The impact and mechanism of vertical fiscal imbalance on green development efficiency: An empirical analysis based on city-level samples in China

Green development has become a prevalent theme due to the tightening of resource constraints. This article explores the institutional factors that may contribute to the slow pace of green modernization in prefecture-level cities during the new era through the examination of the central-local fiscal relationship that local governments in China must navigate. A two-way fixed-effects model is used to theoretically analyze the impact of the increase in vertical fiscal imbalance (VFI) on green development efficiency (GDE) based statistical data from 270 cities between 2007 and 2020. The research shows that the increase in VFI has an N-shaped nonlinear effect on GDE, which is supported by various robustness and endogeneity tests. The greening process is significantly affected by the fluctuating dynamics of China's central-local fiscal relations. The VFI values of 0.2801 and 0.8892 are important transition points along the GDE curve, representing its peak and valley, respectively. At the end of the study period, only 12.13% of the studied cities experienced a higher quality facilitation effect. Streamlining the relationship between central and local finance is urgently needed for the widespread implementation of greening. The stock and supply of scientific and technological personnel play crucial roles in shaping the impact of the central-local fiscal relationship on green modernization. Specifically, VFI has an inverted U-shaped nonlinear impact on the level of scientific and technological human resources (S&TL). The inflection point occurs at VFI = 0.2710, which is close to the point of GDE. Furthermore, heterogeneity tests indicate that the institutional dividend of VFI is more pronounced in economically developed regions, eastern coastal areas, and regions with a more developed industrial structure. The study provides valuable insights for the government to promote green development. However, the lack of indicators and specific samples, as well as the reliance on limited assumptions, constrains the ability of this study to draw meaningful research conclusions. These limitations highlight the necessity for further related research in the future.

Great transition and new pattern: Agriculture and rural area green development and its coordinated relationship with economic growth in China

Agricultural and Rural Green Development (ARGD) and economic growth are major challenges prevalent in China, but also in other developing countries. A notable gap in current literature lies in the limited holistic approach to agriculture and rural areas, with scant attention being paid to the spatiotemporal evolution of ARGD and its coordination relationship with economic growth. This paper first offers a theoretical analysis of the interactive relationship between ARGD and economic growth and subsequently examines the policy implementation process in China in this regard. It observes 31 provinces in China from 1997 to 2020 to uncover the spatiotemporal evolution of Agricultural and Rural Green Development Efficiency (ARGDE). Using the coupling coordination degree (CCD) model and the local spatial autocorrelation model, this paper analyses the coordination relationship and spatial correlation between ARGDE and economic growth. The results show that ARGDE in China exhibited a phased growth trend and was greatly affected by policies during 1997-2020. The interregional ARGD produced a hierarchical effect. However, provinces with a higher ARGDE did not necessarily exhibit faster growth, leading to a differential pattern of optimization that involved continuous optimization, phased optimization, and continuous deterioration. Over a long period, ARGDE exhibited a trend of significant upward leaps or jumps. Finally, the CCD between ARGDE and economic growth improved, with a clear trend of high-high agglomeration characteristics that shifted from the eastern and northeastern provinces to the central and western ones. This suggests that promoting "quality agriculture" and "green agriculture" can have practical significance in accelerating the development of ARGD. In the future, it is vital to promote ARGD's transformation while mitigating the risk of degrading the coordinated relationship between ARGD and economic growth.

Towards sustainability: the impact of industrial synergistic agglomeration on the efficiency of regional green development

Guided by the concept related to sustainable development, we investigate the effects related to the synergistic agglomeration development of productive service and manufacturing industries on regional green development, which is also an important path for promoting the global sustainable development process and achieving carbon neutrality goals. Using the panel data of 285 prefecture-level cities in China from 2011 to 2020 as the basis of our study, we focus on the impact of industrial synergistic agglomeration on the efficiency of regional green development and the mediating influence of technological innovation. Results show that (1) industrial synergistic agglomeration positively contributes to the improvement of regional green development efficiency level and is significantly positive at the 5% level, (2) technological innovation plays a mediating role in the process of promoting regional green development efficiency through industrial synergistic agglomeration and can better realise the green development effect of industrial synergistic agglomeration, (3) results of the threshold effect test show the nonlinear effect of industrial synergistic agglomeration on regional green development efficiency with a single threshold value of 3.2397, and (4) the effect of industrial synergistic agglomeration on regional green development efficiency shows significant variability under different geographical locations, city scales, and resource endowment conditions. On the basis of these findings, we propose corresponding policy recommendations for improving the quality of inter-regional industrial synergistic agglomeration and formulating differentiated policy guidelines to help regions achieve long-term sustainable development.

The evolution and determinants of Chinese inter-provincial green development efficiency: an MCSE-DEA-Tobit-based perspective

Continuous and rapid economic development has brought about excessive resource consumption and environmental pollution. Therefore, it is particularly essential to coordinate economic, resource, and environmental factors to achieve sustainable development. This paper develops a new data envelopment analysis (DEA) method that can be used for multi-level complex system evaluation (MCSE-DEA) to reveal the inter-provincial green development efficiency (GDE) in China from 2010 to 2018. Moreover, the Tobit model is applied to explore the influencing factors of GDE. We found that (i) the MCSE-DEA model tends to have lower efficiency scores than the traditional P-DEA (panel data envelopment analysis) model, and the top three provinces are Shanghai, Tianjin, and Fujian; (ii) the efficiency shows an increasing trend during the whole study period. The southeast region and the Middle Yangtze River region have the highest efficiency values, reaching 1.09, while the northwest region ranks last with an average efficiency value of 0.66. Shanghai performs the best, while Ningxia performs the worst, with efficiency values of 1.43 and 0.58, respectively; (iii) the provinces with lower efficiency values mainly come from economically underdeveloped remote regions, which can be attributed to issues of water consumption (WC) and energy consumption (EC). Moreover, there are much room for improvement in solid waste emissions (SW) and soot and industrial dust emissions (SD); (iv) the environmental investment, R&D investment, and economic development level can significantly improve GDE, while industrial structure, urbanization level, and energy consumption have inhibiting effects.

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 dynamic change trends and internal driving factors of green development efficiency: robust evidence from resource-based Yellow River Basin cities

Promoting the green development of resource-based cities is an essential way to achieve sustainable regional economic development. Based on 2009-2019 panel data of the Yellow River Basin cities, this study adopts the super-directional distance function model to measure the green development efficiency of these selected cities. Furthermore, based on the Malmquist-Luenberger index, this paper focuses on the dynamic change trend of green development efficiency and internal driving factors. Furthermore, the Tobit model is used to specifically explore the influencing factors affecting the green development of cities. The findings suggested that the green development efficiency of selected cities falls in the middle to high range and that the efficiency varies among all cities in the Yellow River Basin. Likewise, technical efficiency improvements and technological progress drive development efficiency, and the former contributes more to green development. However, financial development, energy structure adjustments, and environmental regulation can strongly contribute to the green development of cities, and each influencing factor has obvious temporal and regional differences. This paper proposes appropriate policy suggestions to promote the coordinated development of the economic development and environmental protection of the Yellow River Basin.

Income inequality, carbon emissions, and green development efficiency

Income inequality affects not only social well-being, health, and carbon emissions but also the strategy for green development in China. Based on the panel data of 205 cities in China from 2010 to 2020, a panel model with partial linear functional coefficient is used to analyze and test the relationship between income inequality, carbon emissions, and green development efficiency under different regional economic development levels. The empirical results show that the impact of income inequality on carbon emissions and green development efficiency is significant. The worsening of income inequality could aggravate carbon emissions, but the effect of income inequality on carbon emissions shows an increase-decrease-flattening with the continuous improvement of regional economic development. In terms of affecting the green development efficiency, the effect of income inequality on the efficiency of green development presents an inverted U shape. However, the number of cities where income inequality has an inhibitory effect on carbon emissions and green development efficiency has increased over time, and the impact of income inequality in a few cities on green development efficiency is not significant. These findings provide new insights into the understanding of shared prosperity and the strategy of carbon peaking and carbon neutralization in China.

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.

The impact of digital inclusive finance on provincial green development efficiency: empirical evidence from China

Green development is inseparable from financial support. The impact of digital inclusive finance (DIF), an emerging financial format, on the green development efficiency (GDE) needs to be studied. Using the panel data of the Provincial Digital Financial Inclusion Index from 2011 to 2019, this paper examines the impact of DIF and its coverage breadth (CB), usage depth (UD), and digitalization level (DL) on GDE, and analyzes the regional heterogeneity of the impact of DIF on GDE. The research also explores the mechanism by which DIF affects the efficiency of provincial green development, including the moderating role of environmental regulation (ER) and the mediating role of industrial structure upgrade (ISU). The results show that DIF, UD, and DL can significantly improve provincial GDE, and the effect of coverage breadth is not obvious. From a regional perspective, DIF can promote GDE in the eastern and central regions, whereas it has no obvious effect on the western region. Moreover, ER has played a moderation role in the process of DIF affecting GDE. ISU has played a partial mediation role in the process of DIF affecting GDE. The research conclusions can provide relevant suggestions for the green development of China's provinces.

The impact of land price distortion on green development efficiency: mechanism discussion and empirical test

Based on the panel data of 30 Chinese provinces, the Cobb-Douglas production function and GML index were constructed to measure the degree of land price distortion and green development efficiency, respectively, in China, and the System Generalised Method of Moments model was employed to explore the relationship between land price distortion and green development efficiency, and a mediating effect model was further constructed to analyse the transmission mechanism. The results show that, first, land price in China is characterised by a negative distortion, but the degree of negative distortion tends to decrease after 2010. Second, land price distortion significantly inhibits the improvement of green development efficiency; this conclusion still holds after a series of robustness tests, and land price distortion significantly promotes the progress of green technology, while significantly inhibiting the improvement of green technology efficiency. Third, the results of the mediating effect show that the inhibiting effect of land price distortion on green development efficiency is mainly achieved through three channels: house price, industrial structure and infrastructure. Finally, policy recommendations for green sustainable development are put forward from the aspects of land supply structure adjustment and so on.

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

The study aims to analyze the impacts of capital misallocation and technological innovation on green development efficiency in China by using the panel data from 2000 to 2018. We employ the Super-SBM model to evaluate green development efficiency and use the system generalized method of moments (GMM) for empirical estimation. The results suggest that capital misallocation has a significant inhibitory effect on green development efficiency. Moreover, capital misallocation restrains technological innovation, which plays an important role in improving green development efficiency. Further research on the effect of regional heterogeneity indicates that the negative impact of capital misallocation on green development efficiency is more significant in the central and western regions, while the effect is not significant in the eastern region. Our findings provide useful policy implications for improving green development efficiency in China.

Will green finance promote green development: based on the threshold effect of R&D investment

Deeply understanding the driving effect of green finance on green development is of great significance to promote economic transformation and realize the long-term green development. This paper uses the entropy method and undesirable-SE-SBM model to measure provincial green finance and green development efficiency respectively from 2008 to 2018. And based on the above, the panel threshold model is constructed to discuss the nonlinear relationship between green finance and green development efficiency from the first empirical verification. The results show that ① the impact of green finance on green development has a significant single threshold effect, only when R&D investment crosses 2.810 can green finance significantly promote green development efficiency, and before that, it will suppress green development efficiency. ②At present, a few provinces in China have crossed the threshold value of R&D investment, only including Beijing, Tianjin, and Shanghai, while the R&D investment of Jiangsu, Zhejiang, Shandong, and Guangdong gradually approaches the threshold value. Therefore, improving the construction of the green financial system, correctly guiding the direction of green capital investment, and strengthening the supervision of environmental information disclosure are important.

Does manufacturing agglomeration promote or hinder green development efficiency? Evidence from Yangtze River Economic Belt, China

Sustainable development can be mainly achieved by promoting the green transformation and development of the world economy and by improving the efficiency of regional green development, which often receive extensive attention from the academia. This paper uses a spatial econometric model to estimate the impact of manufacturing agglomeration on green development efficiency based on the panel data of China's Yangtze River Economic Belt (YREB). The results show an overall large gap of green development efficiency between regions in the Yangtze River Economic Zone, mostly due to the extremely uneven development of green development efficiency in the upper reaches. Opposite to the middle and lower reaches, manufacturing agglomeration in the upper reaches of the YREB improves green development efficiency. Manufacturing agglomeration is conducive to the improvement of green development efficiency in adjacent areas. Nonetheless, it may hinder green development efficiency by inhibiting green technological innovation. This paper provides empirical evidence and policy implications for applying manufacturing agglomeration to promote green development efficiency in accordance with local conditions.

How industrial convergence affects regional green development efficiency: A spatial conditional process analysis

Industrial convergence is a key means to transform the economic mode. Taking the convergence of manufacturing and producer services in China as the research object, this study explored how industrial convergence affects regional green development efficiency (GDE). First, a coupling evaluation system was established to measure industrial convergence degree, and the directional distance function-based slacks-based measure was combined with the global Malmquist-Luenberger index to measure GDE. Second, we employed spatial econometric models to analyze the relationship between industrial convergence and GDE. Then, using the spatial conditional process analysis, a unified framework of green innovation, investment structure, and energy intensity was constructed to investigate the transmission mechanism involved. The results showed that: (1) Regional GDE and green innovation had a spatial dependence. (2) Considering the spatial correlation, industrial convergence is conductive to regional GDE. (3) Green innovation is an effective path by which industrial convergence improves regional GDE. (4) In this mediating process, the investment structure and energy intensity play a moderating role. The investment bias in high-tech industries increases the role of industrial convergence in promoting regional GDE and green innovation, while the moderating direction of energy intensity is opposite. In addition, there is a crowding-out effect in energy dependence, which hinders the effectiveness of green innovation.