Green Total Factor Productivity Growth Research Articles

How can green finance promote the transformation of China's economic growth momentum? A perspective from internal structures of green total-factor productivity

Green financing is a crucial tool for promoting China's economic growth and helping to achieve carbon neutrality, but its implications on the internal dynamics of green economy remain uncertain. This study examines the impacts of green finance on China’s Green Total Factor Productivity (GTFP) and its internal factors, including technical innovation, industrial structure, balanced regional growth, scale, and resource allocation efficiency, by using a three-hierarchy meta-frontier Data Envelopment Analysis (DEA) and provincial panel data from 2008 to 2020. The findings show that: (1) regional green finance development may greatly boost the growth of GTFP, and the findings remain reliable after applying a series of robustness tests; (2) further research finds that green finance enhances GTFP by promoting technological innovation, facilitating the optimization of industrial structure, and improving resource allocation efficiency; and (3) there are significant spatial heterogeneities in this effect. The effect of green finance on GTFP is more pronounced in developed and market-oriented regions. This study helps to understand the pathways of green finance affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions.

The Impacts of Water Ecological Carrying Capacity on Green Total Factor Productivity: The Case of Chemical Industry in Jiangsu, China

The chemical industry is not only a crucial sector of national economy, but also a significant consumer of water resources and a major initiator of water pollution. The sustainable development of this sector is intricately linked to the regional water ecological carrying capacity (WECC). Based on SBM-DEA and Global Moran’s I, the green total factor productivity (GTFP) and spatial correlation characteristics of the chemical industry in 13 cities within China’s chemical agglomeration region in Jiangsu Province were estimated from 2015 to 2019. By combining the WECC results, the Tobit model was employed to reveal the driving factors of WECC in optimizing GTFP. The results indicated that the regional WECC in southern Jiangsu was increasing compared with that in northern Jiangsu, which promoted the growth of GTFP. WECC has been a positive radiation-driven effect since 2017, and the optimization of the various subsystems of WECC has had a different impact on GTFP. For the sustainable development of Jiangsu’s chemical industry, effective water resource policies should be formulated by the government, while enterprises need to pursue sustained structural adjustments.

Clean air policy and green total factor productivity: Evidence from Chinese prefecture-level cities

Clean air policy is an important mechanism for improving the urban environment and promoting green economic development. Green total factor productivity (GTFP) is an important way to measure these impacts. We apply the super-efficiency slack-based measure model, considering undesirable output, and the Global Malmquist-Luenberger index to measure the GTFP of 278 prefecture-level cities in China from 2005 to 2020. We find that GTFP growth is driven by both green technology progress (GTC) and green technology efficiency change (GEC). The traditional total factor productivity is overestimated, because energy and environmental factors are not considered. GTFP growth is higher in the cities in the eastern coastal regions compared to the western regions. We analyze the effect of clean air policy on GTFP using a difference-in-differences model and spatial-difference-in-differences model, and further conduct a heterogeneity analysis and mechanism analysis. The results show that clean air policy promotes GTFP growth. In addition, there is a significant negative spatial spillover effect with respect to the impact of clean air policy on GTFP. The heterogeneity analysis results show that the impact of clean air policy on GTFP growth is lower in resource-based cities and cities in the northern region, compared with non-resource-based cities and cities in the southern region. Further, the impact of clean air policy on GTFP growth is mainly achieved through GTC, GEC, innovation, and financial development. In resource-based cities and cities in the northern region, clean air policy decreases GTFP by inhibiting GTC, innovation, and financial development.

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.

A Study on the Changes of Green Total Factor Productivity in Chinese Cities under Resource and Environmental Constraints

Confronting the dual challenges of excessive resource consumption and environmental pollution, the traditional extensive economic development pattern significantly impeded the high-quality development of the Chinese economy. Examining variations in green total factor productivity across different types of cities holds substantial practical significance for promoting coordinated regional development and facilitating the green transformation of urban economies. Panel data from 283 cities in China spanning the years 2006 to 2020 were selected for analysis. The window-Malmquist–Luenberger index model, incorporating a mixed distance function, was employed to assess changes in green total factor productivity among the sample cities. The results were then categorized and analyzed based on different city attributes. The findings indicate that (1) the variation in green total factor productivity across China’s four major regions from 2006 to 2020 is generally characterized by an initial decline followed by an increase; (2) the proportion of cities with significantly improved green total factor productivity decreases from the east to the central, western, and northeastern regions; (3) the increase in green total factor productivity is positively correlated with city size, suggesting that larger cities experience higher growth in green total factor productivity; (4) first- and second-tier cities exhibit a relatively high mean value of green total factor productivity growth, while third-, fourth-, and fifth-tier cities demonstrate relatively lower growth.

Effects of environmental information disclosure on the green development of mining industry: Evidence from Chinese provincial mining sub-sectors

How environmental information disclosure (EID) affects green transformation of mining industry (MI) is still unknown. Based on the panel data of China's provincial mining sub-sectors, this study explores the effects of EID on the green total factor productivity (GTFP) of China's mining sub-sectors and its influence mechanism. The research shows that EID exerts an inverted U-shaped influence on the GTFP growth of MI, implying that reasonable EID facilitates the green transformation of China's MI, while excessively EID requirements may be counterproductive. The above conclusion still holds after considering the endogeneity and conducting a series of robustness tests. Further analysis shows that the impact of EID on the GTFP of MI has a lag and long-term, and the current EID affects its future GTFP. Meanwhile, EID has a more remarkable effect on the GTFP of the MI in the eastern and central regions and the mining and washing of coal (S3) and extraction of petroleum and natural gas (S4). Mechanism analysis reveals that EID affects the GTFP of the MI through technological innovation, but due to the ‘black expected effect’, EID is still unable to increase the GTFP of the MI through energy structure. This study provides important insights for the government to fully leverage the positive role of social supervision in promoting the green development of heavy polluting industries such as MI.

Going green while getting lean: Decomposing carbon and green total factor productivity

While research on carbon productivity is growing rapidly, the role of structural change in green transition remains unexplored due to the scarcity of firm-level emission data. This study addresses this gap by utilizing unique register-based greenhouse gas emission data from Finland’s energy-intensive manufacturing firms for 2000–2019. Applying a structural change productivity decomposition, we break down the sector’s carbon productivity and green total factor productivity into four components: contributions from non-switching continuing firms, industry-switching continuing firms, the effects of entry and exit, and resource allocation. The findings highlight the important role of structural change in the sector’s productivity. Non-switching continuing firms emerged as the key drivers of both carbon and green total factor productivity growth. The contribution of entry and exit was negative during the financial crisis, while inefficient resource allocation significantly hindered productivity growth throughout the study period. These findings emphasize the importance of public subsidies targeted at environmentally efficient firms to enhance their competitiveness under challenging market conditions. Furthermore, the establishment of a stable yet positive carbon price would incentivize less-productive firms to adopt environmentally friendly technologies.

How does artificial intelligence affect the transformation of China's green economic growth? An analysis from internal-structure perspective

Artificial intelligence (AI) has been proved to be an important engine of green economic development, yet how it will affect the internal structure of green economy is unknown. The aim of this study is to examine the impact and its mechanism of AI on green total factor productivity (GTFP) from the internal-structure perspective, by using provincial panel data of China from 2009 to 2021 and global Malmquist index. The main research results show that: (1) the development of AI contributes to China's GTFP growth. And this effect is more significant in undeveloped areas; (2) AI promotes China's GTFP growth mainly by improving resource allocation efficiency, while it exerts little impact through the paths of technological progress and scale efficiency; (3) the transmission mechanism of AI on GTFP varies greatly among China's three main regions. In the eastern region, AI improves GTFP mainly by both advancing technological progress and improving resource allocation efficiency, while in central region AI contributes to GTFP growth mainly through technological progress. Compared with the eastern and central regions, AI in the western region plays a stronger impact on GTFP through the channel of improving scale efficiency. This study helps to understand the pathways of artificial intelligence affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions.

Digitalization and sustainable development: Evidence from OECD countries

To examine the intricate relationship between digitalization development and sustainable development, this study commences its analysis by employing the entropy method to establish an integrated indicator of digitalization development among advanced nations. Subsequently, we utilize a panel dataset spanning a decade from 2010 to 2020, encompassing 36 developed countries, to estimate Green Total Factor Productivity (GTFP) growth. We establish a fixed effects model, a mediation effect model and a threshold regression model to explore the relationship between the two variables. The empirical findings of this research reveal a significant positive association between the progress and enhancement of digitalization and the advancement of sustainable development (GTFP). Furthermore, this research elucidates the underlying mechanism by which digitalization development indirectly fosters the advancement of green productivity. This facilitation occurs through the promotion of technological innovation, the enhancement of human capital, and tupgrades in the industrial framework. Notably, our study finds the non-linear relation between digitalization development and GTFP growth, suggesting that the magnitude of impact on environmental performance is contingent on the scale of technological innovation, the growth of human capital, and the level of financial development.

The impact of digital economy on green total factor productivity considering the labor-technology-pollution factors

The digital economy provides new impetus for the high-quality development of manufacturing industry. Through the DEA-Malmquist model and panel regression model, this paper confirmed that there is a positive and significant relationship between the development of digital economy and the green total factor productivity (GTFP) of manufacturing industry. The research result is as follows: (1) the development of digital economy can enhance the overall GTFP of manufacturing industry. (2) The green technology progress brought by the development of digital economy is the main path to promote the GTFP of manufacturing industry. (3) The heterogeneity analysis shows that the impact of digital economy on GTFP of high pollution manufacturing industry is significantly positive, the impact of labor-intensive manufacturing industry is significantly negative, and the impact of technology intensive manufacturing industry is not obvious. The contributions of this study are as follow. In terms of theory, this study theoretically continues Solow’s classical theory, demonstrating the scientific nature of digital technology progress in promoting GTFP growth. In empirical analysis, this study build a new digital economy development level evaluation index system based on the perspective of manufacturing industry. In addition, this study also add a labor-technology-pollution perspective for the development of relevant policies.

Green total factor productivity growth and its driving forces in China’s fisheries sector

The rapid development of China’s fisheries sector has brought about significant environmental problems, which are detrimental to the sustainable development of the sector. Balancing environmental protection while promoting fisheries development has become an urgent issue in China. Based on data from 30 provincial-level administrative regions in China from 2004 to 2019, this study utilizes the Epsilon-based Measure (EBM) model considering undesirable outputs and the global Malmquist-Luenberger (GML) index to measure the green total factor productivity (GTFP) growth in China’s fisheries sector. Furthermore, it explores the spatiotemporal evolution and driving forces of fisheries GTFP growth using spatial Durbin model (SDM). The results indicate that ignoring the resource and environmental costs in fisheries production would overestimate the growth of total factor productivity (TFP) by 1.3%. The growth of fishery output primarily comes from the increase in input factors, exhibiting extensive characteristics that have been gradually diminishing over time. During the sample period, the provinces with the fastest growth in GTFP shifted from being mainly concentrated in the central and western regions to the eastern region. The local driving forces behind the improvement of fisheries GTFP include internet penetration rate, transportation convenience, education level of rural residents. The driving forces from economically similar provinces include the positive spatial interplay between provinces, fishery disaster rate, fisherman training, fishery trade openness, and urbanization rate. Overall, these finds offer a novel approach to reexamine the growth of China’s fisheries and provide valuable insights for the future fisheries development.

Challenges or drivers? Threshold effects of environmental regulation on China’s agricultural green productivity

This study investigates the effect of environmental regulation (ER) on the growth of Chinese agricultural Green Total Factor Productivity (GTFP). Threshold model results suggest an inverted-U shaped interconnection between command-control ER and growth of agricultural GTFP, a decreasing positive marginal effect of voluntary ER, and an absence of influence of incentive-based ER. Regional heterogeneity test indicates that command-control ER affects agricultural GTFP growth in a far more favorable way in less developed provinces than in more developed provinces, and only the former can benefit from the synergistic effect between command-control and voluntary ER. Mediating effect test results reveal that agricultural green innovation and grain crop proportion are channels through which ER affect agricultural GTFP growth, highlighting the pressing need to stimulate green innovation and realize green transformation of grain production.

Does innovative city pilot policy promote urban green growth in China? An analysis of green total factor productivity, 2005–2020

The innovative city pilot policy (ICPP) is an essential manifestation of China’s construction of an innovative and green-driven development country. We incorporated urban green total factor productivity (GTFP) growth into the evaluation of ICPP. Based on the panel data of 223 cities in China from 2005 to 2020, we used the difference-in-differences model to empirically assess the influence and mechanism of the ICPP on urban GTFP growth. The main results show that (i) The ICPP has maintained an effectively fluctuating promotion on urban GTFP growth, mainly manifested in the urban green technological progress improvement. (ii) The ICPP has urban heterogeneity in promoting GTFP growth in pilot cities, mainly affecting key cities such as provincial capitals. (iii) The interaction between the agglomeration of producer services and the ICPP inhibits GTFP growth in pilot cities.

Assessing green total factor productivity and spatial spillover effect in China’s maize industry for sustainable food production: a carbon emissions perspective

Although Enhancing green total factor productivity (GTFP) within the agricultural sector is crucial for fostering sustainable development. In this paper, the GTFP of China’s maize industry is analyzed using the SBM-GML index method, considering data from the primary maize-producing provinces from 2004 to 2020. This analysis incorporates carbon emissions as undesirable outputs. The spatial Durbin model aids in investigating the factors influencing maize GTFP. Our findings reveal a positive trajectory for China’s maize GTFP over the designated period, featuring an average yearly increase of 0.8%. This ascension is primarily attributed to advancements in green maize technology. In the key cultivation regions of the Yellow and Huaihai areas, the Northern region, and the Southwest region, the average annual growth rates were 1.5%, 0.87%, and 0.09%, respectively. Among the direct influences, variables such as regional human capital, the extent of maize cultivation area, financial assistance towards agriculture, and the degree of agricultural mechanization considerably bolster the optimization of maize GTFP. Conversely, urbanization and the prevalence of natural disasters in the agricultural sector pose substantial challenges to enhancing maize GTFP. Furthermore, the spatial spillover effects reveal that natural agricultural disasters in a particular region inadvertently contribute to the improvement of maize GTFP in adjacent regions. Additionally, the regional human capital levels can significantly impede the progress of maize GTFP in neighboring regions. Therefore, to ensure food security, it is imperative to actively advocate for green development within the maize industry to Enhancing green total factor productivity (GTFP) in agriculture is crucial for agriculture to promote sustainable development. In this paper, using data from 2004-2020 from China’s main maize-producing provinces, the SBM-GML index method is used to measure China’s maize GTFP, and the spatial Durbin model is applied to examine the influencing factors and spatial spillover effects of China’s maize GTFP growth. The results of the study revealed a positive trajectory of Chinese maize GTFP over the specified period, with an average annual growth of 0.8%. This enhancement is mainly attributed to the progress of green maize technology. The average annual growth rates were 1.5%, 0.87%, and 0.09% in the major cultivation areas of the Yellow and Huaihai regions, the northern and southwestern regions, respectively. The analysis of influencing factors showed that among the direct influencing factors, variables such as regional human capital, extent of maize cultivation area, financial assistance to agriculture and degree of agricultural mechanisation contributed significantly to the optimization of maize GTFP. Conversely, urbanisation and the prevalence of natural disasters in the agricultural sector pose significant challenges to improving maize GTFP. Furthermore, spatial spillovers reveal that natural agricultural disasters in a given region unintentionally contribute to the improvement of maize GTFP in neighbouring regions. Furthermore, regional human capital levels can significantly hinder progress in maize GTFP in neighbouring regions. Therefore, in order to ensure food security, the greening of maize production must be actively promoted.

Digital inclusive finance and green total factor productivity growth in rural areas

Transitioning to environmentally friendly economic growth is crucial for achieving sustainable development. Digital inclusive finance (DIF) can promote environmentally friendly economic activities and play a crucial role in fostering green and low-carbon development. In this context, a fundamental research question revolves around the theoretical foundations of how DIF impacts the growth of green total factor productivity (GTFP) and whether this relationship can be empirically verified. This question is particularly relevant for rural areas where financial innovations are necessary for the advancement of businesses and society as a whole. Additionally, expanding DIF can bring benefits to the environment, which is affected by agricultural activities. Therefore, it is important to assess the mechanisms behind the development of DIF and its impact on agricultural productivity growth. This paper presents an analysis of the interaction between DIF and GTFP growth in China's agricultural sector. Panel data from 2012 to 2019 at the province level are used for this analysis. The results reveal that GTFP and DIF demonstrate similar growth patterns, with DIF significantly contributing to GTFP growth. DIF can enhance GTFP by promoting information channels and fostering innovation in green technologies.

Research on the Influencing Factors of The Green Coordinated Development of Productive Service Industry and Manufacturing Industry Under the Background of Dual Carbon

Under the dual-carbon background, along with the process of the two-wheel drive development strategy, the industrial synergistic agglomeration has quietly become the "new normal" of urban industrial spatial layout, and the green total factor productivity has become an essential measure of the quality of economic development of cities in China. This project takes the synergistic agglomeration at the factor level between the productive service industry and manufacturing industry as the perspective and analyzes the realization mechanism of green total factor productivity growth under the synergistic agglomeration of the manufacturing industry and productive service industry from the current situation of China's industrial development, which is also a deepening and expanding of the theory of agglomeration economy. This project first discusses the "greening" issue in the development process of the productive service industry and manufacturing industry, and applies the super-efficient DEA model to account for the green total factor productivity of the productive service industry and manufacturing industry according to the difference of industrial characteristics, and then expounds the inner mechanism of green total factor productivity growth under the synergistic agglomeration of industries. Then, the panel data of 24 provinces in China are used to modify the existing indexes for measuring the level of industrial synergistic agglomeration and analyze the impact factors of the synergistic evolution of the productive service industry and the manufacturing industry on the green total factor productivity. Finally, through scenario simulation analysis, different policy scenarios with different policy incentives are set up to study the impact of policy incentives further and propose corresponding policy recommendations.

RETRACTED ARTICLE: Digital Economy, Technical Innovation and China’s Green Total Factor Productivity Growth

This study investigates the impact of the digital economy (DE) on green total factor productivity (GTFP) and its transmission mechanism. Using panel data from 256 cities in China from 2009 to 2020, the study examines a directional distance function and the Malmquist–Luenberger productivity index to estimate the GTFP growth and constructs an ordinary least squares model to explore the impact effect and mechanism. Three findings are drawn from the estimation results: (1) The DE has significantly promoted GTFP. (2) Technological innovation has significantly aided in the promotion of GTFP. (3) By encouraging technological innovation, the DE further enhances the promotion of GTFP, verifying the DE → technology innovation → green conduction mechanism of total factor productivity.

On the driving forces of green total factor productivity growth in China: evidence from biased technological progress analysis

The traditional model of factor-driven economic growth can no longer be maintained due to an increasing demand to save energy and reduce emissions and a rapid rise in the cost of related factors. The concept of green total factor productivity (GTFP) has emerged as an essential component of high-quality economic growth; consequently, how to boost GTFP through the development of technical advancement has become an important question in recent years. An improved CES production function of labor, capital, and energy is created using the theoretical framework for biased technological growth as its foundation. Subsequently, the mechanisms resulting from the synergy of factor structure, factor efficiency and biased technological progress (BTP) on GTFP are theoretically deduced and empirically analyzed. The conclusion shows that the types of technical advancement are mainly net labor-enhancing and net energy-enhancing technical advancement in China from 2001 to 2017. Due to the biased effect of technical advancement, the relative comparison of the three elements is determined predominantly by excessive capital investment and less by labor and energy. Factor-enhancing technical advancement led to the growth of GTFP, while the synergistic effect of BTP, factor structure and factor efficiency hindered the growth of GTFP.

Green Technological Progress Implications on Long-Run Sustainable Economic Growth

The main objective of this study is to model and examine the green technological progress’s positive and negative externalities spillover effects on the sustainable economic growth of 15 economies from Asia, the Pacific, and Latin America. The study calculated labour and capital contributions to green total factor productivity growth via the inclusion of CO2 emissions as undesirable output or private unpriced input and energy consumption that proxies for unmeasured pollutant emissions. The results, in most cases, confirm that a high level of air pollutant emissions generated by these countries’ economic development affected the growth rates of TFP growth as an indicator of green technological progress. The significant contribution of this study is to integrate innovation and climate change in the form of green productivity (green technological progress). The role of these externalities on long-term sustainable economic growth has been ignored by several past studies undertaken in these areas.

Unleashing the power of informatization: How does the “information benefiting people” policy affect green total factor productivity?

Information development is a necessary means for China to achieve technology force and an effective path toward sustainable development. Regarding the “information benefiting people” policy led by the Chinese government as a quasi-experiment of information technology, this study builds an analysis framework for the impact of informatization on green total factor productivity (GTFP). Based on panel data at the Chinese city level from 2006 to 2019, this study further empirically evaluates the mechanism path, heterogeneity, and spatial spillover effects between informatization and GTFP by using a difference-in-difference (DID) model, a mediating model, and a spatial DID model. The results show that (1) the information benefiting people policy contributes considerably to greater GTFP levels in the pilot cities; (2) the policy also promotes the rapid growth of GTFP by fostering the advancement of education, the share of the number of ICT employees, and green technology innovation; (3) the information benefiting people policy raises GTFP in the eastern cities, small cities, and non-old industrial based cities; and (4) the policies lead to a large rise in local GTFP levels, but a decline in GTFP in surrounding cities. This paper offers valuable reference suggestions for the Chinese government to implement informatization-policies to support green development.