Performance of power generation: A dynamic productivity and efficiency analysis.

This study evaluates the performance dynamics of Oman's principal part of electricity generation. Emphasis is placed on capturing the influence of the COVID-19 pandemic on the industry's performance indicators. We utilised the Malmquist Index method to analyse the changes in overall performance indicators over time. This approach allows us to distinguish between efficiency and technology changes. In addition, we employed the analysis of variance approach to test hypotheses related to COVID-19. Data is collected from twelve electricity producers across Oman's power sector. These consist of companies listed on the Stock Exchange Market in Oman, accounting for about 60 % of the total electricity production in the Sultanate. The predominant findings indicate that COVID-19 detrimentally impacted the sector's aggregate performance in 2020 but had a swift recovery in 2021. The analysis of the sample firm's productivity indices verifies that the decline in productivity in 2020 due to the Pandemic is attributable to a decrease in average efficiency indices and a negative shift in the projected frontier. These are probable consequences of the recessionary effects caused by the Pandemic. Despite a considerable decrease in average efficiency scores, a positive change in the frontier has facilitated a rapid recovery in 2021. This recovery can be attributed to the implementation of advanced technical upgrades in particular enterprises, which began as early as 2018/2019, well before the onset of the Pandemic.

Environmental regulation, innovation choices, and agricultural green total factor productivity under a multi-regulatory perspective.

As environmental challenges escalate, green development is crucial for sustainability. This study analyzes China's county-level agricultural green total factor productivity using SBM and ML index, introducing a comprehensive index to quantify the impact of different types of environmental regulations on productivity. The findings reveal the following: baseline analysis reveals that comprehensive environmental regulation notably boosts agricultural green total factor productivity (AGTFP), with regulatory intensity positively linked to productivity growth. Other factors like policy intervention, industrial structure, savings levels, and per capita GDP also favorably impact productivity. All three types of regulations, command, incentive, and voluntary type, substantially enhance AGTFP. The mediating effect test results show that all three types of regulations directly and positively impact AGTFP. Indirect effects vary: command-type regulation's mediating effect through independent R&D is significant, accounting for 39% of the impact. For incentive type, both industry structure upgrading (23.79%) and independent R&D (3.1%) mediate the effect. For voluntary type, technological advancement via independent R&D mediates about 13.0% of the impact. Heterogeneity analysis reveals distinct impacts of different environmental regulations on AGTFP across regions. Command-type regulation is most effective in the west, while in the central region, both command- and incentive-type regulations have similar promotional effects. In the east, incentive- and voluntary-type regulations show stronger impacts. Robustness tests, including endogeneity testing, dependent variable substitution, sample winsorizing, and model substitution, consistently confirm the baseline finding that environmental regulation significantly boosts AGTFP.

Environmental, social and governance performance: Can and how it improve internationalization of Chinese A-share listed enterprises.

As an important enterprises' practice in implementing the UN 2030 sustainable development, environmental, social, and governance (ESG) performance has drawn escalating attention from government, business and academia. This focus substantially impacts internationalization of enterprises. This paper tries to provide quantitative evidence of the impact of ESG performance of Chinese A-share listed companies on their international operation from 2009 to 2021. The results show that: (i) the ESG performance of listed enterprises exercise a significant positive impact on the internationalization operation. (ii) The effect of ESG performance on enterprises internationality is driven by increasing total factor productivity, enterprise reputation, and green innovation, as well as by mitigating financing constraint. (iii) Good ESG performance significantly boosts enterprise internationalization for non-heavy polluting, large-scale enterprises. This effect is also pronounced for enterprises with local government reports featuring a high frequency of environmental terms or those in high-tech industries.

Does government environmental attention drive green total factor productivity? Evidence from China.

Based on city-level panel data spanning 2008 to 2021, this study investigates the impact of government environmental attention (GEA) on green total factor productivity (GTFP). The findings suggest that increased GEA substantially enhances the growth of GTFP. After conducting robustness and endogeneity tests, the study's results consistently show reliability and robustness. Further analysis elucidates several mechanisms through which GEA influences GTFP, including fostering green technology innovation, optimizing resource allocation, and promoting upgrades in industrial structure. Heterogeneity analyses reveal that the impact of GEA on GTFP is notably pronounced in eastern cities, as well as in cities characterized by low resource dependency, mature industrial development, and high market competition. Conversely, the influence of GEA on GTFP is less discernible in cities prioritizing economic development goals, possibly due to differing policy orientations and resource allocation strategies. This study offers a novel perspective on understanding how GEA shape green development and provides empirical support for policy formulation.

Information disclosure, multifaceted collaborative governance, and carbon total factor productivity---an evaluation of the effects of the 'environmental information disclosure pilot' policy based on double machine learning.

As an environmental institutional arrangement related to the information factor of the diversified participation of the government, enterprises, the media and the public, the environmental information disclosure pilot policy, can and how to affect the carbon emission efficiency through multiple collaborative governance? This study uses the Environmental Information Disclosure Pilot Policy implemented in China in 2007 as a quasi-natural experiment. It examines 284 prefecture-level cities from 2004 to 2021 and A-share listed companies from 2004 to 2021, constructing an evolutionary game dynamic model involving government, public, enterprises, and media. Through mathematical derivation and assignment analysis, it explores how environmental information impacts carbon emission efficiency under multifaceted collaborative governance, assessing the strategic choices and evolutionary paths of stakeholders before and after policy implementation, using methods like double machine learning for empirical testing. The study highlights several key findings: First, the implementation of the Environmental Information Disclosure Pilot Policy significantly enhanced carbon total factor productivity in pilot cities, as revealed through Double Machine Learning (DML) policy effect evaluation. Second, adjustments for potential estimation biases using Doubly Debiased LASSO (DDL) regression indicated that environmental information disclosure impacts carbon productivity via a governance mechanism involving government, public, media, and enterprises. Third, a causal pathway analysis suggested a sequential logic in governance effectiveness, starting from governmental environmental focus to corporate environmental responsibility. Lastly, integrating DML with a moderation effect model revealed a regulatory role for environmental legislation construction, offering new insights for achieving dual carbon goals and enriching empirical evidence on information's impact on carbon emission efficiency.

The impact of urbanisation on green total factor productivity: Exploring threshold and mediating effects of human capital.

Green development is main direction of high-quality economic development in China. Urbanisation and human capital (HC) are important factors affecting green development. This study examines effects of urbanisation and HC on green total factor productivity (GTFP) using least squares dummy variable model, based on provincial data in China from 2001 to 2019. This study then explored impact of urbanisation on GTFP through HC (educated HC, healthy HC, and HC structure), adopting mediating effect and threshold effect model. The results showed that urbanisation and three types of HC promote GTFP in China and coastal region. In inland region, urbanisation has insignificant impact on GTFP, while educated HC and HC structure improve it. The mediating analysis revealed that educated and healthy HC in China and coastal region enhance promotion effect of urbanisation on GTFP, whereas HC structure hinders it. In inland region, only healthy HC stimulates promotion effect of urbanisation on GTFP. Considering threshold effect of educated and healthy HC, promotion effect of urbanisation on GTFP is weaker than threshold value; but effect is stronger above threshold value. The promotion effect of urbanisation on GTFP is stronger when value of HC structure is below the threshold, while effect is weakened as value exceeds threshold value. Policy implications are documented to promote urbanisation in a differentiated manner, increase investment in HC, and strengthen coordination between urbanisation and HC.

Which productivity can promote clean energy transition -total factor productivity or green total factor productivity?

Developing clean energy is a key pathway and an inevitable choice for achieving the goals of carbon peak and carbon neutrality. From a global perspective, technology is increasingly affecting the trajectory of energy transition, driving clean energy into a stage of rapid development. Therefore, this paper focuses on exploring the dynamic evolutionary characteristics of clean energy transitions driven by different productivity. Using panel data from 171 economies from 1990 to 2019, this paper systematically examines the impact of Total Factor Productivity (TFP) and Green Total Factor Productivity (GTFP) on clean energy transitions. The empirical results indicate that both TFP and GTFP positively impact clean energy transition. Specifically, clean energy consumption increases by 3.35% and 6.03%with a one standard deviation change in TFP and GTFP respectively. Upon decomposing TFP and GTFP, it was found that Green Efficiency Change (GECH) and Green Technical Change (GHCH), especially GECH, are the main factors driving the clean energy transition. Heterogeneity analysis shows that, in developed economies, GTFP has a larger positive impact on clean energy transition than TFP. Furthermore, GTFP demonstrates a significant positive impact on the clean energy transition both before and after the 2008 financial crisis, whereas TFP's positive impact is only evident before the crisis. Our findings emphasize the social benefits of further investments in GTFP.

Does the digital economy improve comprehensive total factor productivity in China?

Total factor productivity is an important symbol of high-quality economic development. At present, the question of whether the digital economy can infuse fresh impetus into enhancing total factor productivity has emerged as a prominent concern in China. This paper constructs a new undesirable output to measure comprehensive total factor productivity (CTFP) with the slack-based measure (SBM) undesirable Malmquist-Luenberger index by using 2011-2020 Chinese provincial panel data. Then, this paper explores the impact of the digital economy (DIG) on CTFP with a fixed effects (FE) panel model and a mediating effect model. The results show that CTFP increases by an average of 3.9%, technical efficiency contributes -1.1%, and the contribution rate of technological progress is 5.0%. Technological progress is the main source of CTFP growth. The empirical findings show that the DIG has a positive and significant impact on CTFP. This paper conducts various robustness tests, and the results remain consistent with the previous conclusion. Moreover, mechanism tests suggest that the promoting effect of the DIG on CTFP can be attributed to three main effects: technological innovation, the factor endowment structure and the educational level. Furthermore, the results of heterogeneity analysis demonstrate that the promoting effect of the DIG on CTFP exists in China's eastern, central and western regions. The findings of this research can serve as a valuable reference for informing decision-making processes related to environmental governance and high-quality economic development in China.

An evaluation of the regional heterogeneity of museums' operational efficiency and productivity changes across Chinese provinces.

Museums are critical in safeguarding cultural heritage and cultivating community educational opportunities. This research aims to evaluate operational efficiency (OE), the impact of technological change on total factor productivity change (TFPC), and the regional heterogeneity of museum performance in three regions and 31 provinces across China. To this end, the study employed DEA-SBM and the Malmquist Productivity Index to gauge OE, TFPC, and determinants of TFPC (efficiency change or emerging technologies change) across 31 provinces for 2012-2021. Results reveal that the average OE of the Chinese Museum is 0.8394. It shows a 16.06 % growth potential in the operational efficiency of Chinese Museums. Further, the OE of Chinese Museums declined over the study period from 0.8965 in 2012 to 0.8088 in 2021. Beijing, Fujian, and Hunan are ranked top with a Museum's OE Score of 1. The average MI score of Chinese Museums is 0.9744, and technology change is the main determinant of Decline in productivity change as EC = 0.9992 is greater than TC = 0.9846. The MI of Liaoning, Shanghai, Ningxia, Jiangxi, Chongqing, Sichuan, Guangdong, and Tianjin is over 1, indicating growth in total factor productivity over the study period. The eastern region of China shows higher operational efficiency and total factor productivity scores of museums than the central and western regions. The results of the Kruskal-Wallis test proved that a statistically significant difference exists among different regions of China for the OE, MI, EC, and TC of museums.

From bits to green: Unraveling the digital economy's influence on natural resource efficiency.

This study explores the impact of the digital economy (DE) on natural resource efficiency (NRE) across 275 Chinese cities between 2011 and 2021. Through a comprehensive empirical analysis, we find that the DE significantly positively affects NRE. A key moderating factor in this relationship is green technological innovation (GTI), focusing on the quality rather than the quantity of green technology. Our study also uncovers regional variations of moderating effect. Additionally, we identify several mechanisms through which the DE contributes to enhanced NRE, including the transformation of industrial structure and improvements in green total factor productivity. A detailed heterogeneity analysis shows that the DE's impact on NRE varies according to city-specific factors such as natural resource endowment, city size, environmental regulations, and administrative levels. These findings provide a more nuanced understanding of how the DE influences NRE at the urban level, contributing to the broader discourse on sustainable development in the digital age. Our research offers policy recommendations and potential pathways for cities to leverage the DE for greater natural resource efficiency.

Industry star or production elite: evidence from total factor productivity of Chinese electricity sector's green transformation.

China is constantly seeking rapid, high-quality growth in order to meet its carbon peaking and neutrality goals. Approximately 40% of China's carbon emissions come from the electric power industry, which is beset by issues of poor efficiency and excessive emissions. Thus, it is essential to determine if environmental restrictions increase economic benefits total factor productivity while still preserving the environment. We use the Quasi-DID method to examine the impact of carbon emissions trading scheme on firm-level total factor productivity of electric power companies. The findings demonstrate the following: (1) carbon emissions trading scheme considerably impedes total factor productivity development; (2) the primary cause of this detrimental impact is the need for additional improvements in marketization since green innovation is still in its infancy; (3) additional study indicates that law enforcement's heterogeneity is what affects this restriction. Our research may both enhance the Chinese carbon emissions trading scheme's effectiveness assessment framework and point out several potential avenues for high-quality growth.

An integrated framework for improving green agricultural production sustainability in human-natural systems.

Water scarcity, land pollution, and global warming are serious challenges and crises facing the development of sustainable or green agriculture and need to be addressed using efficient and environmentally friendly management strategies. This paper proposed an integrated framework appropriate for agricultural green total factor productivity (AGTFP) assessment coupled with microscopic and mesoscopic perspectives under water-energy-food (WEF) nexus, which generated scientific and reasonable strategies for green and low-carbon agriculture from internal core factors and peripheral environmental impacts to improve green agricultural production sustainability. Taking the Lianshui irrigation district (LID) with three sub-areas as the object, internal core factors were explored by partial least squares regression (PLSR) and the external impact path through partial least squares structural equation modeling (PLS-SEM). Results indicated that AGTFP in LID was the smallest (0.818) compared to the three sub-areas and was in a fluctuating state. Meanwhile, AGTFP which was calculated considering undesirable outputs, was closer to tangible productivity. Resource endowments and technical facilities will promote agricultural production, desirable outputs will stimulate green production, and undesirable outputs can inhibit green production. The external influence pathway was shown to be primary environment - > secondary environment - > economic aspects - > social aspects - > AGTFP. The innovative perspectives presented in this study can facilitate preferable decisions and avoid unintended consequences for human-natural systems.

Measuring Technical Efficiency and Productivity of Secondary Maternal and Child Health Hospitals in Hubei, China: Some Evidences from Hubei Province of China 2019 to 2021.

Environmental factors like COVID-19 can have significant impact on technical efficiency (TE) and total factor productivity (TFP) of health services provided. In this study, focusing on Maternal and Child Health (MCH) hospitals in Hubei Province of China in 2019 to 2021, we aimed to measure their TE and TFP, identify some influential environmental factors, and propose some policy recommendations. Altogether 62 secondary MCH hospitals were selected as the study sample. Four input indicators, 3 output indicators, and 4 environmental indicators were selected to analyze the panel data from 2019 to 2021. Three-stage Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI) model were employed to estimate the TE and TFP of these hospitals. During 2019 to 2021, the inputs of the sample hospitals had increased, while the outputs had decreased. The inputs redundancy was negatively associated with birth rate, number of residents, and GDP per capita (P < .05). It was positively associated with number of COVID-19 infections (P < .05). The adjusted TE scores in 2019 to 2021 were 0.822, 0.784, and 0.803, respectively. The TFP declined in 2020 and 2021 compared to 2019, with scores being 0.845 and 0.762. The technical efficiency change (TEC) scores from 2019 to 2021 were 0.926 and 1.063. The technological change (TC) scores from 2019 to 2021 were 0.912 and 0.716. During 2019 to 2021, the operation of sample hospitals had been significantly influenced by environmental factors like COVID-19 pandemic, low birth rate, number of residents, and GDP per capita. The inputs had increased but outputs had decreased, leading to an increase in inputs redundancy and a decline in TE. The TFP showed a downward trend, with TC and SEC being the priority directions for improvement. Some recommendations are made for both hospitals and government to continuously improve the TE and TFP.

How does market-incentive environmental regulation affect enterprises green growth? The mediating role of R&D investment and innovation output.

Manufacturing enterprises is a country's economic mainstay. However, their longtime extensive growth pattern of "high growth and high emission" has brought huge environment pollution and restricted sustainable development. Under the circumstance of carbon reduction and global green development, market-incentive environmental regulation (MER) has attracted the attention of scholars and become a kind of important methods of encouraging manufacturing enterprises green growth. Presently, two fairly distinct viewpoints of "Follow Cost" and "Porter Hypothesis" both have their own supportive research results, and the explanation for the role of MER is completely opposite. What's more, empirical research at the enterprise level is scarce. Therefore, this study makes a further analysis from the perspective of enterprises heterogeneous innovation ability. Guided by the classic theory of "Follow Cost" and "Porter Hypothesis", this study aims to evaluate the applicable conditions of MER's environmental improvement effect, and testing the differential impact mechanism of MER on enterprise Green Total Factor Productivity (GTFP), enterprise Green Technological Change (GTC) and enterprise Green Efficiency Change (GEC). All these give theoretical and empirical supplementation for the rationality of related theories. This study examines the hypotheses and mechanism according to 1220 Chinese manufacturing listed companies data 2011-2020. The empirical results indicate that: (1) In short term, MER has a significant positive impact on GTC, and a significant negative impact on GTFP and GEC. (2) As innovation driven factors, both enterprise R&D investment and innovation output play the mediating role. (3) Heterogeneity analysis indicates that the impact mechanism varies depending on enterprise industry-type, location and digital level. Thus, policymakers should develop appropriate MER policies, and manufacturing enterprises should strengthen technological innovation to help achieve environmental sustainability and profit performance.

The role of renewable energy and total factor productivity in reducing carbon emissions: A case of top-ranked nations in the renewable energy country attractiveness index.

On the one hand, economies, particularly developing ones, need to grow. On the other hand, climate change is the most pressing issue globally, and nations should take the necessary measures. Such a complex task requires new theoretical and empirical models to capture this complexity and provide new insights. Our study uses a newly developed theoretical framework that involves renewable energy consumption (REC) and total factor productivity (TFP) alongside traditional factors of CO2 emissions. It provides policymakers with border information compared to traditional models, such as the Environmental Kuznets Curve (EKC), being limited to income and population. Advanced panel time series methods are also employed, addressing panel data issues while producing not only pooled but also country-specific results. 20 Renewable Energy Country Attractiveness Index (RECAI) nations are considered in this study. The results show that REC, TFP, and exports reduce CO2 emissions with elasticities of 0.3, 0.4, and 0.3, respectively. Oppositely, income and imports increase emissions with elasticities of 0.8 and 0.3. Additionally, we show that RECAI countries are commonly affected by global and regional factors. Moreover, we find that shocks can create permanent changes in the levels of the factors but only temporary changes in their growth rates. The main policy implication of the findings is that authorities should implement measures boosting TFP and REC. These factors are driven mainly by technological progress, innovation, and efficiency gains. Thus, they can simultaneously reduce emissions while promoting long-run green economic growth, which addresses the complexity mentioned above to some extent.

Efficiency and productivity gains of robotic surgery: The case of the English National Health Service.

This paper examines the effect of new medical technology (robotic surgery) on efficiency gains and productivity changes for surgical treatment in patients with prostate cancer from the perspective of a public health sector organization. In particular, we consider three interrelated surgical technologies within the English National Health System: robotic, laparoscopic and open radical prostatectomy. Robotic and laparoscopic techniques are minimally invasive procedures with similar clinical benefits. While the clinical benefits in adopting robotic surgery over laparoscopic intervention are unproven, it requires a high initial investment cost and carries high on-going maintenance costs. Using data from Hospital Episode Statistics for the period 2000-2018, we observe growing volumes of prostatectomies over time, mostly driven by an increase in robotic-assisted surgeries, and further analyze whether hospital providers that adopted a robot see improved measures of throughput. We then quantify changes in total factor and labor productivity arising from the use of this technology. We examine the impact of robotic adoption on efficiency gains employing a staggered difference-in-difference estimator and find evidence of a 50% reduction in length of stay (LoS), 49% decrease in post-LoS and 44% and 46% decrease in postoperative visits after 1 year and 2 years, respectively. Productivity analysis shows the growth in radical prostatectomy volume is sustained with a relatively stable number of urology surgeons. The robotic technique increases total production at the hospital level between 21% and 26%, coupled with a 29% improvement in labor productivity. These benefits lend some, but not overwhelming support for the large-scale hospital investments in such costly technology.

Exploring the dual impact: Dissecting the impact of tourism agglomeration on low-carbon agriculture.

Despite extensive research on the relationship between tourism and agriculture, the specific impact of tourism on agriculture's low-carbon transition has not been thoroughly investigated. This study analyzes the effects of tourism agglomeration on agricultural carbon intensity across 30 Chinese provinces from 2001 to 2020. It is framed within the context of rural digitalization, with a particular emphasis on the integration of agro-tourism and the total factor productivity of agriculture. Utilizing spatial econometric models, we find that tourism agglomeration hinders the low-carbon transition in agriculture by influencing carbon intensity both directly and indirectly. At the national level, the impact of tourism agglomeration follows an inverted-U curve with respect to agro-tourism integration and carbon intensity. At the regional level, the effects vary, with weaker indirect influences in major grain-producing areas. Furthermore, rural digitalization appears to lessen the adverse impacts of tourism on carbon intensity. This study also identifies significant spatial spillover effects from tourism agglomeration. The findings suggest that provinces with high tourist influx should enhance investments in climate-smart agricultural practices and technologies to counteract these negative impacts. Moreover, integrated governance of tourism and agriculture is essential for achieving carbon neutrality in both sectors.

Has environmental protection tax reform promoted green transformation of enterprises? Evidence from China.

Facing the increasingly stringent constraints of resources and the environment, the green transformation of enterprises is imperative. This study selects A-share listed companies in Shanghai and Shenzhen from 2014 to 2021 as samples, using the difference-in-differences method to examine the impact of the environmental protection tax reform (EPTR) on the green transformation of enterprises. The results indicate that the EPTR can promote the green transformation of enterprises, achieving this through three channels: raising the cost of pollution, strengthening the rigidity of law enforcement, and breaking the collusion between the government and enterprises. Notably, this promotional effect is more significant in non-state-owned enterprises, companies in the eastern and western regions, firms with low financing constraints, and those with high media attention. Further analysis shows that the EPTR has a positive impact on the green total factor productivity (GTFP) of enterprises, which implies that enterprises are not only proactively pushing for a green transformation at the strategic level but also taking practical actions. This study responds to the problem of the greening of tax system to promote the green development of enterprises from two aspects of enterprise strategic implementation and productivity and explores the impact mechanism from the perspective of institutional logic. It enriches the research on the effectiveness of the EPTR at the micro-level and broadens the research perspective on the impact mechanisms of environmental regulation. The findings of this study provide references for further optimising relevant policies and regulations and also offer insights for other countries and regions seeking sustainable development.

Does ecological economic zone policy affect pollutant emission: Evidence from a case study of Dongting Lake.

Environmental pollution affects human health, reduces work motivation, and addressing environmental pollution is a common challenge faced by the world. The Chinese government has recently implemented a new environmental policy - the national-level ecological economic zone - to develop a green economy and reduce environmental pollution. This study utilizes the difference-in-difference method to analyze the impact of the Dongting Lake ecological economic zone on environmental pollution. The results show that: policy led to a 68 % reduction in sulfur dioxide emissions. This impact was more pronounced in economically developed areas, regions with a high concentration of foreign-invested, and areas with greater economic openness. Mechanism tests indicate that the policy reduces environmental pollution by promoting technological progress. Robustness checks show that the policy also resulted in a 37 % reduction in industrial wastewater emissions. The results offer new insights to advance the development of the ecological economic zone more effectively. The ecological economic zone should focus on enhancing technological advancement and green total factor productivity to amplify the policy's positive effects.

Analysis of the impact factors of industrial structure upgrading on green total factor productivity from the perspective of spatial spillover effects.

Green development has already been a vital part of China's high-quality economic progress in the future, and accelerating the restructuring and improvement of the industrial structure plays a crucial roll in promoting a regional green economy. In this article, based on the data of 278 prefecture-level cities in China from 2011 to 2020, the SBM directional distance function and Malmquist-Luenberger (ML) index are used to gauge regional green total factor productivity (GTFP). The spatial Durbin model is also introduced to investigate the spatial spillover mechanism of GTFP and its influencing factors under the optimized and upgraded industrial structure. The study indicates that the optimization of the industrial structure have an important effect in promoting the growth of GTFP. Specifically, industrial structure integration has a greater bearing on the increase in GTFP, while there is a difference in the effectiveness of industrial structural advancement and rationalization of GTFP. Economic growth level inhibits the enhancement of GTFP, and urbanization level and industrial agglomeration have a significant negative impact on the enhancement of GTFP in the spatial dimension. On a different hand, foreign investment degree and government intervention level have a significant positive affect on regional GTFP. In addition, this study fills the research gap of the regional industrial structure upgrading influence on GTFP, which has great theory and practice value for promoting China's high quality growth of green economy.