in regional ETFP. This study employs global Malmquist-Luenberger productivity index, based on super SBM directional distance function, to estimate the China's regional ETFP from the perspective of sustainable development. Furthermore, this paper adopts dual-effect fixed regression model, spatial econometric model and threshold model to verify the impact of digital finance on provincial ETFP. Results show that: (1) ETFP in China presents a trend of improvement, and the driving force is technological progress. The spatial distribution is in accordance with the “East, middle and West” gradient distribution; (2) Digital finance inhibits the improvement of ETFP, which shows nonlinear characteristics. The impact of digital finance on restraining ETFP will gradually weaken with the development of digital finance. In terms of decomposition terms, the coverage breadth and usage depth of digital finance have inhibitory action on the betterment of ETFP; (3) Digital finance can promote the regional ETFP of the surrounding areas, and the potential reason may be the “siphon effect”. Therefore, it is essential to further guide financial resources to enterprises and industries with high environmental benefits. (4) There is also significant heterogeneity in the impact of digital finance on ETFP. This study explores from the two aspects of region and material capital, and finds that the more backward the economy is, the more significant the inhibition effect is.

Carbon emissions trading policy and green transformation of China’s manufacturing industry: Mechanism assessment and policy implications

Accelerating the green transformation of manufacturing industry is the way to the sustainable development of China’s economy and an inevitable requirement for realizing the great vision of carbon peaking and carbon neutrality. This paper employs the global Malmquist-Luenberger productivity index based on the SBM-DEA method to calculate the green total factor productivity covering manufacturing industry of 30 Chinese provinces between 2006 and 2019. A difference-in-difference model is constructed to empirically study the direct impact and mechanism assessment of carbon emission trading policy on the green total factor productivity. The results show that the green total factor productivity of China’s manufacturing industry generally showed a dynamic trend of rising during this period. Critically, the implementation of the carbon emissions trading policy has a significant effect on promoting the green total factor productivity of China’s manufacturing industry. Interestingly, this promoting effect will be enhanced by higher technical levels, a cleaner energy structure, and a greener industrial structure. Additionally, our evidence also shows that the positive impact of carbon emission trading policies on green total factor productivity will be improved by higher carbon emission trading prices and a more active carbon emission trading market, thereby accelerating the green transformation process of manufacturing industry. Therefore, taking carbon emissions trading policy as a long-term strategy and improving its effectiveness is crucial to ensuring the green and sustainable development of China’s manufacturing industry.

Fiscal Decentralization, Export Technology Complexity and Regional Green Total Factor Productivity: Empirical Study based on GML Productivity Index

With the Global-Malmquist-Luenberger (GML) productivity index, we calculate and evaluate the Chinese green total factor productivity and the decomposition, and further take the dynamic GMM method to empirically study the effect of export sophistication, fiscal decentralization and their interaction terms on regional green total factor productivity. The increasing export technology complexity has a significant effect on the regional green total factor productivity growth. Increasing export sophistication degree means the improving status of international vertical specialization division and upgrading of export product structure, which has a positive incentive effect on adoption of regional environmental technology and transformation and upgrading of regional industrial structure. However, this effect will be disturbed by the regional fiscal decentralization. Fiscal decentralization intensifies local government’s competition and distorts local factor market and resources misallocation. It will not only distort the incentive of enterprises to increase less technology and the R&D on the export of products, but also will inhibit the upgrading process of regional industrial structure, which would lead to extensive growth trap of “high consumption and high emission”. To continue to enhance China's position in the international division of labor is necessary. Moreover, a diversified evaluation system is encouraged in the performance evaluation system of local officials to optimize the resources allocation efficiency, and propose a proper guidance and incentive for local enterprises to promote industrial transformation and upgrading. Ultimately a win-win situation between ecological civilization construction and economic sustainable growth is achieved.

Environmental Legislation, Resource Allocation Efficiency and the Green Growth of Industry: Based on Global Malmquist-Luenberger Productivity Index and Difference-in-Difference Method

Facing with severe environmental constraints, will the promulgation of environmental laws and regulations be conducive to promoting the green growth of industry in developing country? This paper tries to answer it by providing an empirical study of China. Based on the SBM Directional Distance Function, we first calculated the green growth index of industry and its decomposition, and then investigated the heterogeneous effects of environmental legislation on the industrial resource allocation efficiency and the green growth of China's industry. The paper reveals some following findings. First, local environmental legislation is conducive to promoting the green growth of China's industry. Meanwhile the mismatch of resource allocation shows negative effects on it. This result remains robust after considering some controlled variables at the enterprising and regional levels or using different methods. Second, local environmental legislation can alleviate the negative effects of resource allocation mismatch on the green growth of China's industry by presenting positive moderating effects. Third, the effect of local environmental legislation on technological progress is more significant than that of technical efficiency, which implies an obvious anti-driving mechanism of local environmental legislation on the technological innovation. Finally, we propose some policy implications on how to achieve the green growth of industry by implementing efficient environmental legislation and optimizing industrial resource allocation efficiency in transitional economy.

Environmental Regulation, Urban-Rural Income Gap and Agricultural Green Total Factor Productivity

Environmental regulation is the basis for achieving green agricultural development, and urban-rural integration is the key to optimizing the allocation of agricultural elements and achieving sustainable agricultural development. This paper aims to investigate the spatial spillover effect of environmental regulation on China’s agricultural green total factor productivity (AGTFP) and examine the mediating effect of the urban-rural income gap. Both the Super-SBM-DEA model and the Global Malmquist–Luenberger productivity index are used to account for the AGTFP of China’s 30 provinces, and the spatial Durbin model and the mediating effect model are used to analyze the impact of environmental regulation. We found that firstly, during the sample period, China’s AGTFP has increased with an average annual growth rate of 3.27%, which is mainly promoted by agricultural green technology progress (AGTC). Secondly, both the direct and spatial effects of environmental regulation on AGTFP show a significant “U”-shaped feature and have regional heterogeneity based on differences in economic development levels and factor endowments. Thirdly, there is an “inverted U”-shaped relationship between environmental regulation and the urban-rural income gap, and the urban-rural income gap negatively affects AGTFP. Based on the empirical results, we propose that the Chinese government should pay attention to green technology innovation, break the market segmentation, promote urban-rural integration, and then promote the AGTFP.

Green total factor productivity measurement of industrial enterprises in Zhejiang Province, China: A DEA model with undesirable output approach

The green production efficiency of industrial enterprises in Zhejiang Province is not only related to the level of green economy in Zhejiang Province, but also provides an example for the green development of national industrial enterprises. This paper used the panel data of industrial enterprises by sector and city in Zhejiang Province from 2012 to 2017. Firstly, the entropy weight method is employed to calculation the Comprehensive Environment Pollution Index (CEPI) of various sectors and cities including sulfur dioxide; nitrogen oxide; smoke and dust; solid waste and hazardous solid waste. The method of output-oriented Data Envelopment Analysis (DEA) model with undesirable output was employed to measure Global Malmquist-Luenberger Productivity Index (GMLPI). The conclusion shows that: (1) Zhejiang industrial enterprises have made slight progress (0.738% per year on average) in comprehensive efficiency between 2012 and 2017. (2) In sectoral efficiency analysis, the fluctuation of TC and SEC is the main factor affecting the comprehensive efficiency of the sector. (3) In city efficiency analysis, Hangzhou; Ningbo; Wenzhou; Jiaxing and Shaoxing have made progress in comprehensive efficiency in the research period, while Jinhua; Quzhou and Zhoushan have made decline. This paper provides support for the green development of Zhejiang Province.

A Blessing or a Curse? Exploring the Impact of Environmental Regulation on China's Regional Green Development from the Perspective of Governance Transformation.

China’s rapid economic growth has caused serious problems, such as environmental pollution and resource exhaustion. Only by improving the green total factor productivity (GTFP) can China’s economic development get out of the dual dilemmas of environmental degradation and resources exhaustion. Although environmental regulation helps to improve China’s productivity, its impact on GTFP is still controversial and deserves careful investigation. In this context, this study adopts the global Malmquist-Luenberger productivity index to measure the GTFP change of China’s 30 provinces over the period of 2003 to 2017 and then it uses the fixed-effect dynamic panel model to investigate the impact of environmental regulation on GTFP from the perspective of governance transformation. The results show that: (1) there is a nonlinear U-shaped relationship between environmental regulation and GTFP, indicating that the Porter hypothesis is verified in China. More notably, the values of environmental regulation are still located on the left side of the U-shaped curve at present, which means that the promotional effect of environmental regulation on GTFP has not been realized fully. (2) The U-shaped relationship shows significant regional heterogeneity. The western region demonstrates the highest level of significance, followed by the eastern region. However, the U-shaped relationship is insignificant in the central region. (3) Governance transformation can not only significantly improve GTFP but it can also accelerate the realization of the Porter hypothesis by inspiring the innovative enthusiasm of enterprises, which means that governance transformation can contribute to the achievement of the improved effects of environmental regulation on GTFP. (4) R&D investment can significantly improve GTFP, where the impacts of trade openness and factor endowment were significantly negative and the influence of foreign direct investment was not significant. These conclusions provide a good reference point for optimizing the relationship between the government and the market, as well as promoting regional green and high-quality development in China.

Airlines’ eco-productivity changes and the European Union Emissions Trading System

• The link between the airlines’ eco-productivity changes and the EU ETS is explored. • The airlines continuously improved eco-productivity over time, but at a slow pace. • Efficiency gain, technology progress respectively led the eco-productivity growth. • Implications are provided for promoting eco-productivity in the airline industry. • Non-convexity is used to form global Malmquist Luenberger productivity index. With the rapid traffic growth, carbon dioxide emissions from aviation have become a growing cause of climate change. Currently, the European Union Emissions Trading System (EU ETS) remains the largest cap-and-trade system tackling aviation emissions. This study examines how the eco-productivity of airlines in the European Economic Area – which are directly affected by the EU ETS – changed during 2012–2019. A non-convex global Malmquist-Luenberger productivity index was developed to provide better estimates of the changes. The study presents three major findings as follows: First, since the inclusion of aviation in the EU ETS, the airlines displayed continuous but slow growth in their eco-productivity. Second, efficiency improvement and technological innovation respectively drove the airlines’ eco-productivity growth. Third, the carbon price on the EU ETS was not a strong indicator of the airlines’ eco-productivity changes.

Technology or Institutions: Which Is the Source of Green Economic Growth in Chinese Cities?

To relax the increasingly tight resource and environmental constraints on development, China needs to follow a pattern of growth that comprehensively encompasses economic growth, environmental protection, and resource conservation, namely, green economic growth. The key to achieving green economic growth is to improve green total factor productivity, of which technological innovation and institutional innovation are the primary driving forces. Based on the panel data of 266 cities in China from 2004 to 2018, this paper first uses the Directional Distance Function and Global Malmquist–Luenberger productivity index to measure the urban green total factor productivity to represent urban green economic growth; then, the impact of technological innovation and institutional innovation on urban green economic growth is studied by using the panel Granger causality test and SYS-GMM dynamic panel model. The results are described as follows: China’s urban green total factor productivity shows an increasing trend from 2004 to 2018, and the average growth rate of green total factor productivity is 3.27%, which is far lower than the average GDP growth rate of 9.14%; both technological innovation and institutional innovation can significantly promote the growth of the urban green economy, but institutional innovation has a greater role in promoting the growth of the urban green economy than technological innovation. In addition, the relationship between institutional innovation and urban green economic growth is more stable.

New patterns in China's regional green development: An interval Malmquist–Luenberger productivity analysis

A better understanding of regional differences in green development (GD) is crucial to achieving the sustainability goals in China's high-quality development stage. Data envelopment analysis–based productivity indexes, which link multiple inputs and multiple outputs, have been widely used to evaluate GD. However, most of these models do not take into account the imprecision of regional economic data due to over- or under-reporting by local governments. Here, to alleviate the GD calculation errors due to point estimation as far as possible, we propose a novel global Malmquist–Luenberger productivity index with the interval slacks-based measure to evaluate the provincial green total factor productivity (GTFP) in China from 2000 to 2018. The results showed that the overall GTFP in China during the study period exhibits an increasingly upward trend, accompanied by a declining and converging growth rate in recent years. Moreover, we found an emerging shift in the patterns of inter-regional GTFP from “East–Center–West” to “South–North”, as the differences in the GTFP between the eastern, central and western regions shrink while the gap between the southern and the northern regions expands. A further impact mechanism analysis based on dynamic spatial Durbin panel models revealed that the green development mode in the central, western and northern regions is more exogenously government-dependent, whereas that in the eastern and southern regions is more endogenously market-driven. These findings provide a new reference for optimizing the relationship between the market and government and coordinating the regional green development of China.

Analysis of resource allocation and PM2.5 pollution control efficiency: Evidence from 112 Chinese cities

The State Council of China initiated an air pollution prevention and control key (APPCK) city program to drive the national economic development and air pollution control since 2003. However, little known about whether the initiation is efficient. This paper examined the PM2.5 pollution control efficiency (PPCE) of 112 Chinese APPCK cities in 2003–2017 using Super-slack-based measure (Super-SBM) model with undesirable outputs. Results show that: (1) PPCEs of coastal cities (e.g., Shanghai, Guangzhou, and Suzhou) are much higher than those of less-developed northern cities (e.g., Jiaozuo, Anyang and Kaifeng); (2) the overall PPCE of 112 APPCK cities is relatively low and improvable; (3) the annual average growth rate of global Malmquist-Luenberger productivity index is 6.3%; (4) the technological progress is a significant contributor to improve the PPCE of these cities with 3.1% global technological change. These results provide reference to not only the policy-makers of China for synergies and tradeoffs between economic development and PM2.5 pollution control but also the studies on PM2.5 pollution control efficiency in the international context.