Impact of digital inclusive finance on agricultural total factor productivity in Zhejiang Province from the perspective of integrated development of rural industries.

Improving agricultural total factor productivity is crucial for comprehensive rural revitalization and building a strong agricultural nation. Digital inclusive finance amalgamates the benefits of digital technology and inclusive finance, mitigating financial exclusion in agricultural production. It fosters rural revitalization and the modernization of agriculture by bolstering farmers' innovation, entrepreneurship, and agricultural technology advancements. Consequently, it significantly enhances overall agricultural total factor productivity. This study uses panel data from 2011 to 2020 to empirically investigate the impact and mechanism of digital inclusive finance on agricultural total factor productivity in Zhejiang Province, China. The research results show that digital inclusive finance significantly enhances agricultural total factor productivity in Zhejiang Province, which holds true even after a series of robustness tests. Analysis of the mechanism reveals that the integrated development of rural industries plays a crucial mediating role in empowering agricultural total factor productivity through digital inclusive finance. Furthermore, heterogeneity analysis indicates that the positive effect of digital inclusive finance on agricultural total factor productivity is more pronounced in the northeastern region of Zhejiang Province and in areas ranked in the second tier of agricultural development. Therefore, we recommend comprehensively enhancing the development of digital inclusive finance in rural areas, fostering a financial ecosystem that integrates rural industries, promoting the coordinated development of digital inclusive finance in different regions, and comprehensively improving agricultural total factor productivity.

Did regional coordinated development policy mitigate carbon emissions? Evidence from the Beijing-Tianjin-Hebei region in China.

In order to promote the balanced development of regional economy, governments at all levels are constantly introducing regional coordinated development policy (hereinafter referred to as "the Policy"). However, there is an important and interesting issue, namely, with the increasingly severe environmental problems resulted from rapid regional economic growth, what kind of impact will the Policy have on carbon emissions reduction? This is attracting wide attention from relevant stakeholders. Therefore, taking the Beijing-Tianjin-Hebei (BTH) region in China for example and through constructing the difference-in-differences (DID) model, this paper evaluated the effect of the implementation of the Policy on carbon emissions reduction. Results indicated that the Policy significantly reduced the level of regional carbon emissions in the BTH region. After carrying out a series of robustness tests, this paper still found that the above conclusions were reliable. Moreover, the mediation effect test shown that the Policy indirectly lessened carbon emissions by optimizing energy structure and reducing the intensity of carbon emissions, while the expanding of economic scale would lead to an increase in carbon emissions due to the effect from the Policy. Additionally, heterogeneity analysis revealed that the Policy had a more significant effect on carbon emissions reduction in underdeveloped regions with low environmental constraints. Overall, this paper would be beneficial to understanding the environmental effects of the Policy at the urban regional scale, thus providing an important basic theoretical basis for promoting the green and sustainable development of regional economy.

Has China's carbon market stress released? Measurement and comparison of national and pilot carbon markets' stress.

This paper constructs a novel stress measurement system of carbon market from the perspective of trading, emission reduction, and external shocks and simulates the stress indices of national and pilot carbon markets of China with the methods of functional data analysis and criteria importance through intercriteria correlation. It concludes that the overall carbon market stress is in the shape of "W" and still at a high level, with frequent fluctuations and an upward trend. In addition, the stress of Hubei, Beijing, and Shanghai carbon market fluctuates and rises, while the stress of Guangdong carbon market decreases. Moreover, carbon market stress mainly comes from trading and emission reduction. Furthermore, stress fluctuation of Guangdong and Beijing carbon market is more prone to "big waves," indicating that the two markets are sensitive to big events. Finally, the pilot carbon markets are divided into stress-driven and stress-release market and the type of which keeps change in different period.

Inter-regional economic spillover and carbon productivity embodied in trade: empirical study from the Pan-Yangtze River Delta Region.

How to promote the carbon productivity embodied in trade and regional balanced development has become the focus of attention to combat climate change and improve regional management. Taking the Pan-Yangtze River Delta region for example and based on the input-output model, this paper explored the relationship between inter-industry economic spillover and embodied carbon productivity in trade from 2007 to 2012. Results indicated that the intra-regional multiplier effect presented a slow downward trend during the studied period, while the trend in the inter-regional integration was intensifying. Moreover, the multiplier effect of the lower reaches of the Yangtze River was relatively lower than that of the middle reaches. Owing to the geographical location and industrial structure, the industries in the middle reaches of the Yangtze River were strongly correlated. In addition, the regional multiplier effect was mostly concentrated in industries with high carbon emission intensity. The economic spillovers between regions showed a growing trend from 2007 to 2012, indicating that regional economic integration was further strengthened, and the economic spillovers in the Yangtze River Delta region were significantly higher than those in the middle reaches. Furthermore, from the perspective of embodied carbon productivity in trade, most of Shanghai's carbon productivity to other regions was mostly less than 10,000 Yuan per ton, which means Shanghai had little demand for intermediate products of other regions, and inter-regional trade between Shanghai and other regions brought less total output and more environmental pollution to other regions, while Shanghai obtained more total output through trade. As embodied carbon productivity in trade in Jiangsu and Zhejiang was more than 10,000 Yuan per ton, Jiangsu and Zhejiang had played an important role in realizing the coordinated development of low carbon in the Pan-Yangtze River Delta. In particular, for Anhui and Jiangxi, embodied carbon productivity in the Yangtze River Delta region was relatively low. Therefore, in order to achieve green, coordinated, and high-quality economic development in the Pan-Yangtze River Delta region, Anhui and Jiangxi should not only strengthen regional cooperation with Shanghai, Zhejiang, and Jiangsu, but also they should avoid regional zero-sum game competition in regional climate policy. In other words, for policy-makers in the Pan-Yangtze River Delta, promoting the deep integration of industrial chain and regional coordinated development, and thus, improving carbon productivity during the regional development process, should receive more attention.

Spatiotemporal Evolution of Global Greenhouse Gas Emissions Transferring via Trade: Influencing Factors and Policy Implications.

Global climate change caused by greenhouse gas emissions (GHGs) from anthropogenic activities have already become the focus of the world. A more systematic and comprehensive analysis on the factors influencing the changes of global GHGs transferring via trade have not been fully discussed. To this end, employing spatial econometric regression models and multi-regional input-output models, this paper reveals factors influencing the GHGs transferring via trade changes in 39 major economies, so as to develop the relevant GHGs reduction policies. The results indicate that regions with the highest net outflow of GHGs transferring via trade are primarily Russia and Canada, and the adverse effects of promoting GHGs reduction on the national economy could be avoided by these regions owing to trade relations. Additionally, factors influencing the changes in GHGs transferring via trade have significant spatial autocorrelation, and population size and energy structure exert significant spatial spillover effects on the changes in the GHGs transferring via trade. On this basis, this paper suggests that one more effective way to prevent trade from the rigorous demands of environmental governance measures while preserving the economic benefits of international trade may be to facilitate cooperation between countries on GHGs mitigation. Further, we articulate more balanced environment governance policies, including conducting the sharing of advanced energy technologies and developing clearer production technologies.

How does China's green institutional environment affect renewable energy investments? The nonlinear perspective.

This paper proposes a concept of green institutional environment and constructs a green institutional environmental index through ordered logistic model. Based on this, taking 92 renewable energy listed enterprises in China from 2007 to 2016 as sample, it investigates the effect of green institutional environment on renewable energy investment with semiparametric method and further discusses how the effect works. The results show that, first, there is a nonlinear ("U-shaped") relationship between green institutional environment index and renewable energy investment. It indicates that when green institutional environment is in the initial stage of development, it cannot promote renewable energy investment, but produces an inhibitory effect; however, when the green institutional environment develops to a certain level, it will significantly promote renewable energy investment. Second, green institutional environmental index consists of green credit, government subsidies and environmental taxes. When the green credit and government subsidies develop to certain levels, they will promote renewable energy investment, however, when government subsidies exceed a certain level, it may produce a negative impact on renewable energy investment, and effect of the green institutional environment on renewable energy investment is mainly reflected through green credit; besides, increasing environmental taxes can promote renewable energy investment in sample intervals. Third, the impact of green institutional environment on renewable energy investment of large enterprises is more significant than that of medium-, small-, and micro-sized enterprises; however, the impact of government subsidies on renewable energy investment is mainly embodied in medium-, small-, and micro-sized enterprises. Fourth, during a period of high volatility (2012-2015), relationship between the green institutional environment and renewable energy investment (inverted "U-shaped") are different from that of 2007-2016. It indicates that the implementation of policies has increased the volatility of the level of the green institutional environment, which may lead to a negative impact on renewable energy investment.

Impact of green credit on industrial structure in China: theoretical mechanism and empirical analysis.

Chinese industrial structure is characterized by a large proportion of industries with high energy consumption and high pollution, such as coal, steel, and cement production, and with only a small proportion of green and environment protection industries. In order to optimize this structure, the Chinese government has clearly proposed to upgrade the industrial structure by solving funding problems in the field of environmental protection in the 13th 5-year plan. However, there are no systematic researches on how green credit affects industrial structure and what the corresponding effects are in the current theoretical circle. Therefore, by analyzing current situations of green credit and the industrial structure, this research explores mechanisms concerning the effects of green credit on the industrial structure. Furthermore, this study conducts an empirical research by using a fixed effects model constructed based on sample data from eastern, central, and western China from 2006 to 2016. The results find that (1) green credit mainly influences the industrial structure through capital and funding channels of enterprises. (2) On the whole, China's green credit has significant effects on the transformation of the industrial structure. (3) Influences of green credit in China on the industrial structure are significantly different in each region. In order to effectively upgrade the industrial structure, for the related stakeholders, some effective ways are to establish a sound legal system for green credit, raise depth of understanding on green credit, and implement green credit according to local conditions.

Spatial characteristics and driving factors of global energy-related sulfur oxides emissions transferring via international trade.

Using the logarithmic mean divisia index decomposition methods within the multi-region input-output analytical framework, this paper investigates global energy-related sulfur oxides emissions transferring via trade, so as to reveal spatial characteristics of the pollutant emissions flows, and explores driving factors of the changes of sulfur dioxide emissions embodied in trade (SEET) for 39 major countries for the period 1995-2011. One important finding from this study is that the global SEET mainly flew from developing countries like China to highly developed economies like the U.S., the EU, and Japan. However, of particular concern is that for some countries like Canada and Australia with ample resources and wealthy regions, they had been gradually becoming the net sulfur dioxide emissions exporters in global trade since 1995. Another important finding is that economic development had played a significant role in promoting the global SEET growth, and the expanse of population scale had a slight and positive driving effect on increasing the sulfur oxides emissions embodied in trade for a large proportion of 39 countries, but some coping strategies like improving energy intensity, increasing the proportion of clean energy in the total energy consumption, and optimizing industrial structure could effectively lower the sulfur oxides emissions embodied in trade in a group of 39 countries.

Structural decomposition analysis of embodied carbon in trade in the middle reaches of the Yangtze River.

The middle reaches of the Yangtze River are the first demonstration zone for low-carbon urbanization in the midwest regions of China, and the division of carbon emission reduction responsibility is an important aspect of construction of ecological civilization. In this paper, the embodied carbon emissions in trade are estimated by using an input-output model in the middle reaches of the Yangtze River, and then a structural decomposition analysis (SDA) model is further applied to conduct decomposition analysis on factors of embodied carbon changes. Our primary findings show the following: (1) Production-based CO2 emissions from Hubei and Hunan are higher than consumption-based CO2 emissions. There are situations in Jiangxi and Anhui where production-based CO2 emissions are both higher and lower than consumption-based CO2 emissions. However, inter-regional trade implied carbon is dominated by net inflows. Moreover, the inter-regional embodied carbon emissions in trade mainly flow out to relatively developed regions, such as Jiangsu and Shanghai. The inflow of embodied carbon in trade comes mainly from relatively backward economic development areas, such as Shaanxi and Inner Mongolia. (2) From the perspective of industry, industries in Jiangxi and Anhui are dominated by net inflow, whereas industries in Hunan and Hubei are dominated by net outflow. Meanwhile, industry in the middle reaches of the Yangtze River displays a high carbon-locked phenomenon. Specifically, the high carbon-locked outflow industries are mainly concentrated in the transportation and warehousing industry, agriculture, and the chemical industry, and the outflow provinces flow out mainly to Jiangsu, Guangdong, and other economically developed regions; high carbon-locked inflows are concentrated in metal smelting and rolling processing, food manufacturing and tobacco processing, and construction, and the provinces are mainly Hebei, Henan, and Inner Mongolia, where economic development is lacking. (3) Furthermore, the results of SDA decomposition indicate that scale effect is generally the most important factor leading to embodied carbon outflow. Meanwhile, the energy carbon emission effect, the energy intensity effect, and the structural effect are important factors-the inter-industry association effect mainly promotes the embodied carbon outflow. Consequently, based on the distinction between production and consumer responsibility, and from the perspective of scale effect and structural effect, the related policy suggests that consumers should be held responsible.

Agricultural environmental total factor productivity in China under technological heterogeneity: characteristics and determinants.

With limited resources, growing environment constraints and downward pressure on the economy, increasing agricultural environmental total factor productivity (AETFP) and its contribution to agricultural growth is significant for transforming agricultural development to make it more resource efficient and environment-friendly. This paper considered technological heterogeneity in different regions of China and measured AETFP in 30 provinces from 1997 to 2015 using the Metafrontier Malmquist-Luenberger (MML) productivity index. Multi-dimensional analysis was made on temporal and spatial characteristics, evolution patterns, and influencing factors of AETFP in China. The results showed that: (1) AETFP increased in the Ninth, Tenth, Eleventh, and Twelfth Five-Year Plan periods, with average annual growth rates of 0.76%, 0.88%, 1.17%, and 0.87%, respectively. (2) The average annual growth rate of AETFP in the eastern, central, and western regions decreased successively. The eastern region generally had played a leading role. The central region had a catch-up effect on environmental production technologies from the eastern region, while the western region lacked the catch-up effect. (3) The dynamic evolution of AETFP had prominent features. For the whole nation, the kernel density curve of AETFP continuously moved to the right. The main peak value continuously decreased and the width of the main peak continuously increased. The internal differences of AETFP in the eastern and western regions exhibited an increasing trend, while the internal differences of AETFP in the central region showed little change. (4) There was an inverted U-shaped relationship between agricultural economic growth and AETFP. Both the disaster rate and planting structure had a negative impact on AETFP with varying degrees of significance. Income gaps between urban and rural areas can partially offset the role of urbanization in promoting the growth of AETFP. The greater the income differences between urban and rural areas, the weaker the role of urbanization in promoting the growth of AETFP. These findings can help the government determine policies to change the agricultural development mode and formulate effective measures to improve AETFP.

Coupling and decoupling effects of agricultural carbon emissions in China and their driving factors.

The relationship between agricultural carbon emissions and agricultural economic growth has attracted a significant research attention. A key issue to address in the development of agriculture is the reduction of agricultural carbon emissions while maintaining agricultural economic growth. This study investigated the interactions between agricultural carbon emissions and agricultural economic growth from multiple perspectives based on agricultural carbon emission data from 30 provinces in China measured from 1997 to 2015. Using this dataset, the coupling and decoupling effects of agricultural carbon emissions and the underlying driving factors were explored using a coupling development degree model, the Tapio decoupling assessment model, and a logarithmic mean Divisia index (LMDI) decomposition model. The results were as follows: (1) at the regional scale, the degree of coupling development between agricultural carbon emissions and agricultural economic growth is high in the central region of China and low in the western region. At the provincial scale, the coupling effects of agricultural carbon emissions exhibited four levels: minimal, low, moderate, and high coupling. (2) With the exceptions of Beijing, Zhejiang, Fujian, Guangdong, Inner Mongolia, and Shanghai, the relationships between agricultural carbon emissions and agricultural economic growth in the other 24 provinces were in a weak decoupling state. (3) The effects of agricultural development scale and agricultural technical progress were the major driving factors associated with increases and decreases in agricultural carbon emissions, respectively.

A study of the influence of regional environmental expenditure on air quality in China: the effectiveness of environmental policy.

Based on the panel data model, data on environmental expenditures, the air quality index, economic aggregates, industrial structures, etc., of seven seriously polluted cities in China, from the period 2007-2015, were collected, and this paper estimates the general relationship between environmental expenditures and the air quality index. Besides, the impact of the fuel tax policy on air quality as well as on the relationship between environmental expenditure and the air quality index is tested using the method of regression discontinuity. We find that there is a long-term equilibrium relationship between environmental expenditure and air quality index as well as a 0.0507% positive effect of the former on the latter. Second, for Beijing, Taiyuan, Chongqing, and Lanzhou, a 1% increase in environmental expenditure leads to 0.0773, 0.0125, 0.0965, and 0.0912% decreases in the air quality index, respectively; however, for Shijiazhuang, Ji'nan, and Urumqi, effect of environmental expenditure on air quality is insignificant. Third, both economic growth and optimization of the industrial structure can lead to an improvement of air quality. Fourth, since the implementation of the fuel tax policy in 2009, the air quality of the sample cities has improved, and the pulling effect of environmental expenditure on the air quality index has decreased from 0.0507 to 0.0048%. Our findings cannot only clarify the effect of environmental expenditures on air quality but can also objectively judge the effectiveness of environmental policies of China to a certain extent. It may benefit Chinese government to effectively govern air pollution with fiscal tools in conjunction with economic and environmental characteristics.

The impact of local government investment on the carbon emissions reduction effect: An empirical analysis of panel data from 30 provinces and municipalities in China.

Among studies of the factors that influence carbon emissions and related regulations, economic aggregates, industrial structures, energy structures, population levels, and energy prices have been extensively explored, whereas studies from the perspective of fiscal leverage, particularly of local government investment (LGI), are rare. Of the limited number of studies on the effect of LGI on carbon emissions, most focus on its direct effect. Few studies consider regulatory effects, and there is a lack of emphasis on local areas. Using a cointegration test, a panel data model and clustering analysis based on Chinese data between 2000 and 2013, this study measures the direct role of LGI in carbon dioxide (CO2) emissions reduction. First, overall, within the sample time period, a 1% increase in LGI inhibits carbon emissions by 0.8906% and 0.5851% through its influence on the industrial structure and energy efficiency, respectively, with the industrial structure path playing a greater role than the efficiency path. Second, carbon emissions to some extent exhibit inertia. The previous year's carbon emissions impact the following year's carbon emissions by 0.5375%. Thus, if a reduction in carbon emissions in the previous year has a positive effect, then the carbon emissions reduction effect generated by LGI in the following year will be magnified. Third, LGI can effectively reduce carbon emissions, but there are significant regional differences in its impact. For example, in some provinces, such as Sichuan and Anhui, economic growth has not been decoupled from carbon emissions. Fourth, the carbon emissions reduction effect in the 30 provinces and municipalities sampled in this study can be classified into five categories-strong, relatively strong, medium, relatively weak and weak-based on the degree of local governments' regulation of carbon emissions. The carbon emissions reduction effect of LGI is significant in the western and central regions of China but not in the eastern and northeast regions. This study helps overcome the limitations of previous studies on the regulatory effects of LGI on carbon emissions, and the constructed model may more closely reflect actual economic conditions. Moreover, the current study can benefit countries similar to China that aim to objectively identify the impacts of their LGI on carbon emissions, and such countries can use it as a reference in the formulation of investment policies based on their economic and industrial characteristics.