Global Malmquist-Luenberger Index Research Articles

Spatial and temporal evolution characteristics of urban green innovation efficiency in Northeast China

In the strategic context of promoting the comprehensive revitalization of Northeast China, green innovation, as the integration of the two development concepts of innovation-driven and green development, has become an essential means to promote sustainable and high-quality development in Northeast China. By constructing the Super-SBM model with undesired output and the Global Malmquist-Luenberger index model, the green innovation efficiency and green innovation total factor productivity of 34 prefecture-level cities in Northeast China from 2011 to 2020 are measured. Then the natural break point classification method, standard deviation ellipse and Dagum Gini coefficient decomposition method are used to explore their spatial and temporal evolution characteristics. Based on the measured results of green innovation efficiency and green innovation total factor productivity in Northeast China, all the cities are classified into four types: high-high, high-low, low-high and low-low. The study results show that the green innovation efficiency (GIE) of cities in the northeast region shows an excellent upward trend, and the distribution pattern of “strong in the North and weak in the South” is more prominent. The green innovation total factor productivity shows a fluctuating decline, and technical efficiency and technological progress inhibit the improvement of green innovation efficiency. The centre of gravity of efficiency has generally migrated towards the southwest, green innovation efficiency among cities has gradually tended to develop in a balanced manner, and inter-provincial differences are the primary source of spatial differences in green innovation efficiency. The study concludes that the northeast region should continuously improve its green innovation resource allocation capacity, accelerate the green transformation and upgrading of industrial structure, clarify green innovation subjects, optimize the green innovation environment and formulate differentiated development strategies to promote the synergistic development of green innovation among cities.

The impact of internet development on green total factor productivity in China’s prefectural cities

ABSTRACT This paper uses the global Malmquist-Luenberger index to measure the effect of Internet development on the green total factor productivity (GTFP) of China’s 283 prefectural cities. We find that by promoting high-quality development, the effect of Internet is significantly positive. Firstly, we explore the two mechanisms through which the use of the Internet promotes GTFP: improvements in the quantity and quality of urban innovation and the advancement and rationalization of urban industrial structures. Secondly, we compare the pre- and post-impacts of the Internet + initiative from which it draws critical policy implications. Finally, threshold regression shows that when urban Internet penetration and employee wages rise to their respective threshold levels, the promotion effect of the Internet on GTFP can be further augmented. Meanwhile, from the perspective of Intensive Growth Theory, the Internet’s contribution to green labor productivity is more pronounced.

Optimum combination of heterogeneous environmental policy instruments and market for green transformation: Empirical evidence from China's metal sector

Based on the new structural economics view that the combination of effective governments and efficient markets is the fundamental path to high-quality development, this study investigates how heterogeneous environmental policy instruments combine with marketization to improve the total factor energy-environmental efficiency (TFEEE) in China's metal sector. Utilizing the provincial panel data from 2006 to 2019, a super-efficiency slacks-based measure data envelopment analysis (SBM-DEA) integrated with the global Malmquist-Luenberger (GML) index is employed to estimate the energy-environmental efficiency and its dynamic changes. The evaluation results imply a significant increasing trend in the energy-environmental efficiency, but the overall level is rather low with disparities between sub-sectors and different regions. Using a dynamic panel threshold model, the “strong” version of the Porter Hypothesis is validated that command-and-control environmental policy (CEP), market-incentive environmental policy (MEP), and voluntary environmental policy (VEP) have an optimum stringency range to induce TFEEE growth, while the impact modes are drastically diverse. Further study verifies that higher marketization is conducive to triggering the facilitation effect of heterogeneous environmental policy instruments on the TFEEE but with completely different threshold values of marketization, which decrease sequentially corresponding to VEP, CEP, and MEP.

Research on Beijing Manufacturing Green-Oriented Transition Path under “Double Carbon” Goal-Based on the GML-SD Model

Accelerating the “double carbon” transformation of the manufacturing industry is the key to achieving the strategic goal of “double carbon” in China, among which the low-carbon development of the Beijing manufacturing industry is the top priority. To achieve high-quality development of the manufacturing industry in Beijing, the main task is to reduce carbon emissions and improve efficiency. Therefore, on the basis of the Global Malmquist–Luenberger (GML) index and the system dynamics (SD) method, this study analyzes the green total-factor energy efficiency trends of 25 manufacturing sub-sectors in Beijing from 2006 to 2020 and incorporates the GML index as a key variable into the construction of the SD model. It then explores the path optimization of Beijing’s manufacturing low-carbon development in the 14th Five-Year Plan period via scenario simulation and offers policy recommendations for the green-oriented transition of Beijing’s manufacturing industry. The study finds that Beijing’s manufacturing industry needs to prioritize energy structure optimization and efficient energy utilization and give full play to the city’s advantages in technological innovation and investment while supporting high-end scientific research and innovation projects to confirm the capital city’s strategic position.

Environmental-economic efficiency for carbon neutrality: the role of eco-innovation, taxation, and globalization in OECD countries

ABSTRACT The aim of this paper is to examine the relationship between three determinants – environmental patents, environmental taxation and trade globalization – and the environmental-economic efficiency of 29 OECD countries between 2005 and 2020. Using the Global Malmquist-Luenberger index, this research computes the environmental productivity growth and its main drivers – the catch-up and the frontier shift terms. Besides, dynamic panel linear models are applied to investigate how the three institutional variables affect the dynamics of the computed efficiency indices. Results are as follows: firstly, eco-innovation is the most relevant factor in boosting the environmental productivity growth, pushing forward the technological frontier, and spurring the catch-up term. Secondly, environmental taxation is an ineffective policy instrument in promoting the sustainable growth and technological frontier advancements, having positive impacts only on the catch-up term. Thirdly, trade globalization reveals to hinder the sustainable growth and its two main drivers.

Exploring the Direct and Spillover Effects of Aging on Green Total Factor Productivity in China: A Spatial Econometric Approach

China is a rapidly aging nation. Therefore, it is a matter of urgency to address the challenges of aging in China and to coordinate the relationships between population aging, environmental issues, and socio-economic development. However, few empirical studies have thus far analyzed the impact of aging on green total factor productivity (GTFP) in China. Hence, this study employs a global Malmquist–Luenberger index method (GMLI) to calculate the GTFP scores of 30 Chinese provinces from 2002 to 2018. We apply spatiotemporal analysis methods to identify the variations of population aging and GTFP scores and then build a spatial econometric model to examine the impact of population aging on GTFP. Our study findings are as follows. (1) Whereas at the beginning of the 21st century, provinces with deep aging were mostly situated in the east, the population aging issue in China is now spreading across the entire country. (2) From a dynamic perspective, the overall GTFP growth rate in China during the sample period depicts a U-shaped structure with time. (3) Results of the spatial Durbin model show that the impact of population aging in a given region on GTFP is negative, but the spatial spillover effect of aging in neighboring regions on GTFP in a given region is positive, resulting in the loss of younger local labor forces in some provinces due to low birth rates and migration to neighboring regions. Finally, to cope with a growing aging population and to possibly eliminate the negative impacts of population aging on high-quality sustainable development, the government should promote the establishment of the old-age security system; increased investment in R & D and wide use of advanced technology should also be urgently encouraged.

Examining the Internal-Structural Effects of Internet Development on China’s Urban Green Total Factor Productivity

ABSTRACT In the era of widespread internet access, green development has also entered an era of big data. Using panel data of 282 prefecture-level cities in China from 2003 to 2019, this study adopts slacks-based measure (SBM) directional distance function and Global Malmquist-Luenberger (GML) index to calculate the green total factor productivity (GTFP) and its decomposition (i.e. technological progress, scale efficiency, and resource allocation efficiency). On this basis, econometric models are used to study the internal-structural effects of internet development on China’s urban GTFP. It is found that: (1) Internet development plays a positive role in promoting urban GTFP; (2) specifically, internet development is proven to achieve this effect simultaneously by inducing technological innovations, optimizing economic scale, and improving resource allocation efficiency. Among these, inducing technological innovations is the most important path; (3) there are distinct regional heterogeneous effects of internet development on China’s urban GTFP. Based on the above results, corresponding policy suggestions are provided.

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.

The static and dynamic carbon emission efficiency of transport industry in China

Transport industry is one of the major contributors to energy-related carbon emissions in China, thus becoming a topical area of concern where efforts to improve carbon emission efficiency need to be prioritized. By establishing a Static-Dynamic Efficiency (SDE) framework and using panel data from 30 provinces in China from 2010 to 2019, we develop a super slack-based measure model to assess the static efficiencies and potential for improvement of the TICEE at the provincial level, adopt the global Malmquist-Luenberger index to examine the dynamic changes in TICEE and the underlying driving factors, and propose improvement strategies by integrating the static and dynamic perspectives. We observe: (1) severe carbon emission inefficiency in transport industry in China, particularly in western, central and north-eastern regions; (2) a slow downward trend in static efficiency due to the slow progressing technological innovation; and (3) high potential for saving energy and reducing emissions in the provinces that fall into the “inefficient-deterioration” category. Our research findings extend the literature by bringing together the static and dynamic aspects into the SDE framework, as well as assist policy makers in better understanding the way to improve TICEE.

The total factor carbon emission productivity in China’s industrial Sectors: An analysis based on the global Malmquist-Luenberger index

In this paper, we construct a new Global Malmquist-Luenberger Index to measure the total factor carbon emission productivity (TFCEP). Specifically, by invoking the weak disposability assumptions on both energy inputs and carbon dioxide emissions, the index constructed in this study fully considers the relationship between energy inputs and carbon dioxide emissions. This method avoids the distortion of estimates present in the existing techniques due to their neglect of the inherent relationship between energy inputs and carbon dioxide emissions. Employing this index, the TFCEP of 41 industrial sectors in China from 2013 to 2016 was measured and analyzed. Our main results are as follows. First, for most industrial sectors, the TFCEP increased yearly, but the growth rate was low. Second, the growth and decline of TFCEP were mainly driven by technological progress or deterioration. Third, the change of technical efficiency in the industrial sectors was not synchronized with the technological change. However, higher efficiency changes were often accompanied by a lower best practice gap change (BPC) and vice versa.

Unearthing marine ecological efficiency and technology gap of China’s coastal regions: A global meta-frontier super SBM approach

With the promotion of the maritime power strategy and progressively increasing and severe environmental problems, marine ecological efficiency is fast becoming an essential object of research in achieving sustainable development. By applying the meta-frontier super SBM model and the global Malmquist-Luenberger index, this paper aims to explore the marine ecological efficiency of coastal regions in China and the technology gaps between different regions during 2006–2017. On this basis, the changes in marine ecological efficiency were decomposed to investigate the driving factors. The results indicate that the marine ecological efficiency of China’s coastal regions was still ineffective, and there was a significant gap between the group production technology and the potential optimal production technology. Also, there was a significant regional technological heterogeneity. The Yangtze River Delta region had optimal production technology level, while the Beibu Gulf region distinctly had a sizeable technological gap with the other three regions. Besides, the primary factor affecting marine ecological efficiency was technological progress. Finally, the results of this paper passed the robustness check. Based on these conclusions, some specific policy suggestions are provided for China’s coastal regions.

Dynamic relationship between resource endowment, financial agglomeration, innovation-driven, and green total factor productivity

As conflicts between emissions reductions and economic growth intensify, an increasing number of countries and regions are focusing on green total factor productivity (GTFP). Financial agglomeration (QWS), resource endowment (SE), and innovation-driven (ID) are the main factors that cause regional differences in GTFP. However, few scholars have comprehensively considered the impact of the interaction between SE, ID, and QWS on GTFP. This article uses the Global Malmquist-Luenberger (GML) index to calculate the GTFP of 30 Chinese provinces from 2003 to 2020 and constructs a dynamic panel model to present the first comprehensive study of the interactions between SE, ID, and QWS and their relationship with GTFP. The conclusions are as follows. (1) SE is positively correlated with GTFP, which is different from the “resource curse” theory proposed by existing research. (2) There is a crowding-out effect between SE and ID, and their interaction will restrain the growth of GTFP. (3) QWS promotes ID, and the interaction between the two promotes the growth of GTFP. (4) There is a restraining effect between QWS and SE, and their interaction will hinder the growth of GTFP. (5) The key policy directions to improve China's GTFP are to undertake strategic planning from a comprehensive perspective, including encouraging innovation, guiding financial development reasonably, and avoiding excessive consumption of resources.

Revisiting the Green Growth Effect of Foreign Direct Investment from the Perspective of Environmental Regulation: Evidence from China.

The inflow of foreign direct investment (FDI) has both advanced China's economic development process and influenced the ecological quality of China's regions. Under the deepening of economic globalization and the continuous deterioration in environmental quality, the correlation mechanism between foreign direct investment, environmental regulation, and economic growth is becoming increasingly complex. Therefore, based on the slacks-based measure (SBM) model and the Global Malmquist-Luenberger (GML) index, this study measured the level of green economic growth using data from 30 provinces and cities from 2004-2019 and constructed a panel fixed-effect regression model to study the effect of foreign direct investment on green economic growth in China. The study found that foreign direct investment significantly promoted green economic growth in China, foreign direct investment promoted green economic growth through independent innovation and inhibited green economic growth through imitation innovation, and environmental regulation moderated the impact of foreign direct investment on green economic growth. This paper incorporated foreign direct investment, heterogeneous technological innovation, green economic growth, and environmental regulation into the research framework, and thereby further enriched and improved the research on the theoretical mechanism of green economic growth. The research conclusion clarified the influence mechanism of foreign capital on the quality of China's economic development, which was conducive to the formulation of more reasonable policies for attracting investments and to the promotion of the formation of a positive interaction mechanism between environmental regulation and foreign direct investment, which is of great practical significance for China's economy to achieve sustainable development.

The impact of industrial agglomeration on urban green land use efficiency in the Yangtze River Economic Belt

At present, the insufficient supply of land resources has seriously hindered the sustainable development of regional economy. Improving the urban green land use efficiency (UGLUE) has become a key issue on the road to sustainable development. As an important feature of economic development, industrial agglomeration has an impact on the UGLUE that cannot be ignored. This paper uses the Global Malmquist–Luenberger Index (GMLI) to measure UGLUE of 107 cities in the Yangtze River Economic Belt (YREB) from 2007 to 2016, and uses a dynamic panel model (DPM) to empirically analyze the effects of industrial specialization agglomeration and diversification agglomeration on UGLUE. On this basis, the heterogeneous impact of industrial agglomeration in different regions on UGLUE is further discussed. The results illustrate that: (1) The UGLUE shows a general downward trend. (2) Different modes of industrial agglomeration have different impacts on UGLUE. The impact of industrial specialization agglomeration on UGLUE was inverted U-shaped. Industrial diversification agglomeration has a positive effect on UGLUE. (3) The impact of industrial agglomeration in different regions on UGLUE is heterogeneous. The relationship between the industrial agglomeration and UGLUE in the YREB revealed in this paper will provide a reference for promoting UGLUE.

Spatio-temporal variations, spatial spillover, and driving factors of carbon emission efficiency in RCEP members under the background of carbon neutrality.

Improving carbon emission efficiency (CEE) has emerged as a critical way for Regional Comprehensive Economic Partnership (RCEP) members to promote carbon reduction in the context of climate change mitigation and carbon neutrality. The super-efficiency slacks-based measure (SBM) model, which considers non-desired outputs, is adopted to comprehensively assess the current state and trend of CEE in 15 RCEP countries from a spatio-temporal dynamic perspective, and the global Malmquist-Luenberger (GML) index is coupled to quantify the spatial and temporal differences and dynamic changes. Following that, taking into account the spatial characteristics of CEE, the extended STIRPAT model and the spatial Durbin model are combined to further investigate the primary influencing factors of CEE. It is found that (1) the CEE of RCEP members is generally poor and unevenly distributed in temporal and spatial dimensions, with significant room for improvement and an overall positive spatial autocorrelation; (2) CEE varies considerably among RCEP members, with developed countries far outstripping developing countries in terms of both the current status and trend of CEE; (3) on a dynamic level, the GML index exhibits W-shaped fluctuations, with technological progress acting as the dominant force; and (4) in terms of spillover effects, affluence and economic agglomeration inhibit CEE enhancement, whereas technology level and investment capacity facilitate it. The findings will be useful in developing carbon-neutral plans for various countries as well as coordinated sustainable development for RCEP regions.

Spatial-Temporal Evolution and Convergence Characteristics of Agricultural Eco-Efficiency in China from a Low-Carbon Perspective

While agriculture plays an essential role in food security, it is also one of the largest emitters of carbon emissions. China’s carbon neutrality and carbon peaking goals mean that China’s agriculture is also going through a low-carbon transition. To analyze the spatiotemporal heterogeneity and convergence of China’s agricultural eco-efficiency (AEE), this study used a combined super-efficient slacks-based measure (SBM), global Malmquist–Luenberger index (GML), kernel density estimation, Moran index, and convergence model on panel data from 2005 to 2020 and from 31 Chinese provinces. An innovative eco-efficiency index evaluation system was constructed from a low-carbon perspective that integrated agricultural carbon sinks and carbon emissions. The results revealed that the average AEE movement was U-shaped, but there were significant differences across regions and periods. The AEE demonstrated a gradual decreasing pattern of “northeast > eastern > western > central”, a declining trend during 2005–2010 and increasing trends during 2011–2020. The main reason for AEE growth was technological progress; however, technical efficiency only played a role in several provinces. The AEE in Chinese provinces was also found to have spatial autocorrelation characteristics dominated by high-high, low-low, and high-low clustering. A “catching-up effect” existed in the lagging AEE regions. Therefore, it is recommended to promote the integration of regional strategies and low-carbon development, build a low-carbon technology support system, and construct a national agricultural carbon trading center to facilitate agricultural low-carbon transformation.

The Tourism Eco-Efficiency Measurement and Its Influencing Factors in the Yellow River Basin

Tourism eco-efficiency is an essential indicator to measure the level of green and sustainable development of tourism. Based on the data of nine provinces in the Yellow River Basin, from 2011 to 2020, this article estimates the changes in tourism eco-efficiency in the Yellow River Basin and explores its internal drivers by establishing multiple input-output index systems using the Global Malmquist-Luenberger (GML) index method. Finally, a panel stochastic Tobit model was applied to identify the key external drivers of its eco-efficiency improvement. The analysis shows that with the continuous promotion of the Yellow River Basin’s high-quality development strategy and ecological civilization construction, the tourism eco-efficiency of the Yellow River Basin provinces has been improved in the past decade. Due to the obvious ecological advantages in the upper reaches of the Yellow River Basin and the high level of tourism promotion and economic development in the lower reaches, tourism ecological efficiency in the upstream and downstream areas is commonly higher than in the midstream areas. The improvement of efficiency is the internal core driver of regional tourism eco-efficiency, but the essence of eco-efficiency improvement lies in technological progress. In the analysis of the impact of external drivers on tourism eco-efficiency, tourism economy scale, tourism industry structure, technological innovation, and economic development are the crucial external factors to eco-efficiency enhancement. This work can serve as a guide for the high-level growth of regional tourism industry.

Study on the Change in the Total Factor Carbon Emission Efficiency of China’s Transportation Industry and Its Influencing Factors

The transportation industry is a high carbon emission industry, and China has also put forward strict requirements for the transportation industry to achieve carbon emission reduction. By measuring the total factor carbon emission efficiency of the transportation industry, we can understand the change trend and the influencing factors of the total factor carbon emissions. To fully consider the problem of multiple inputs and outputs in the transportation industry and obtain a more accurate efficiency evaluation value, this paper adopted the slack-based model-data envelopment analysis method and global Malmquist—Luenberger index to study the change in the total factor carbon emission performance of the transportation industry. The combination of static analysis and dynamic analysis was used to calculate the TFP of the transportation industry and increase the content of output indicators. The results indicate that the average TFP and GML index values exhibited significant heterogeneity nationwide. The values in Anhui and Hebei Provinces were greater than 1, and the average GML index values in Shanxi, Guangxi, and Yunnan were greater than 1. The eastern region performed well in terms of technical efficiency and scale efficiency. The technical efficiency in the central, western, and northeastern regions was optimal. In terms of influencing factors, the influencing factors causing the different carbon emission efficiencies in the four regions varied. Finally, corresponding policy suggestions were proposed.

Does the Belt and Road Initiative increase the green technology spillover of China’s OFDI? An empirical analysis based on the DID method

The pollution caused by foreign investment has become a serious concern of the host government and academia. Many studies have discussed much about the environmental impact of China’s OFDI in countries along the Belt and Road Initiative (BRI) region, but ignored the impact of the BRI itself on China’s OFDI. This study uses the Global Malmquist–Luenberger index to measure the green technology spillover of China’s OFDI from 2005 to 2018 and studies the impact of BRI on this spillover effect with the DID (difference-in-difference) method. The results show that (1) the BRI has significantly increased the green technology spillover of China’s OFDI in countries along the routes. The heterogeneity study shows that such an effect is significant in middle- or low-income countries with high institutional quality or poor environmental performance, but not obvious in other countries. (2) The BRI promotes green technology spillover through the mechanism of increasing R&D investment, improving the environmental system, and accelerating the flow of production factors. This study provides a useful reference for developing a greener OFDI and promoting the sustainable development of regional cooperation.

Will bidirectional FDI impact industrial electricity efficiency in China?

Both "dual cycle" and "carbon neutral" policies have been implemented as national strategies in China. But will "dual cycle" policy help carbon neutral policy and how do "dual cycle" policy affect carbon neutral policy? This paper investigates whether unbalanced bidirectional foreign direct investment (FDI) hinders electricity efficiency. To do so, it uses the super slack-based version of the global Malmquist-Luenberger index to measure electricity efficiency in 30 provinces from 2001 to 2020. This paper uses panel threshold regression model, finds out that bidirectional FDI below 1.7174 will positively impact electricity efficiency, but the positive effects disappear when bidirectional FDI exceeds 1.7174. Thus, balanced bidirectional FDI in province is required to enhance electricity efficiency.