Digital Village Development and Agricultural Carbon Reduction in China: Evidence from Provincial Panel Data(中国数字乡村发展与农业碳减排:来自省级面板数据的证据)

1. Introduction

Climate change, ecological degradation, and the continued growth of greenhouse gas (GHG) emissions continue to place considerable pressure on global sustainable development. Carbon mitigation is not only an environmental issue but also a strategic development goal for China. The country has announced that before 2030, it will reach peak carbon dioxide emissions, and before 2060, it will become carbon neutral [1]. While emissions from sectors based primarily on CO 2 combustion from fossil fuels are different from agricultural emissions, this means that achieving national climate targets will not be possible without mitigation measures in all parts of the economy, not just in heavy industry, power generation and transport [2]. It is, hence, essential for policies concerning agricultural and rural progress to be incorporated into the holistic framework of climate governance in China.

When compared with manufacturing, electricity generation, transportation or construction, agriculture is sometimes considered a relatively low-carbon industry. However, this perception might not consider the significant carbon footprint of today’s food production. The current agricultural system relies on chemical fertilisers, pesticides, plastic mulch, machinery powered by diesel, and irrigation and tillage systems. These inputs and practices are sources of emissions during their manufacture and distribution and also during their use on-farm; they are significant contributors to agricultural carbon emissions [3]. Fossil energy is also required during irrigation and land management operations, which can also have an impact on the soil carbon cycle and consequently increase the climate change footprint of agriculture [4]. The spatial distribution of agricultural emissions in China is uneven, and high emissions are frequently found in the north. This trend is due to variations in natural resource endowments, crop composition, production technologies, intensities of production inputs, and local policies [5]. Earlier empirical studies have also revealed that the performance of emissions varies widely across regions, suggesting that mitigating policies should be flexible and locally tailored instead of managed at the national level [6]. Technological progress and the change of the organisation of agricultural production have been important means of achieving a low-carbon transition in agriculture in this context [7].

Rural economies are changing in the context of digitalisation all over the world. The collection, transfer, interpretation and utilisation of agricultural information is transforming through big data analysis, Internet of Things (IoT) equipment, mobile communication networks, remote sensing technologies, cloud-based platforms, and digital service systems. Evidence from the international literature shows that data-intensive farming can lead to better resource allocation and a reduction in the waste of resources [8]. Smart farming systems can help to better manage water, fertilisers, pesticides and machinery [9]. However, rural digital transformation is not merely the introduction of new equipment into agricultural production. It also transforms agricultural extension, institutions at the local level, market linkages, farmers’ behaviour in managing business, and the linkages among farmers, service providers, firms and consumers [10].

The impacts of digital agriculture are quite varied at the national and regional levels. In many high-income countries, sensor-based systems, IoT applications and automated control technologies have been adopted for large-scale commercial farming. In these situations, digital solutions have shown the potential to optimise input usage and create tangible gains in emissions reductions [11]. On the other hand, there is still a significant gap in agriculture mechanisation, according to data from many low- and middle-income economies. Digitalisation is limited by weak rural infrastructure, fragmented farms, limited financial access and a lack of technical support to achieve environmental gains [12]. Such disparities reveal that the climatic effects brought by digital farming hinge on plot scale, institutional arrangement, human capital stock and matched service infrastructures. The digital village strategy in China has emerged in an agricultural landscape dominated by smallholders. It is not the “smart-farm” model that has been adopted by many advanced economies, nor is it the more nascent digital agriculture model in many low-income economies. It, thus, serves as a valuable case study to explore the linkages between rural digitalisation and agricultural carbon mitigation in the context of a developing country.

In China, digital village development is not limited to access to the internet or the construction of hardware. It is a holistic rural transformation approach integrating digital infrastructure, digital industry, public services, financial inclusion, logistics systems and e-governance. According to comparisons among different provinces, it is known that the development of the digital village is still in an imbalanced state in China [13]. Recent evaluation studies also indicate a close relationship between digital rural development results and rural revitalisation outcomes and governance capacity [14]. The advancement of the rural digital economy has further facilitated industrial upgrading and the restructuring of local production and organisational patterns [15]. Digital platforms have made the farmers’ market more accessible, brought agricultural products into circulation faster and have helped rural household income and welfare [16].

However, the environmental implications of digital village development remain insufficiently understood. From a macro perspective, the digital economy promotes green total factor productivity through three channels: knowledge spillover, optimised resource allocation and industrial structure transformation [17]. In China, internet development has impacted energy consumption in three ways: energy use efficiency, the nature of energy consumption, and industrial transformation [18]. International evidence also suggests that digitalisation can contribute to energy transition, but the impact is contingent on the quality of local governance and institutional capacity [19]. Based on the empirical studies conducted in China, energy intensity and emissions may be reduced by digitalisation if the conditions are suitable [20]. Digitalisation in agriculture has the potential to lower carbon intensity through structural change and technological innovation [21]. Digital village development can also enhance information flow and the land use of cultivated lands, which can help greener land use transformation [22]. There is recent research evidence that digitalisation in the countryside can enhance the green performance of agricultural production; however, direct evidence on input-related agricultural carbon emissions remains limited [23].

International studies have highlighted the importance of institutional arrangements and rural human capital in determining the potential of turning digital tools into low-carbon farming practices [24,25]. Many developing economies are confronted with two pressures: on the one hand, rural digitalisation remains underdeveloped, while on the other hand, agricultural production relies on carbon-intensive inputs. The lessons learned from China suggest that digitalisation can contribute to emission reduction and green transition if it is integrated into relevant policy systems, service systems, and production systems; thus, the country is able to offer empirical references for nations confronting similar development challenges [20,21,26].

Despite growing interest in the environmental consequences of digitalisation, several gaps remain. First, much of the existing literature examines the general digital economy, urban digitalisation, or isolated digital–agricultural technologies, while fewer studies focus on digital village development as a multidimensional rural transformation process that integrates infrastructure, industrial applications, public services, digital finance, logistics, and rural e-commerce. Second, agricultural carbon emissions from the input side and the field-operation side have been less directly discussed in many studies, while agricultural green total factor productivity, carbon intensity, and pollution indicators are used as outcome variables. Third, there is scarce evidence regarding the circumstances in which digital village development is more strongly connected to agricultural carbon mitigation, including its relationship to rural education, the region in which it is implemented, grain-functional areas, and mechanisation. Fourth, there is a need for increased transparency in the construction of the composite digital village indicators, including indicator selection, PCA loadings, and the contribution of various digital dimensions.

The following question guides this study: is digital village development associated with lower agricultural carbon emissions across China? A multidimensional digital village development index is constructed from eight standardised indicators to answer this question. PCA diagnostics and a PCA-based alternative index are further used to examine the validity and sensitivity of the index construction. To estimate the relationship between digital village development and agricultural carbon emissions, this study utilises balanced panel datasets covering 30 provincial regions from 2014 to 2023. Empirical analysis consists of two-way fixed-effects models, multiple robustness tests, heterogeneity analysis, and an additional instrumental-variable exercise (reported in the Appendix A) and exploratory subgroup analysis with regard to potential mechanisms.

This study contributes to the literature in three ways. First, it links digital village development with agricultural climate governance by examining input-related agricultural carbon emissions rather than only rural income, industrial upgrading, or agricultural green total factor productivity. Unlike recent prefecture-level or county-level studies that usually focus on the rural digital economy or agricultural green productivity, this study treats the digital village as a multidimensional policy and development framework and directly examines input-related agricultural carbon emissions. Second, it constructs a multidimensional digital village index from eight standardised indicators and reports additional PCA diagnostics, including component loadings, variance contribution, and the KMO statistic. It also uses a recomputed PCA-based index as a sensitivity check, thereby improving the transparency and reproducibility of index construction. Third, it examines heterogeneous associations across rural education levels, regions, grain-functional areas, and mechanisation conditions and provides mechanism-related evidence based on different agricultural carbon-emission sources.

China’s digital village strategy has a distinctive institutional context. It has developed in a smallholder-dominated agricultural system but is supported by national rural revitalisation policies, public investment in digital infrastructure, the rapid expansion of rural e-commerce, digital inclusive finance, and logistics networks. This differs from the capital-intensive smart-farming model in many high-income economies and from more fragmented digital–agriculture initiatives in some low-income economies. Therefore, the findings should not be interpreted as mechanically generalisable to all countries. Rather, they provide analytical evidence for developing economies seeking to combine rural digital inclusion, agricultural modernisation, and low-carbon transition under smallholder conditions.

The remainder of this paper is organised as follows. Section 2 reviews the related literature. Section 3 develops the theoretical framework and research hypotheses. Section 4 describes the data, variables, and empirical models. Section 5 presents the empirical results. Section 6 discusses the findings. Section 7 concludes the paper and provides policy implications.

2. Literature Review

2.1. Digital Village Development and Rural Transformation

Digital village development is a comprehensive process of rural transformation which involves the connectivity of infrastructure, digital industrial activities, service delivery and the modernisation of governance. Digital tools improve agricultural production efficiency through real-time data gathering, remote farm supervision, precision agricultural management and data-driven decision-making [27]. A special characteristic of digitalisation in the rural areas of China is the fast development of rural e-business, especially the growth of the ‘Taobao villages’ linked to big online platforms [28]. These new rural economic models are examples of the way that digital marketplaces can connect geographically dispersed producers with national consumer markets and encourage local entrepreneurship [28,29]. Advancement in the development of digital villages helps bridge the income gap between urban and rural residents. It enables rural populations to gain easier access to information, employment opportunities, financial services, logistics systems and public service facilities [29]. New evidence from the provinces shows that digital village development can also help to foster agricultural green growth [30].

The majority of studies published so far agree that digital village development can bring about economic and social benefits and that the impact on the environment is more complex [17,21,22]. Increased digital infrastructure can, on the one hand, lead to a higher electricity demand and a higher use of digital equipment in rural areas. Conversely, there are applications in the fields of precision agriculture, rural logistics, e-commerce and extension that could help to decrease the overuse of agricultural inputs, enhance coordination and lower agricultural carbon emissions [22].

The environmental impact overall will hinge on how the implementation of digital infrastructure is followed by productive applications and service innovations that impact decisions in agricultural production. International experiences demonstrate that digitalisation in rural areas can take several forms in different countries. In the high-income context of Western Europe, digital technologies are frequently used in large mechanised agriculture, but their use is still dependent on the social, political and institutional situation in rural communities [31]. In many of the settings in which digital benefits are explored in developing contexts, these services are also critical, including mobile money, input markets, extension networks, and reliable infrastructure. Smallholder dominance might also constrain the environmental benefits of applications of digital technology, unless service systems can be developed to address scale constraints [32]. These differences indicate that the size of the farm, institutional conditions and service capacity play a key role in whether or not rural digitalisation can make a positive contribution to carbon reduction.

2.2. Agricultural Carbon Emissions: Measurement, Drivers, and Mitigation

In the agricultural carbon-accounting literature in China, emissions are often estimated based on the inputs and field operations of agricultural production processes [3,5,7]. The use of chemical fertilisers, pesticides and plastic mulch films continues to be a significant source of the carbon footprint of Chinese agriculture [33]. Other practices such as diesel, irrigation and tillage are also important because they are closely related to energy use and field management. Agricultural emissions of carbon are highly location- and time-dependent and are influenced by land resources, planting systems, mechanisation, environmental policies and input levels [34].

Digitalisation has increasingly been regarded as a potential pathway for greener agricultural development. Digital technologies offer the potential to better allocate reso