Green Technological Progress Research Articles

Accelerating decarbonized economic growth through net-zero entrepreneurship: Low-carbon economic development perspective

Net-zero entrepreneurship is a novel concept introduced in the context of carbon neutrality, and exploring whether it can catalyze decarbonized economic growth is a worthy pursuit. This study constructs a comprehensive, low-carbon endogenous economic growth model to scrutinize the intricate nexus between net-zero entrepreneurship and decarbonized economic growth. Empirical validation employs a series of multiple regression models to rigorously test the hypotheses derived from the theoretical framework using an extensive dataset spanning Chinese provinces. The results reveal a nuanced landscape. (i) Net-zero entrepreneurship plays a remarkable role in promoting decarbonization growth, with considerable regional heterogeneity. (ii) Green technology progress exhibits a notable mediating effect. (iii) Environmental regulation and industrial structure optimization have positive moderating effects. (iv) The results passed alternative dependent variable and one-phase lag regression robustness tests. In a distinct contribution to entrepreneurship literature, this study augments the discourse on strategies to steer low-carbon transitions. The research findings indicate that net-zero entrepreneurship can accelerate the global decarbonization process, and green technology progress is a significant driving mechanism in this process. Additionally, it is essential to strengthen environmental agencies’ regulatory oversight and optimize industrial structures to pave the way for transformative sustainable growth. In the future, more entrepreneurs should be encouraged to engage in green technology and business model innovation to contribute to global decarbonization efforts.

Green innovation and natural resource efficiency: The role of environmental regulations and resource endowment in Chinese cities

Achieving natural resource utilization efficiency (NRUE) is a critical objective in addressing the pressing challenges of climate change and the risks associated with the finite availability of mineral resources. Enhancing NRUE can mitigate environmental impacts and support sustainable development for future generations. In this context, green innovation emerges as a pivotal driver of environmental sustainability and resource conservation. However, its potential role in advancing the NRUE has not been fully explored. To fill this gap, this study conducts an empirical analysis of 268 Chinese cities from 2010 to 2022, examining the impact of green innovation on NRUE. This study also incorporates the mediating role of environmental regulations in shaping this impact. The findings demonstrate that green innovation significantly enhances NRUE, primarily by facilitating industrial structural upgrading and reducing resource dependence. Additionally, environmental regulations strengthen the positive effects of green innovation, further amplifying its contribution to NRUE. Moreover, geographical location and differences in resource endowments among cities lead to variations in the effectiveness of green innovation on NRUE. These findings underscore the complex interplay between green technological progress, proactive government policies, and NRUE, offering valuable insights for policymakers and researchers alike.

Effects of the Policy of Re-Designation of Counties as Cities or City Districts on the Agricultural Carbon Emission: Evidence from the Yangtze River Delta Region in China

It is of great practical significance to utilize the agricultural carbon emission reduction effect of the policy of re-designation of counties as cities or city districts (RCCD) to achieve agricultural high-quality development. This paper uses panel data of 39 cities in the Yangtze River Delta region in China from 2010 to 2022, and adopts a staggered difference-in-difference model and a panel threshold model to identify the causal impact of the policy of RCCD on agricultural carbon emissions (ACE). We show that: (1) Overall, the policy of RCCD exerts a tangible dampening effect on ACE, with cities in the experimental group exhibiting a significant reduction of 0.069 in agricultural carbon emissions compared to the control group post-implementation of the policy. (2) A dual-threshold effect of environmental regulation emerges in the context of the policy of RCCD, wherein the impact on ACE varies depending on the level of environmental regulation. (3) The policy of RCCD exerts a notable inhibitory influence on urban ACE in cities with high urbanization levels, underdeveloped regions and central regions. (4) Agricultural green technology progress plays the mediating role in the relationship between the policy of RCCD and ACE. (5) The suppressive effect of the policy of RCCD on ACE is characterized by a delayed and enduring influence. Our study has both theoretical and practical implications for accelerating agricultural high-quality development.

Smarter and Cleaner? The Carbon Reduction Effect of Smart Cities: A Perspective on Green Technology Progress

In the context of the global climate change problem intensifying due to a dramatic increase in carbon emissions, smart cities, as a topical application of digitalization and intelligence, have become a new urban governance mode for countries, which helps to achieve sustainable development. This research studies the relationship between smart city construction (SCC) and carbon dioxide emissions based on the differences-in-differences model (DID) and propensity score matching (PSM) to promote China to achieve dual carbon goals and high-quality development. The findings are as follows: (a) SCC could promote carbon emission reduction by reducing urban carbon dioxide emissions by an average of 11.4%, which also has significant long-term dynamic effects. Specifically, SCC has more obvious emission reduction effects on activities, such as industrial production and waste treatment. (b) Mechanism verification shows that green technology progress is a significant booster for the carbon reduction effect in SCC. The pilot project can increase output of green patents, which helps transfer production mode and consumption patterns in an environmentally friendly manner. SCC could increase the total factor productivity (TFP) through the rational allocation and efficient use of resources, and thus reducing carbon emissions. (c) Research on city heterogeneity shows that a high level of human capital, material, and financial resources can provide support for smart cities to better achieve the carbon reduction effect. Among them, material resources have the best carbon reduction effect in the process of SCC, which could reduce carbon dioxide emissions by about 6.6–17.7%. This study is useful for policymakers to continuously and dynamically adjust urban development strategies in the future, to achieve a balance between socioeconomic prosperity and environmental sustainability.

Effect of smart city construction on an urban transition to a low-carbon economy: evidence from China.

China is currently in a new era of an urban transition to a low-carbon economy and digital economic development. Smart cities, as an advanced form of information-based urban development, may be the key to the urban transition to low-carbon emissions. This paper examined the effect of smart city construction (SCC) on urban low-carbon transitions and its transmission mechanisms in China from the dual perspectives of reducing urban total carbon emissions (TCE) and improving urban total-factor carbon emission efficiency (TFCEE). Utilizing a multi-period difference in differences (DID) method, this study was conducted based on panel data of 245 Chinese prefecture-level cities from 2003 to 2021. The results demonstrated that SCC both reduced TCE and enhanced TFCEE. The effects of SCC were stronger in cities with more stringent environmental regulations. SCC achieved the dual effect of reducing TCE and enhancing urban TFCEE by promoting green technological progress and a low-carbon transformation of city residents' lifestyles. Moreover, optimization of the industrial structure was also a transmission mechanism for SCC to improve TFCEE. These conclusions provide an empirical basis for the SCC to empower low-carbon transitions of cities and help countries in different regions to transform the extensive urban development mode and promote urban low-carbon economic development.

Spatial spillover effect and driving factors of urban carbon emissions in the Yellow River Basin using nighttime light data

Yellow River Basin (YRB) is a pivotal region for energy consumption and carbon emissions (CEs) in China, with cities emerging as the main sources of regional CEs. This highlights their critical role in achieving regional sustainable development and China’s carbon neutrality. Consequently, there is a pressing need for a detailed exploration of the urban spillover effects and an in-depth analysis of the complex determinants influencing CEs within the YRB. Remote sensing data provide optimal conditions for conducting extensive studies across large geographical areas and extended time periods. This study integrates DMSP/OLS and NPP/VIIRS nighttime light datasets for a longitudinal analysis of urban CEs in the YRB. Using a harmonized dataset from DMSP/OLS and NPP/VIIRS nighttime light from 2007 to 2021, this study quantifies CEs of 58 prefecture-level cities in the YRB. By combining ESDA, STIRPAT model and spatial econometric model, this investigation further clarifies empirically the spatial spillover effects and driving factors of urban CEs. The analysis delineates a phase-wise augmentation in urban CEs, converging towards a distinct spatial distribution characterized by “lower reach > middle reach > upper reach”. The spatial autocorrelation tests unravel a complex interplay between agglomeration and differentiation patterns within urban CEs, underscored by pronounced spatial lock-in phenomena. Significantly, this study demonstrates that urbanization, economic development, energy consumption structure, green coverage rate, industrial structure, population, technological progress, and FDI each exhibit varied direct and indirect effect on urban CEs. Furthermore, it elaborates on potential policy implications and future research directions, offering crucial insights for formulating CEs mitigation strategies to advance sustainable development.

Echoes of dependency: The impact of resource reliance on green industry transformation in China

The "resource curse" has garnered significant academic attention, yet a consensus on its causes remains elusive. This article addresses this gap by empirically examining the impact of resource industry dependence on the green transformation of manufacturing corporations (GTM), based on a precise measurement. The study identifies the effect mechanism of the "resource curse" from both macro (city) and micro (enterprise) dimensions. The findings indicate that resource industry dependence significantly hampers the GTM corporations, substantiating the "resource curse" effect. Moreover, this effect is particularly pronounced in western regions, resource-based areas, and regions with well-developed transportation infrastructure. Mechanism analysis reveals that, at the macro level, resource industry dependence stifles technological innovation, weakens market competition, and diminishes credit availability and government investments in technology for manufacturing corporations, impeding their green transformation. At the micro level, resource industry dependence impedes the GTM through reduced total factor productivity, weakened profitability, reduced scale, and increased pollution. Based on these findings, the article proposes various measures to facilitate green technological progress, optimize credit allocation, improve the business environment, and enhance technology investment at the macro level. At the micro level, measures are suggested to foster internal motivation, enhance profitability, expand the scale, and control emissions. By offering empirical evidence and policy insights, this article promotes the GTM corporations and establishes a solid micro foundation for High-quality development.

Can digital transformation curtail carbon emissions? Evidence from a quasi-natural experiment

Digital infrastructure construction (DIC) is a crucial component of digital transformation, yet its impact on the sustainable development of cities remains uncertain. To address this question, this study employs the Difference-in-Differences (DID) model to evaluate the effects of a typical DIC policy, the Broadband China Pilot (BBCP) policy. The research sample covers data from Chinese cities from 2009 to 2019. The DID estimation demonstrates that the BBCP policy effectively decreased carbon emissions (COE). Robustness tests, such as parallel trend tests, placebo tests, propensity score matching DID, and local projection DID, all confirm the negative impact of the BBCP policy on COE. Heterogeneity analysis reveals that the BBCP policy has a greater mitigation effect on COE in non-resource cities. The BBCP policy has a stronger effect on reducing the COE in cities with a higher proportion of green funds or lower fiscal expenditures. Further analysis indicates that the BBCP policy significantly improves low-carbon ecological efficiency and reduces COE intensity. The results of the mechanism analysis reveal that the BBCP policy lowers COE by enhancing the industrial structure and promoting green technological progress. The study provides policy recommendations in the realm of DIC for developing countries to achieve digital transformation and low COE development concurrently. This research can assist governments in better considering how to implement DIC policies to construct ecologically sustainable cities with low COE.

The impact of market integration on industrial green transformation: A case study of the yangtze river delta in China

Regional integration plays an important role in dicarbon reduction and sustainability development. Based on dynamic panel model and spatial econometric model, this study analyzes the impact of market integration (MI) on industrial green transformation (IGT). The study finds that: (1) MI has a nonlinear relationship with the IGT. With the increasing of MI degree, the IGT shows the characteristic of first rising and then declining. (2) MI plays a role in the IGT mainly through industrial agglomeration, resource mismatch and green technological progress, respectively. (3) The impact of MI on IGT exhibits spatial heterogeneity. Although MI significantly promotes IGT in core cities, its impact on the IGT in peripheral cities is not significant. (4) The IGT has spatial spillover effect, and the improvement of MI degree in adjacent regions can also promote the IGT in the cities.

A double machine learning model for measuring the impact of the Made in China 2025 strategy on green economic growth

The transformation and upgrading of China’s manufacturing industry is supported by smart and green manufacturing, which have great potential to empower the nation’s green development. This study examines the impact of the Made in China 2025 industrial policy on urban green economic growth. This study applies the super-slacks-based measure model to measure cities’ green economic growth, using the double machine learning model, which overcomes the limitations of the linear setting of traditional causal inference models and maintains estimation accuracy under high-dimensional control variables, to conduct an empirical analysis based on panel data of 281 Chinese cities from 2006 to 2021. The results reveal that the Made in China 2025 strategy significantly drives urban green economic growth, and this finding holds after a series of robustness tests. A mechanism analysis indicates that the Made in China 2025 strategy promotes green economic growth through green technology progress, optimizing energy consumption structure, upgrading industrial structure, and strengthening environmental supervision. In addition, the policy has a stronger driving effect for cities with high manufacturing concentration, industrial intelligence, and digital finance development. This study provides valuable theoretical insights and policy implications for government planning to promote high-quality development through industrial policy.

“Cooperation” or “competition”: Digital finance enables green technology innovation—a new assessment from dynamic spatial spillover perspectives

Green technology innovation is crucial in promoting the establishment of a green economic system. Digital finance is vital in supporting green technology innovation by combining finance and technology to extend the boundaries of financial services. This study constructs a theoretical framework by extending the Solow growth model and introduces a dynamic spatial Durbin model to investigate how China's green technology innovation is impacted by digital finance performance. Our results show that digital finance positively affects green technology innovation in local cities and hinders environmental technology improvement in nearby cities, resulting in unfavorable externalities. The mechanism check shows that digital finance motivates green technology innovation by expanding the scale of consumption, promoting industrial upgrading, and strengthening government support. The positive effects of digital finance on environmental technology improvement are prominent in regions with higher levels of digital finance, particularly in China's eastern and central regions. The degree of digitization and the depth of usage have notable positive impacts on green technology progress. Our findings provide important decision-making references on sustainable growth and have some significance for eliminating the digital development gap between regions and promoting innovation-driven development strategy.

Decoding the impact of fiscal decentralization on urban pollution intensity in China: A spatial econometric analysis

Utilizing city-level data from China, the paper employs a spatial econometric analysis to investigate the impact of fiscal decentralization on urban pollution. Empirical evidence indicates: (1) In the context of the emphasis of ecological civilization construction in China, an increase of fiscal autonomy for local governments is conducive to mitigating urban pollution intensity. Specifically, fiscal decentralization in one city not only promotes a reduction in local pollution intensity but alleviates environmental pollution problems in adjacent cities through spatial spillover effects. (2) Industrial structure upgrading and green technology progress become crucial measures for local governments to realize pollution reduction targets through fiscal expenditure. (3) Heterogeneity analysis reveals that the positive significance of decentralization is most prominent in the eastern China, while local governments with fiscal autonomy in central region tend to transfer pollution to neighboring cities. (4) There is a threshold characteristic for fiscal decentralization to promote a reduction in urban pollution intensity, and its marginal effect becomes more significant accompanied by continuous introduction of sophisticated foreign direct investment. Finally, the paper summarizes the potential significance of fiscal decentralization among Chinese local governments against the background of “Chinese-style decentralization” and proposes corresponding policy recommendations.

How Does the Digital Transformation Affect the Carbon Emissions of Manufacturing Enterprises in China? The Perspective of Green Technology Innovation

With the continuous intensification of competition among major countries and the resurgence of anti-globalization trends, countries around the world have strengthened their strategic deployment for digital transformation in the manufacturing industry. Digital development enables enterprises to transform and upgrade, and the digital transformation and green transformation of enterprises have a historic intersection. This study uses the panel data of 1900 A-share listed companies to explain the theoretical mechanism of digital transformation to promote carbon emission reduction from the perspective of green technology progress. In addition, the threshold model is used to analyze the nonlinear relationship. The results show that the digital transformation has significantly reduced the carbon emission level of Chinese manufacturing enterprises, and the conclusion is still true after the instrumental variable estimation and robustness test. Heterogeneity analysis found that the carbon emission reduction in state-owned enterprises is more obvious. Green technology innovation capability shows the technology dividend effect, which is an important way for digital transformation to promote carbon emission reduction. This study expands the research on the sustainable development of China’s manufacturing industry and provides guidance for policy makers and business decision makers.

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.

Innovation or introduction? Impacts of the low-carbon city pilot policy on the pathways toward green technology progress

To examine whether the low-carbon city pilot (LCCP) policy influences the green technology innovation (GTI) or embodied technology introduction (ETI), two different pathways to green technology progress, in manufacturing enterprises in China, this study employs a staggered difference-in-difference (DID) model to evaluate the effects of the policy. The findings suggest that the LCCP policy has stimulated an increase in the quantity of GTI and ETI among enterprises, but reduced the quality of innovation. Large, high-carbon-intensity, and state-owned enterprises are more likely to engage in GTI, while small, low-carbon-intensity, and non-state-owned enterprises prefer ETI. The policy is effective in alleviating financing constraints and improving environmental concerns. Both GTI and ETI play a crucial role in economic performance, while the latter also promotes environmental and ESG performance. Accordingly, we recommend establishing a policy-compatible evaluation system, strengthening mandatory and incentive measures, and cultivating a green innovation ecosystem, etc., to improve the performance of the LCCP policy.

Environmental, social and governance performance and green transformation strategies for enterprises: Improving technical efficiency or expanding technological boundaries.

Under the ongoing implementation of the "dual carbon" goal, research has focused on the impact of Environmental, Social, and Governance (ESG) initiatives on green innovation. However, few studies have analyzed in depth the mechanisms of ESG impact on green total factor productivity (green TFP). Here, we explored the impact of ESG performance on green TFP, green technical efficiency, and green technological progress using A-share listed companies in China's Shanghai and Shenzhen stock markets from 2011 to 2021. The results show that good ESG performance can significantly improve the green TFP of enterprises, and that this effect is more prominent in industries with lower environmental risks and enterprises in the growth and maturity stages. We identified the importance of the psychological account path and propose that the promotional effect of ESG performance on green TFP mainly derives from improving green technical efficiency, rather than from expanding green technological boundaries. These findings have practical implications for guiding companies to implement ESG concepts, strengthening the synergistic role of government regulation and professional supervision, and promoting micro-level implementation of innovation-driven and sustainable development strategies, thereby promoting high-quality development.

Trade openness and green technology: The extent of trade openness and environmental policy matter

Much effort has been devoted to understanding how trade openness is linked to technological progress. Less documented is the effect on green technology, which is particularly important as it is green technological progress that alleviates environmental degradation while improving economic growth. To fill the void, this paper empirically examines whether trade openness drives green technology development and whether the effect depends on the extent of trade openness and environmental policy stringency. In a sample covering both advanced and developing countries, the paper finds that green technology first decreases and then rises with increased trade openness, meaning that a sufficient level of trade openness is required for green technological progress. Tighter environmental policy is also found to weaken the beneficial effect of trade openness on green technological progress, implying that lax environmental policy creates a better environment for more open countries to develop green technology. However, these effects vary across countries, depending on the origin and destination of trade.

Artificial intelligence, green technological progress, energy conservation, and carbon emission reduction in China: An examination based on dynamic spatial Durbin modeling

Artificial Intelligence (AI), as the core driving force of industrial and technological innovation, has brought technological advances that profoundly affect energy conservation and carbon emission reduction in China. This study constructs a dynamic spatial Durbin model to empirically analyze AI's mechanism path using Chinese inter-provincial panel data as a sample. The findings show the following: (1) Spatial and temporal variations exist in AI development levels and energy conservation and carbon emission reduction. (2) AI has a significant negative impact on energy consumption efficiency and a significant negative spatial spillover effect on carbon emission efficiency, and the effects of AI development level on energy conservation and carbon emission reduction are mainly dominated short term. (3) Green technological progress on both the input and output sides has not played a determinant role in the effects of AI on energy conservation and carbon emission reduction. (4) Given the moderating effect of the degree of factor market development, the improvement of green technological advances can play a positive role in the impact of AI on energy and carbon reduction. These findings suggest the need to provide policy support for energy conservation and carbon emission reduction by improving the spatial and regional linkage mechanism to narrow spatial and temporal differences in development levels, formulating AI policies addressing regional heterogeneity to promote the full transformation of AI's short-term effects into long-term effects as well as emphasizing the negative role of green technological advances and accelerating the transformation of green technological achievements, among other measures.

Carbon emission efficiency in the age of digital economy: New insights on green technology progress and industrial structure distortion

AbstractThere is a dual impact of the digital economy (DE) on carbon emission efficiency (CE). An in‐depth study of the impact of the DE on “local‐adjacent” CE at different spatial scales can support the debate on whether the digital economy is empowerment or impairment. This study reassesses the DE at the urban level from a micro‐perspective by cross‐referencing the data of listed companies with the information obtained from city yearbooks. Considering the potential spatial correlation of the digital economy, we use the spatial Durbin model to examine 281 cities from 2011 to 2019 and study the influence of the DE on “local‐adjacent” CE. We further explain the pathways of this influence from the perspectives of green technological progress and industrial structural distortion. The study findings indicate that the impact of DE on local CE exhibits a “U”‐shaped pattern overall while its impact on neighboring CE shows an inverted “U”‐shaped pattern. These conclusions are still valid even after conducting a series of robustness tests, including spatial difference‐in‐differences and spatial replacement matrix. Further research reveals that the impact of DE on neighboring CE weakens with increasing spatial distance. The promoting effect of DE on neighboring CE peaks at 250 km, and the inverted “U”‐shaped pattern holds within a range of 300 km. In the initial stages, green technological progress can mask the negative impact of DE on local CE while simultaneously improving CE within a 250‐km range of neighboring areas. However, in the later stages, DE exacerbates the distortion of neighboring industrial structures, thereby reducing neighboring CE. The lack of synergy in the scale and growth rate of DE development in different regions significantly reduces the enhancement effect of the digital economy on CE.

Green technology advancement, energy input share and carbon emission trend studies

In order to study the theoretical mechanism of the impact of green technology progress on carbon emissions, this article constructs a theoretical mechanism of the impact of green technology progress on carbon emission growth. Explore the conditions for achieving carbon peak and carbon reduction. Based on the Cobb Douglas production function, construct a three sector model that includes capital, labor, and energy. Empirical methods were used to analyze the quantitative impact of green technology progress on carbon emission growth and the moderating effect of energy input share. This study mainly used provincial panel data from 1995 to 2020. Calculate carbon dioxide emissions based on energy consumption and carbon dioxide emission coefficients of various energy sources in different regions. Using the perpetual inventory method to calculate capital growth rate, green computing progress rate, etc., to provide data support for the green technology carbon reduction model. Empirical analysis of the impact of green technology progress on carbon emissions using the FGLS panel model. Theoretical and empirical analyses show that green technological progress promotes an increase in the carbon emission growth rate through the scale effect, with an impact coefficient of 0.607; it promotes a decrease in the carbon emission growth rate through the technological effect, with an impact coefficient of − 0.667; the combined effect promotes a decrease in growth rate of carbon emissions, with an impact coefficient of − 0.06. The share of energy inputs has a positive regulating effect on the scale effect.