Driving patterns of industrial green transformation: A multiple regions case learning from China

How does green credit affect industrial green transformation? Mechanism discussion and empirical test

Sustainable development has become a strategic consensus in response to the global environmental problems. Green credit is a major policy innovation that promotes the transformation of economic development mode and industrial green transformation (IGT). Using provincial panel data from 2005 to 2020, we investigate the effect of green credit on IGT using a systematic GMM model, a dynamic threshold model, as well as the possible nonlinear relationship. Benchmark regression results show that green credit can encourage industrial green transformation. In addition, there is a single green credit threshold with a value of 0.2612. The trend is "negative to positive". According to the moderating effect results, environmental regulation moderates in a negative manner. As environmental regulations become more stringent, the contribution of green credit to IGT will diminish. The intermediary mechanism test demonstrates that green technology innovation and marketization level play a partial intermediary role. Heterogeneity testing confirms that the function of green credit in promoting industrial green transformation is more significant in regions with a higher level of green finance development and a lower degree of government intervention. Therefore, the government should encourage financial institutions to provide green credit products and services to meet the financing needs of different green projects, thereby facilitating the industrial green transformation.

Does green technology transformation alleviate corporate financial constraints? Evidence from Chinese listed firms

Green technology transformation is crucial for China to achieve its carbon peak and carbon neutrality goals. We use green transformation keywords extracted from the annual reports of listed firms to construct a green technology transformation intensity index for enterprises and investigate the impact of green technology transformation on corporate financial constraints. Our findings indicate that green technology transformation significantly mitigates corporate financial constraints, with green subsidies and debt financing as crucial mechanisms. Moreover, this effect is particularly pronounced in high-carbon-intensity industries, firms with fewer political connections, and firms affected by the carbon trading pilot. Additionally, digital and green transformations have a synergistic effect on alleviating corporate financial constraints. Therefore, we should promote the green technology transformation of enterprises and guide green finance to serve the real economy, effectively solve the financing dilemma of green enterprises, and provide strong green kinetic energy for sustainable development.

Can the application of artificial intelligence in industry cut China's industrial carbon intensity?

As an emerging technology, industrial intelligence focus on the integration of artificial intelligence and production, which creates a new access to achieve the goal of carbon emissions reduction. Using data on provincial panel data from 2006 to 2019 in China, we empirically analyze the impact and spatial effects of industrial intelligence on industrial carbon intensity from multiple dimensions. Results show an inverse proportionality between industrial intelligence and industrial carbon intensity, and the mechanism is to promote green technology innovation. Our results remain robust after accounting for endogenous issues. Viewed from spatial effect, industrial intelligence can inhibit not only the industrial carbon intensity of the region but also the surrounding areas. More strikingly, the impact of industrial intelligence in the eastern region is more obvious than that in the central and western regions. This paper effectively complements the research on the influencing factors of industrial carbon intensity and provides a reliable empirical basis for industrial intelligence to reduce industrial carbon intensity, as well as a policy reference for the green development of the industrial sector.

Green finance, environmental pollution and high-quality economic development-a study based on China's provincial panel data

Under the new normal, green finance is inevitably linked to high-quality economic development in China. Based on 30 province panel data sets from China from 2010 to 2019, this research employs an innovative spatial econometric model to integrate green finance, environmental pollution and high-quality economic development into a unified empirical analysis framework. Regional green finance and high-quality economic development have spatial spillover effects in China, according to spatial auto-regressive and spatial error model tests, with the eastern region leading, the central region running in parallel and the western region chasing, because of a strong moderating effect in the eastern region. Green finance contributes greatly to high-quality economic development, but increased environmental pollution impedes high-quality economic development. Green financing can help to mitigate the detrimental effects of pollution on high-quality economic development. According to the mechanism of action analysis, green finance reduces pollution by modifying the industrial structure and boosting scientific and technological growth. Finally, the green finance threshold test demonstrates a nonlinear impact on economic quality development after passing a specified threshold value and has a strong threshold characteristic. This research has policy implications since it improves understanding of the dynamics of high-quality economic development as well as the benefits, mechanisms and heterogeneity of green finance in reducing pollution and empowering high-quality economic development.

Green transition in manufacturing: Dynamics and simulation

Under the dual background of global industrial value chain and low-carbon emission reduction, the green transformation and upgrading of the manufacturing industry is an important way to promote production and promote sustainable economic development. Considering that the green transformation of the manufacturing industry is a typical complex adaptation system, based on the intrinsic relationship between the dynamic theory and the green transformation of the manufacturing industry, this paper takes the endogenous variable of the transformation of manufacturing enterprises as the entry point, simulates the transformation of new and old dynamic energy of green transformation, and explores the mechanism of green transformation and upgrading of manufacturing industry and the conversion process. According to the model, it is concluded that the green transformation of manufacturing enterprises is the result of the multi-stage transformation of enterprises. In this process, the change inertia overcomes old dynamic inertia and promotes the new dynamic to gradually replace the old dynamic. At the end of the article, specific suggestions are given to promote the green transformation of manufacturing enterprises from the aspects of ideology, policy support, digital empowerment, financial service guarantee system and communication and cooperation.

Coordination of IFDI and OFDI, government innovation support, and China's industrial green transformation

Accelerating industrial green transformation (IGT) is the intrinsic requirement of realizing low-carbon and green economic development. Inward Foreign Direct Investment (IFDI) and Outward Foreign Direct Investment (OFDI) are the main channels of international technology spillover. Whether the coordination of IFDI and OFDI (CIO) can promote IGT and what role the Chinese government's innovation support plays need to be investigated. Using China's provincial panel data from 2003 to 2019, this paper discusses the impact of CIO on IGT and the moderating effect of government's innovation support. It is found that the CIO can significantly promote the IGT. Government providing R&D funds directly can enhance the promotion of CIO to IGT. However, government releasing innovation signal indirectly shows a significant negative impact on the promotion of CIO to IGT. In addition, the impact of CIO on IGT and the moderating effect of government's innovation support are heterogeneous significantly among different regions. This study not only helps to clarify the relationship between CIO and IGT but also provides enlightenment for government to scientifically formulate innovation policies to achieve green economic development.

Measurement and Spatial-Temporal Characteristics of Inclusive Green Growth in China

In the context of the widely recognized concept of inclusive green growth, it is of great practical significance to study the measurement of inclusive green growth, its temporal characteristics and its spatial heterogeneity. However, it should be noted that most existing studies only consider the situation of China when constructing inclusive green growth indices, and such studies lack international comparators. The index selection dimension is relatively single, and the temporal characteristics and spatial heterogeneity are rarely studied simultaneously. In this study, a spatial correlation analysis method is introduced, and the time series characteristics and spatial heterogeneity of inclusive green growth are deeply analyzed by means of a Moran’ I and LISA agglomeration diagram. The results show that: (1) Economic development, fair opportunity, green production and consumption and ecological environment protection are important factors affecting the level of inclusive green growth, but their development is not balanced; (2) Inclusive green growth has obvious time series characteristics, but there are great differences between provinces and regions; (3) The inclusive green growth has significant spatial heterogeneity. From 2010 to 2019, the inclusive green growth level has a dynamic evolution process. Moran’s I Index Global Spatial Test results show that inclusive green growth has obvious spatial autocorrelation, that is, it has great spatial differences. Local spatial test results also show that the inclusive green growth in China has obvious spatial aggregation characteristics. Therefore, it is important to coordinate the development of inclusive green growth between provinces and regions and improve the overall level of inclusive green growth in the future.

What inhibits regional inclusive green growth? Empirical evidence from China

The diversity of locations, environment, and resource elements among different regions leads to the regional imbalance of inclusive green growth (IGG), especially in those developing countries like China. A core issue for achieving the coordination of regional IGG is to identify what influence factors with what extent to inhibit IGG levels of different regions. In this paper, a comprehensive IGG indicator system is designed based on the IGG connotation from four dimensions of economic development, social opportunity equity, green production and consumption, and ecological environment protection. An improved TODIM method is proposed to measure the regional IGG level and further reveal the inhibition effects of various influence factors on regional IGG. The results exemplified by China's 30 provinces during 2008-2018 show that China's eastern provinces possess more superior IGG levels, while the catch-up effect of IGG in central and western provinces is significant. The lower economic output, larger income gap, and weaker green production and consumption restrict the IGG of most western provinces. The higher economic and population agglomerations in eastern and central provinces challenge the ecological resource endowment and environment governance, which inhibits their IGG development. The inhibition effects of social opportunity equity involving employment, education, medical treatment, social security, and infrastructure on IGG levels do not reflect obvious regional agglomeration.

Evaluation of Industrial Green Transformation in the Process of Urbanization: Regional Difference Analysis in China

Population mobility and the expansion of construction land in industrial development promote urbanization, and the sustainable development of cities creates requirements for the green transformation of industry. This paper uses the directional distance function (DDF) and the global Malmquist–Luenberger (GML) index method—including urbanization factors—to calculate the industrial green transformation (IGT) index in China, and to analyze its evolution and spatial distribution characteristics. The results show that ignoring the urbanization factor will lead to the overestimation of the IGT. The growth of the index has multiple stages, and it shows a decreasing order in the middle, east and west regions. Overall, the distribution of the index spreads out over time, and the gap widens. In terms of spatial correlation, high values are mostly concentrated in the eastern region and low values are mostly concentrated in the western region, and the gap in the eastern region is larger than those in the central and western regions. Therefore, in addition to the transformation of industrial production into a circular economy model, it is also necessary to promote the circulation of technical talent between regions in the development of urbanization, reducing the unbalanced development between regions and comprehensively promoting the green transformation of industry.

Research on Regional Differences and Influencing Factors of Chinese Industrial Green Technology Innovation Efficiency Based on Dagum Gini Coefficient Decomposition

Industrial green technology innovation has become an important content in achieving high-quality economic growth and comprehensively practicing the new development concept in the new era. This paper measures the efficiency of industrial green technology innovation and regional differences based on Chinese provincial panel data from 2005 to 2018, using a combination of the super efficiency slacks-based measure (SBM) model for considering undesirable outputs and the Dagum Gini coefficient method, and discusses and analyses the factors influencing industrial green technology innovation efficiency by constructing a spatial econometric model. The results show that: firstly, industrial green technology innovation efficiency in China shows a relatively stable development trend, going through three stages: “stationary period”, “recession period” and “growth period”. However, the efficiency gap between different regions is obvious, specifically in the eastern > central > western regions of China, and the industrial green technology efficiency innovation in the central and western regions is lower than the national average. Secondly, regional differences in the efficiency of industrial green technology innovation in China are evident but tend to narrow overall, with the main reason for the overall difference being regional differences. In terms of intra-regional variation, variation within the eastern region is relatively stable, variation within the central region is relatively low and shows an inverted ‘U’ shaped trend, and variation within the western region is high and shows a fluctuating downward trend. Thirdly, the firm size, government support, openness to the outside world, environmental regulations and education levels contribute to the efficiency of industrial green technology innovation. In addition, the industrial structure hinders the efficiency of industrial green technology innovation, and each influencing factor has different degrees of spatial spillover effects.

Can Green Finance Development Reduce Carbon Emissions? Empirical Evidence from 30 Chinese Provinces

Dealing with the relationship between environment and economic development is the core issue of China’s sustainable development. At present, China’s economic transformation is urgent, and green finance is being widely concerned. This paper measured the development level of China’s green finance from the perspective of green credit, green securities, green investment, and green insurance. Then, it used a spatial dynamic panel model to empirically test the mechanism of the impact of green finance on carbon emissions with panel data of 30 Chinese provinces from 2005 to 2018. The following can be seen from the results: (1) The development of green finance contributes to carbon emission reduction. (2) The spatial spillover effect of green finance is significant. Specifically, the development of green finance can not only reduce the carbon emissions of the local region but also inhibit that of adjacent areas. (3) The development of green finance indirectly leads to a decrease in carbon emissions by reducing financing constraints and boosting green technology innovation. In order to stimulate the carbon emission reduction effect of green finance to a greater extent, we should further support the development of green finance, reduce the financing constraints of energy-saving and environmental-protection enterprises, and encourage the research and development of green innovative technologies.

Perspectives and Problems of Using Renewable Energy Sources and Implementation of Local “Green” Initiatives: A Regional Assessment

Environmental pollution, energy supply and security of supply have become major issues across the world due to climate change, limited energy sources, energy price volatility and energy supply constraints. Energy availability, energy efficiency and the replacement of fossil fuels by renewable energy sources are key factors in the global development of sustainable energy. In many countries with limited fossil fuel resources, the sustainable development of renewable energy sources is an important tool in reducing dependence on imported fuels. Some alternative energy sources, such as wind, solar, tidal and hydropower, seem almost inexhaustible. With the exception of tidal energy, all of these sources have been used extensively and for a long time. This article examines the improvement of energy security and the government’s actions to promote the use of renewable energy sources, focusing on increasing energy efficiency and reducing energy intensity and dependence on energy imports in Lithuania. In addition, the article provides the state of renewable energy sources in Lithuania, aspects of sustainability and future development directions and perspectives.

Optimal path for overcoming barriers in developing China's wind energy industry

Developing the wind energy industry (WEI) has been a long-term strategy in China for responding to the energy crisis and greenhouse gas emissions. However, China's WEI faces various barriers despite its favorable prospects. This paper aims to propose a path analysis approach for exploring the best methods and timing for overcoming diverse barriers in developing WEI systematically, especially in terms of revealing in which phases these barriers should take priority. A multidimensional barrier set categorized by institutional, economic and financial, social, technical, and market factors is identified via the integration of a literature review and empirical interviews. A path analysis approach based on the grey group DEMATEL-NK model is constructed, where the causalities and intensities among barriers are extracted to design a path simulation algorithm with heuristics. The optimal path for overcoming barriers in developing the WEI is generated through a simulation of the search and optimization process used to climb to the fitness landscape peak. The results show that the different barriers to completing the legal and regulatory framework should be prioritized to reach adequate financial incentives and coordination among stakeholders, and that an efficient talent cultivation system should be developed and industry-academic cooperation should be strengthened to increase technical and R&D capabilities in the short term. The optimal path presents a strategic instrument for managers to use to better develop sustainable and clean wind energy systems from the novel insights of prioritizing to overcome barriers.

Barriers to implementing the strictest environmental protection institution: a multi-stakeholder perspective from China

Increasingly severe environmental issues, especially those in developing countries such as China, drive the evolution of the environmental protection institution (EPI) to its strictest levels. However, the implementation of the strictest EPI still confronts various challenges and barriers, and the multi-stakeholder features of EPI determine these barriers are not independent of one another but rather present complex interactive relationships. This paper identifies the barriers to implementing China's EPI from four aspects of environmental legal, economic, regulatory, and public participation institutions. A variable precision rough DEMATEL approach is proposed to visualize the causal relationships and intensities among barriers from the similarities and differences in perspectives of stakeholders from the government, company, and public levels. The obtained causal interactive mechanism among barriers highlights the need to prioritize the improvement of environmental policy assessment, and the concrete measures in policies or plans should be integrated into legislation to ensure they are mutually supportive early. The non-substantive contributions achieved by China's public participation in environmental protection reveal prejudices that the public is often regarded as a supporter or spectator by both government and company groups, which makes the transparent environmental information disclosure, transfer and feedback into an effective mediation among stakeholders. Comprehensive coordination and feedback mechanisms including source prevention, process control, and severe punishment for consequences while enhancing linkages among stakeholders are put forward to overcome barriers and help implement the strictest EPI.

How does China's Western Development Strategy affect regional green economic efficiency?

Narrowing regional economic gaps and constructing an environmentally friendly society are two major objectives of China's current economic policies. Promoting green development in resource-based regions is a global issue. Focusing on China's Western Development Strategy (WDS), this study first calculates the provincial green economic efficiency (GEE) in China. The synthetic control method is adopted to evaluate the net effect of WDS on regional GEE. The transmission mechanisms are then investigated in perspective of the interregional flow of innovation factors. The results show that: (1) The GEE in coastal areas of China is generally higher than that of western China; (2) The WDS can improve the overall regional GEE but the effect decays over time and through the diversity of the regions; (3) WDS can improve regional GEE by introducing innovation factors into the western regions, further improving the regional industrial structure, urbanization, and labor quality; (4) The optimal scale of innovation factors flowing into the WDS regions is calculated. The transmission mechanisms will have a positive effect on the GEE of the western regions simultaneously only if the inflow scale of the innovation factors varies on the interval (0.347, 0.618). The paper concludes with targeted policies to promote regional green development.