The role of digital finance in reducing agricultural carbon emissions: evidence from China's provincial panel data

Coupling coordination between digital village construction and agricultural carbon emissions in China

Exploring the coupling coordination degree (CCD) between digital village construction (DVC) and agricultural carbon emissions (ACE) is crucial for promoting village revitalization and sustainable agricultural development. Analyzing data from 30 provinces in China in 2011-2020, this paper employs the CCD model, the Dagum Gini coefficient, and the geographic detector for in-depth analysis. The results show that the overall level of CCD gradually increases over time, but the national CCD still remains in a state of "low coordination," and there are apparent spatial differences in the CCD among provinces. In addition, the overall difference in CCD shows a decreasing trend, and the contribution of inter-regional differences has gradually become the most critical source of CCD's regional difference. Finally, the spatial differences of CCD are the result of two-factor interaction, among which the innovation level is the most core driving factor. The above findings provide important implications for China and other developing countries to fully leverage the interaction between village digitalization and agricultural decarbonization to promote sustainable agricultural development.

How does green finance impact carbon emissions in China: Evidence from the fintech perspective

In light of China's objectives for carbon peak and carbon neutrality, there is an opportunity for fintech to leverage its technological advantages and enhance its integration with green finance (GF). This can bring about enhanced coverage and precision of financial services for green industries, facilitating the transformation towards a sustainable, greener, and low-carbon real economy. We investigate how fintech development influences the carbon emission reduction effects of GF utilizing a two-way fixed effects model with a panel dataset covering 30 provinces in China from 2011 to 2020. Our findings indicate that the negative impact of GF on carbon emissions (CE) is heightened in areas with high levels of fintech development. Furthermore, we notice regional disparities in how fintech development impacts the effectiveness of GF in reducing CE. Specifically, fintech has a statistically significant impact in the central and western regions, whereas its significance is absent in the eastern region. Lastly, our mechanism analysis reveals that fintech plays a vital role in enhancing GF's capacity to mitigate CE, which is achieved through channels of promoting green technology innovation (GTI), alleviating corporate financing constraints (FC), and optimizing energy structure (ES). These findings provide compelling evidence for the positive effect of fintech on the environment and offer justification for promoting the development of fintech and GF.

Does green finance matter for agricultural carbon abatement? Fresh insight from China

Green finance constitutes a fundamental financial institutional arrangement aimed at achieving the dual-carbon objective during China's agricultural transition toward low-carbon, which aligns with the pragmatic necessity for reducing agricultural carbon emissions. For this purpose, this study investigates the impact of green finance on agricultural carbon reduction and its underlying mechanism by analyzing panel data from 30 regions using a two-way fixed effects model. Results indicate that green finance significantly promotes agricultural carbon reduction. The promotion effect of green finance on agricultural carbon reduction demonstrates an uneven spatial distribution, declining from eastern to western to central regions. Notably, non-Yangtze River Economic Belt provinces exhibit more pronounced effects compared to the Yangtze River Economic Belt region. Industrial structure upgrading and green innovation serve as crucial pathways for green finance to augment agricultural carbon reduction. Our finding reveals policymakers should implement differentiated green finance implementation strategies to accelerate the restructuring of the agricultural industry and encourage the introduction and use of innovative low-carbon technologies.

Effect of agricultural fiscal expenditures on agricultural carbon intensity in China

Few studies provide direct evidences that agricultural fiscal affects agricultural carbon intensity. This study tries to fill this gap. Using panel data of 30 provinces in China from 2005 to 2019, we conclude that agricultural fiscal expenditures significantly reduce agricultural carbon intensity. The result is still robust after employing the provincial agricultural leaders' birthplace information as an instrumental variable. Further study shows that the negative effect of agricultural fiscal expenditures on agricultural carbon intensity is more pronounced in regions with less corruption and is also more visible in central, western, and inland regions than other areas. For this effect, agricultural technological improvement and structure optimization are possible channels, but not operation scale expansion. Interestingly, although agricultural fiscal expenditures reduce the local agricultural carbon intensity, neighbor regions' carbon intensities are increased due to fiscal rivalry.

The effect of environmental regulation and green subsidies on agricultural low-carbon production behavior: A survey of new agricultural management entities in Guangdong Province

Agricultural low-carbon production emerges as a pivotal function for achieving sustainable green development. However, there remains insufficient empirical evidence regarding the effect of environmental regulations and green subsidies upon the low-carbon production behavior of new agricultural entities. In this study, a questionnaire survey was administered to 268 respondents representing new agricultural entities in Guangdong Province, P.R.C. Subsequently, a structural equation model had been employed for validation analysis. This study's findings demonstrate that in general, environmental regulations positively and significantly affect the behavior of agricultural low-carbon production. Conversely, the influence of green subsidies is not statistically significant. In addition, differences are observed across different sectors, with environmental regulations significantly affecting low-carbon production behavior in the plantation sector, but not in the livestock sector. Conversely, green subsidies significantly impact low-carbon production behavior in the livestock sector, but not in the plantation sector. These findings highlight the promotional role of government-enforced environmental regulations and green subsidies in fostering low-carbon agricultural practices. Therefore, new agricultural entities should strive to augment green production technology capacities to realize sustainable green development.

Does digital technology innovation promote low-carbon development in agriculture?: A spatial econometric analysis based on 31 provinces in China

China's traditional agriculture has grown quickly but at the cost of excessive pollution and energy consumption. Therefore, low-carbon development in agriculture is crucial to achieving "carbon neutrality" and "carbon peaking." With the development of China's digital economy and the construction of digital villages in recent years, digital technology innovation (DTI) is probably going to a significant role in lowering agricultural carbon emissions (ACEs). Based on Chinese provincial panel data from 2006 to 2021, we analyze the spatial and temporal evolution characteristics of DTI and ACE, explore the impact and the pathways of DTI on ACE using a spatial econometric model, and reveal this impact's heterogeneity and nonlinear character. The findings show that DTI and ACE increased significantly throughout all Chinese provinces. DTI agglomeration is becoming stronger, whereas ACE displays a tendency for discontinuous distribution. DTI is essential in promoting low-carbon development in agriculture, and there are significant spatial spillover effects due to technology spillovers. Heterogeneity analysis indicates that DTI has positive impacts on local agriculture in different regions. However, there is variation in the impact's degree. The mechanism test's findings show how DTI reduces ACE by improving technology and enhancing resource endowment. The relationship between DTI and ACE exhibits an inverted "U" curve, and the level of economic development is the threshold variable that constrains the relationship between the two variables. To achieve a regional balanced low-carbon development in agriculture through DTI, it is important to emphasize the impact of DTI on reducing carbon emissions and to encourage the transfer of mature technology from high-level regions to low-level regions.

New evidence on the impact of No-tillage management on agricultural carbon emissions

Controlling agricultural carbon emissions contributes to achieving peak carbon emissions and carbon neutrality. However, as a conservation management practice of farmland, the impact of No-tillage management (NTM) on agricultural carbon emissions needs to be further discussed. The main purpose of this paper is to assess the direct effect and spatial spillover effect of NTM on agricultural carbon emissions, revealing the regulating mechanism of NTM on agricultural carbon emissions and the combined application of NTM. Results indicate that NTM reduces agricultural carbon emissions, which is significant in the central and western regions, along with the primary grain, corn, and rice production areas, as well as the northern regions of the Huai River. Furthermore, the spatial spillover analysis reveals that the implementation of NTM increases agricultural carbon emissions in neighboring regions, but financial support and cross-regional services can negatively regulate the relationship between NTM and space agricultural carbon emissions. This paper also finds that combining straw-returning technology and NTM reduces agricultural carbon emissions. Building a cross-regional coordination mechanism, an incentive mechanism, and innovating the conservation tillage model is essential for promoting the NTM and achieving agricultural carbon reduction.

How digital finance promotes renewable energy consumption in China?

This study uses a quantitative methodology to investigate how the rise of digital money has affected efforts to increase green energy use in China. This work contributes to the body of knowledge by using a number of empirical methods, such as regression analysis, parametric quantile estimation, stability diagnostic tests, and sensitivity analysis. This study's results further demonstrate the importance of digital financing in easing the adoption of renewable energy sources throughout China. Financing alternatives for renewable energy projects have increased as a result of digital finance's integration of digital technology with financial services. A wider range of investors has been attracted through crowdfunding, peer-to-peer lending, and other alternative financing models made possible by digital platforms, allowing the development of small and medium-sized renewable energy projects that may have had trouble securing funding through more traditional channels. The impact of digital finance on energy management and optimization is also investigated. As a result, renewable energy sources have been more widely adopted due to increased energy efficiency, better grid integration, and more efficient energy delivery. This study presents substantial evidence of the beneficial benefits of digital finance on renewable energy use in China using rigorous empirical methodologies such as regression analysis, parametric quantile estimation, stability diagnostic tests, and sensitivity analysis. The results highlight the significance of using digital money to boost the use of renewable energy, lessen reliance on fossil fuels, and help create a greener, more sustainable future.

Can digital inclusive finance promote agricultural green development?

Digital inclusive finance (DIF) provides new momentum for green agricultural development (AGD). This paper measured AGD with entropy weight TOPSIS in five dimensions, including resource conservation, environmental friendliness, ecological conservation, green supply, and economic growth. After that, it estimated the regional spillover effects and threshold impacts of DIF on AGD utilizing China's provincial panel data from 2011 to 2020. The paper shows that (1) DIF and AGD have such a U-shaped complex interrelationship; (2) the AGD is spatially impacted by DIF. The unique manifestation is that as DIF has increased, its effect on AGD has steadily changed from being direct to being indirect, and this effect has regional heterogeneity; and (3) in regions with higher levels of green technology innovation, better development of traditional finance, or relatively concentrated agricultural industries, DIF plays a more prominent role in promoting the AGD.

Impact of digital infrastructure inputs on industrial carbon emission intensity: evidence from China's manufacturing panel data

Digital infrastructure inputs (DIIs) are vital in strengthening the framework for developing the digital economy and encouraging economic growth. Nonetheless, the risks of environmental contamination are pervasively caused by the rapid expansion and utilization of digital infrastructure. Assessing the carbon emission intensity (CEI) and level of the DIIs of 18 manufacturing in China as the research subject, this study discusses the heterogeneous behavior of various input sources and industries. Furthermore, a two-way fixed effects model, threshold effects model, mediating effects model and moderated mediation effects model have been adopted to examine the nexus between DIIs and CEI of manufacturing. The results show that (1) DIIs raise China's manufacturing CEI and exert a non-linear threshold effect. (2) From the perspective of national attributes, the foreign DIIs will put more pressure on reducing the CEI in China. From the perspective of industry characteristics, DIIs are the most unfavorable for low-carbon development in capital-intensive industries. (3) Due to the mediating effect of total factor productivity (TFP), the positive influence of DIIs on CEI has dramatically diminished. (4) Participation in the global value chain (PAR) and foreign direct investment (FDI) exert moderating effects in the process of the direct effect and mediating effects. In light of the aforementioned conclusions, specific recommendations for developing digital infrastructure and reducing carbon emissions are proposed.

Spatiotemporal characteristics and determinants of agricultural carbon offset rate in China based on the geographic detector

This paper attempts to explore the spatiotemporal variation characteristics of the agricultural carbon offset rate (ACOR) and the reasons that shape its differentiation characteristics in China. To achieve this objective, the Dagum Gini coefficient, kernel density estimation, and geographic detector model are employed in this study. The results show that there are some differences in ACOR among regions in China. Interregional differences are the main source of their overall variation. Excluding the spatial conditions, the ACOR of each province in the sample period shows low mobility characteristics. Considering the spatial conditions, there is convergence in the lower-middle neighborhoods. The three-year lag period did not significantly affect the interaction of ACOR between regions under the accession time horizon. At the aggregate level, the spatial and temporal divergence in China's ACOR is driven by urbanization rate, agricultural fiscal expenditure, and rural education level. As for the regional level, the scale of household farmland operation plays a greater role in determining the spatiotemporal variation of the eastern and central regions' ACOR. While urbanization rate is more determinant for the western region, the interaction between any two factors has significantly higher explanatory power for the spatial and temporal variation of ACOR than the single factor.

Does economic agglomeration improve agricultural green total factor productivity? Evidence from China's Yangtze river delta

Economic agglomeration plays an important role in China's social transformation process of industry feeding agriculture and urban supporting rural areas, and is one of the core weapons to promote agricultural economic growth and green and efficient development. Based on panel data of 41 cities in the Yangtze River Delta (YRD) from 2010 to 2020, this paper constructs an "environment-resource-energy-economy" agricultural input-output system, taking into account carbon emissions and surface pollution, and provides a more comprehensive accounting of agricultural green total factor productivity (AGTFP), the non-linear effects of economic agglomeration on AGTFP and shock responses were empirically analyzed using a panel threshold model and a panel vector autoregression (VAR), respectively. The findings show that: (1) during the period 2010-2020, the AGTFP in the YRD showed an overall rising trend with regional spatial agglomeration characteristics. (2) Economic agglomeration has a triple threshold effect on AGTFP, which was a weak facilitative effect in the early stage, inhibited by the siphoning effect of resource loss and arable land fragmentation in the growth stage, promoted by the radiation effect of external increasing return to scale in the form of sharing, matching and learning in the maturity stage, and finally tends to decline. (3) The shock response of economic agglomeration to AGTFP showed a continuous positive shock, peaking in the first period and then gradually converging to zero. (4) The heterogeneity analysis demonstrated that economic agglomeration has a considerable impact on boosting AGTFP in non-metropolitan areas and cities on the outskirts of YRD. In the future, China should effectively play a positive role in economic agglomeration on AGTFP and enhance the mutual coordination of economic agglomeration and agricultural green development in the process of urban cluster economic growth.