Capital misallocation, technological innovation, and green development efficiency: empirical analysis based on China provincial panel data

Can green bonds empower green technology innovation of enterprises?

Green bonds, a new green financial instrument, encourage enterprises to achieve high-quality development through green technology innovation. However, a lack of research is currently being conducted into the effect of green bond issuance in China. Can green bonds effectively empower enterprises to green innovation? What is the underlying mechanism? In the context of carbon-neutral strategies, it is significant to answer these questions scientifically. This paper uses a quasi-natural experiment of the launch of the green bond market in China in 2016 to conduct empirical studies based on the panel data of 1 558 non-financial Chinese-listed enterprises from 2015 to 2020 with the multi-period difference-in-difference model. The results show that ① issuing green bonds can significantly empower enterprises' green technology innovation. The empowering effect is mainly for green utility patents rather than green invention patents. This result remains after dynamic heterogeneity analysis, placebo test, and other tests. In addition, the effect has a lag. ② Heterogeneity tests show that this empowerment effect varies across enterprises with different property rights, industries, and regions. ③ In terms of the mechanism of action, green bonds can enhance enterprises' ability to innovate green technology by increasing the proportion of long-term loans and improving their debt structure. This paper broadens the relevant literature on the economic consequences of green bonds and the influencing factors of enterprises' green technology innovation and provides policy suggestions for further improving the analysis of green bonds.

Data-driven low-carbon transformation management for manufacturing enterprises: an eco-efficiency perspective

The low-carbon transformation of manufacturing enterprises is considered to be imperative to achieve carbon neutrality. Therefore, we propose a data-driven strategy to achieve a low-carbon transformation of manufacturing enterprises from an eco-efficiency perspective. Following the collection of input (energy, materials, equipment, R&D, and services) and output (waste and products) data from production systems of manufacturing enterprises, an ecological efficiency model of manufacturing enterprise production system was constructed from the perspective of carbon emissions, thus allowing the quantitative evaluation of the ecological efficiency of the production system. Furthermore, a "measurable, evaluable, and optimized" low-carbon transformation and upgrading method for manufacturing enterprise production system was established. Finally, through the production practice data of an enterprise from 2017 to 2021, the feasibility and effectiveness of this method were verified. The results show that this method can effectively improve the ecological efficiency of enterprises by 3.6% and reduce waste emissions by 12%. Our study provides new tools for improving the ecological efficiency of manufacturing systems, along with theoretical and methodological support to manufacturing enterprises for low-carbon transformation.

Spatiotemporal differentiation and convergence characteristics of green economic efficiency in China: from the perspective of pollution and carbon emission reduction

Accurate quantification of pollution and carbon emission reduction policies, as well as analysis of green economic efficiency (GEE), are of great significance to accelerating green economic development in China and contributing to pollution prevention and carbon peaking. Using data from 2006 to 2022, this study incorporates pollution and carbon emission reduction policies into the evaluation system, and uses a model with slacks-based measures and a directional distance function (SBM-DDF) to calculate the GEE of 30 provinces. The Dagum Gini coefficient, kernel density estimation, and spatiotemporal convergence analysis are used to analyze the spatiotemporal differentiation and convergence characteristics of GEE. The findings show that the strengths of the pollution and carbon emission reduction policies are increasing but vary greatly among the provinces. China's overall GEE has a time trend with the characteristics of "decline-fluctuation-stable." The Dagum Gini coefficient reveals the relative differences between the major regions. Both the intra-regional and inter-regional differences tend to widen over time and the latter explains most of the sources of the overall differences. Kernel density estimation shows that the absolute differences between the provinces are generally widening, whereas the absolute differences between the provinces in the central and western regions are smaller than those in the eastern region. No obvious σ convergence characteristics exist in the country overall and the three major regions, but β convergence characteristics are present in each region. The factors affecting changes in the GEE of each region are not the same. The study suggests that the China should further improve the implementation of pollution and carbon emission reduction policies, pay attention to the regional differences and convergence issues of GEE, and promote the coordinated development of green economy in different regions. This study innovatively quantifies the policies related to pollution and carbon emission reduction, providing empirical evidence for understanding the performance of pollution and carbon emission reduction policies in various regions. Furthermore, this study incorporates policies as inputs into the GEE evaluation system, reveals the spatiotemporal differentiation of GEE, thereby providing reference for green economic transformation and sustainable development.

Can heterogeneous environmental regulations improve industrial green total factor energy efficiency?

Whether heterogeneous environmental regulations in China can improve industrial green total factor energy efficiency (IGTFEE) is essential to sustainable industrial development nationwide. However, under China's fiscal decentralization system, the impact of heterogeneous environmental regulations on the IGTFEE and its underlying mechanism needs further exploration. This study incorporates capital misallocation and local government competition into the research framework and systematically investigates the mechanisms and effects of environmental regulations affecting the IGTFEE under China's fiscal decentralization system. Based on provincial panel data from 2007 to 2020, this study measured the IGTFEE using the Super-SBM model with undesirable outputs. Based on efficiency, this study uses a bidirectional fixed-effects model, an intermediary effect model, and a spatial Durbin model for empirical testing. The results show that the effect of command-and-control environmental regulation on the IGTFEE presents an inverted U shape, while the effect of market-incentive environmental regulation on the IGTFEE presents a U shape. Conversely, the effect of command-and-control environmental regulation on capital misallocation presents a U shape, while the effect of market-incentive environmental regulation on capital misallocation presents an inverted U shape. Capital misallocation is the mediating variable of heterogeneous environmental regulations affecting IGTFEE, but heterogeneous environmental regulations do not affect the IGTFEE through the same mechanisms. The spatial spillover effects of command-and-control and market-incentive environmental regulations on IGTFEE present a U shape. Local governments adopt a differentiation strategy for command-and-control environmental regulation and a simulation strategy for market-incentive environmental regulation. Environmental regulations have spillover effects on the IGTFEE under different competitive strategies, but only the imitation strategy, characterized by the race-to-the-top, can promote local and neighboring IGTFEE. Therefore, we propose the following recommendations: the central government should flexibly adjust the intensity of environmental regulations to maximize the capital allocation effect, set diversified performance assessment indicators to motivate local governments into the healthy competition and reform the modern fiscal system to correct distortions in the behavior of local governments.

Pathways to carbon neutrality: how do government corruption and resource misallocation affect carbon emissions?

The government corruption and resource misallocation are important factors that inhibit economic transformation and environmental governance. Using a study sample of 30 provinces in China, this study employs the spatial econometric methods and threshold model to investigate the relationship between regional corruption, resource misallocation, and CO2 emission. The results show that there is a clear spatial dependence and correlation of CO2 emissions. Government corruption is a neglected contributor to carbon emissions, and this promotion effects are attributed to a promotion in resource misallocation. Moreover, the CO2 emissions are significantly promoted by local labor misallocation and capital misallocation, and the increasing effect is more pronounced in areas with high corruption. For spatial spillover effects, there is also no evidence that local CO2 emissions are significantly promoted by capital misallocation of surrounding areas. Additionally, the promoting effect of corruption on CO2 emissions is more pronounced in regions with weak environmental regulation, low marketization process, and the central and western of China. This work elucidates the mechanism of the impact of corruption on environmental pollution from the perspective of resource allocation, and provides an important reference for the effective management of environmental pollution.

How does digital technology empower urban green development efficiency in the Beijing-Tianjin-Hebei region-mechanism analysis and spatial effects

Under the strategy of "Digital China" and "Sustainable Development," the synergistic development of digital economy and green economy has become a crucial topic. Based on the panel data of 13 cities in the Beijing-Tianjin-Hebei (BTH) region from 2011 to 2019, this study investigates the direct effect, intrinsic mechanism, and spatial spillover effect of digital technology development (DTD) on urban green development efficiency (GDE). The empirical results show that (1) DTD significantly improves urban GDE in the BTH region, and it passes the endogeneity test, (2) DTD can enhance urban GDE by improving the environmental regulation intensity and technological innovation level in the BTH region; however, the industrial structure optimization weakens the promotion effect of DTD on urban GDE in the BTH region, which shows a "masking effect," (3) the kernel density estimation method and ArcGIS technology reveal the existence of "digital divide" and GDE differences among cities in the BTH region. Moreover, the spatial distribution pattern of DTD gradually forms "H-H" and "L-L" clusters in the BTH region, and (4) DTD also increases the GDE of neighboring cities through spatial spillover effects in the BTH region, and it passes the robustness test of replacing the spatial weight matrix. This study is important for the BTH region to simultaneously solve economic development and environmental problems in the context of digitalization.

The effect of mandatory environmental regulation on green development efficiency: evidence from China

The existing literature finds that mandatory environmental regulation (MER) can significantly reduce environmental pollution. However, much less is known about how the implementation of MER affects green development efficiency (GDE). Based on the Air Pollution Control Action Plan which was enforced in 2013 in China's most developed regions as an exogenous shock, we find that first, MER has a significant negative effect on the improvement of GDE by reducing regional scale efficiency. Second, MER mainly reduces the GDE of cities with stronger regulation intensities and with larger economic volumes. Third, MER also has a negative impact on regional green total factor productivity by changing technical progress. We suggest that when implementing MER, governments should enhance regional and global cooperation, promote green technology, and use comprehensive policy tools to stimulate firms' green innovation.

China's industrial green development and its influencing factors under the background of carbon neutrality

To measure and analyze the evolution characteristics and influencing factors of China's industrial green development level is of great significance in achieving carbon neutrality goal. Based on the panel data from 2000 to 2018 of 30 provinces in China, this research uses the super slack-based measuring model and the Malmquist-Luenberger index to calculates China's industrial green total factor productivity and to describe its evolution characteristics using the kernel density function and moreover uses the Spatial Durbin model and the partial differential method to explores its main influencing factors. This study finds that China's overall industrial green development level is not high but shows an upward trend year by year; carbon emissions, fiscal decentralization, and urbanization are not conducive to improving the national industrial green development level, whereas economic development, foreign direct investment, industrial structure, and technological progress are positive contributors. At the same time, the level of economic development and technological progress have significant direct and spatial spillover effect. Our findings also provide some policy implications for improving China's industrial green development.

Green Development Performance Evaluation Based on Dual Perspectives of Level and Efficiency: A Case Study of the Yangtze River Economic Belt, China

In the context of continuing to promote the construction of an ecological civilization, it is of great significance to explore green development performance. However, most of the literature is based on a single perspective of level or efficiency, lacking a comprehensive examination of both. It is not scientific to explore how to promote green development only from a single perspective, which may be a new advancement by breaking the conventional thinking focusing only on level or efficiency. On this basis, we first established evaluation index systems of green development performance based on a theoretical framework. Furthermore, green development performance was measured with the entropy weight technique for order preference by similarity to ideal solution (TOPSIS) and super-EBM models, and finally, we analyzed the spatial and temporal evolution patterns of green development performance using the ESDA method and examined its influencing factors with a geographic detector (GD) and econometric models. The main results were as follows: (1) The trend of the green development level in the Yangtze River Economic Belt from 2004 to 2017 had an inverted “N” shape, while the overall average green development efficiency continuously increased. (2) In terms of spatial and temporal patterns, both the green development level and green development efficiency showed “high in the east and low in the west” spatial divergence characteristics. In terms of the spatial and temporal evolution pattern of the green development level, the L-L clusters were mainly distributed in the western region. However, for green development efficiency, the L-L clusters were mostly distributed around the H-H clusters. (3) The results of the influencing factor analysis indicated that industrial structure and people’s welfare are still important factors of the green development level. The improvement of green development efficiency was mainly driven by economic development, and the inhibiting effect of energy consumption is significant. In addition, the effect of opening up has not yet changed from a “pollution paradise” to a “pollution halo”.

The impact of environmental regulation on China’s industrial green development and its heterogeneity

The research analyzes the impact of environmental regulation on industrial green development using panel data from 30 provinces in China from 2006 to 2018. We employ the Super-slack-based measuring (SBM) model to measure the level of domestic industrial green development and use the ordinary panel model, the panel threshold model, and the spatial panel model for empirical estimation. The results reveal that the environmental regulation index plays a significant role in promoting such development. Environmental regulation index, command-and-control environmental regulation, market-incentive environmental regulation, and public-participation environmental regulation all have only a single threshold of technological progress and fiscal decentralization. Further analysis shows that China’s industrial green development presents obvious spatial agglomeration characteristics, and there is a significantly positive spatial correlation between different environmental regulation indicators and industrial green development. Our findings provide useful policy recommendations for promoting industrial green development in China.

Causes and Evolution Characteristics of Green Innovation Efficiency Loss: The Perspective of Factor Mismatch under Local Government Competition

The objective of this paper is to measure the efficiency loss of green innovation caused by local government competition and explore its causes and evolution characteristics. Based on the equimarginal principles such as the deviation of the allocation of green innovation output factors, this paper uses the panel data of China’s provinces (excluding Tibet, Hong Kong, Macao and Taiwan) from 2000 to 2020 and employs the spatial panel measurement model and the Kernel density estimation. The study finds that first, local government competition causes the mismatch of local innovation factors not only locally but also in neighboring regions. Second, the mismatch of innovative talents and capital caused by local government competition lowers the green innovation efficiency. Third, the shortage of innovative talents caused by local government competition is the main reason for the loss of green innovation efficiency in Beijing, Tianjin, and Shanghai. Fourth, the degree of efficiency loss of green innovation at the provincial level in China is heterogeneous in government competition strategies, and the loss due to tax competition is the most significant. Fifth, although the loss of green innovation efficiency generally decreases yearly, in the future, the institutional competition will still hinder the improvement of green innovation efficiency in the eastern, central and western regions of China. Our policy suggestions include promoting regional cooperation and cultivating innovative talents to further improve the efficiency of green innovation.

Human Health, Environmental Quality and Governance Quality: Novel Findings and Implications From Human Health Perspective

Human health and wellbeing are intimately linked to the state of the environment. The current study emphasizes the role of environmental quality, government policies, and human health. This paper provides a detailed literature review of existing findings regarding our key variables of interest. The results argue that the implications of poor government policies and environmental pollution for rising economic development have led to poor environmental quality and health issues for humans. Based on earlier investigations, the present study reviewed the state-of-the-art review and determined innovative insights for outdoor and indoor environment difficulties. This study provides a detailed review of human health, environmental quality, and governance quality. In addition, the study conducts an empirical analysis using the annual data of low-income countries from 1996 to 2020. Government actions and health systems must be modified immediately to address these rising concerns successfully. The report offers policy recommendations for addressing health, governance, and environmental change mitigation issues, all of which are directly or indirectly related to the study. This article presents an overview of environmental change's health impacts and explores how health hazards may be reduced or eliminated through effective adaptation strategies.