Qihua Cai

Green is the foundation of agricultural development. By leveraging modern information technology, digital village construction injects new momentum into the green growth of agriculture. Using balanced panel data from 31 provinces in China from 2011 to 2022, this paper employs the entropy approach and SBM-GML index to measure the indicators of digital village construction and agricultural green total factor productivity (AGTFP). The impacts and mechanisms of digital village construction on AGTFP are examined through fixed effect, mediating effect, and threshold models. The findings are as follows: (1) AGTFP in China shows an overall increasing trend from 2011 to 2022, with significant growth in the western region compared to the eastern and central regions. (2) Digital village construction significantly accelerates the improvement of AGTFP, a conclusion supported by robustness tests. (3) Mechanism analysis indicates that digital village construction advances AGTFP by fostering agricultural technology innovation, enhancing agricultural human capital, and improving agricultural productive services. (4) Digital village construction has a more significant impact on major grain-producing areas, economically underdeveloped areas, and northern region compared to other regions. (5) Environmental regulation acts as a threshold effect on the impact of digital village construction on AGTFP. Digital village construction substantially impacts AGTFP when environmental regulation is below the threshold, with the positive effect continuing beyond this point but at a reduced intensity.

The livelihood capital of rural households is an essential basis for their selection of livelihood strategy. This paper uses rural household data from the 2018 CFPS to construct a “hexagonal” framework for the analysis of livelihood capital. Natural capital, material capital, financial capital, social capital, human capital, psychological capital, and total livelihood capital are measured using entropy weight method. The paper uses logit and tobit models to analyze how livelihood capital affects rural households’ entrepreneurship. Finally, the heterogeneous impact of livelihood capital on rural households’ entrepreneurial behavior is discussed from the view of household head gender, household education level, and regional differences. The results show that rural households’ livelihood capital distribution in each dimension is uneven and the difference is great. Rural households’ capital of livelihood and finance have positive effects on their entrepreneurial behavior. Heterogeneity analysis shows that the increase in livelihood capital impacts entrepreneurship in female-headed households more positively and significantly. Livelihood capital can significantly promote the entrepreneurial behavior of rural households with lower education levels. The impact of livelihood capital on rural household entrepreneurship presents a decreasing distribution pattern from east to the middle to west. The results of the robustness test show that the conclusion of the positive impact of livelihood capital on rural household entrepreneurship is reliable. The main conclusions provide guidance and a foundation for further optimizing rural household entrepreneurship policies and promoting rural household entrepreneurship.

Traditional urbanization has stimulated economic growth. Meanwhile, it has damaged the natural environment. China has initiated new urbanization to resolve this dilemma. This paper aims to clarify the relationship between new urbanization and environmental pollution and prove new urbanization's superiority in containing environmental pollution. Thus, this paper adopts the static and dynamic spatial Durbin and mediating effect models to estimate the environmental pollution control mechanism of the new urbanization, using the panel data collected from 285 prefecture-level cities in China from 2003 to 2018. Findings show that: (1) Environmental pollution has time inertia and spatial spillover effect. The degree of pollution in an area is related to the environmental quality in the earlier stage and the surrounding areas. (2) The role of new urbanization in containing environmental pollution can take effect in the long run. In the short term, population urbanization can restrain the environmental pollution of both local and surrounding cities. (3) Heterogeneity analysis shows that the higher the level of environmental pollution, the greater the impact of new urbanization on environmental pollution. (4) Mediating effect test shows that technological effect and industrial structure upgrading are two important channels for new urbanization to reduce environmental pollution. (5) Threshold effect test shows that the inhibition effect of new urbanization on environmental pollution is gradually enhanced after crossing the threshold.

Purpose: The purpose of this paper is to examine how households’ engagement in concurrent business (CB), which is measured by the contribution of off-farm income to household income, affects the farm size–technical efficiency (TE) relationship in Northern China.Design/methodology/approach: This paper applies a stochastic frontier analysis method to analyze data on 1,006 rural households collected from four major wheat-producing provinces in Northern China, adopting a translog specification for the underlying production function.Findings: The analysis yields three findings. First, the farm size–TE relationship is inverted U-shaped for all CB engagement levels higher than 5 percent, and the most technically efficient farm size increases with the level of household CB engagement. Second, how TE varies with the level of CB engagement depends on farm size: an inverted-U relationship for relatively small farms (20μ). Finally, the overall TE score, 0.88, suggests that wheat output can be increased by 12 percent in Northern China if technical inefficiency were eliminated.Originality/value: Unlike most previous studies that examine the impacts of farm size and households’ off-farm business involvement separately, this paper examines how these two factors interact with each other.

Purpose: – The purpose of this paper is to examine the roles social networks play in households’ contribution to the provision of small hydraulic facilities (SHFs) in rural China.Design/methodology/approach: – This paper adopts a sample-selection ordered probit model (Greene and Hensher, 2010) to estimate the impacts of overall social-network intensity, of the number of strong ties (relatives), and of the number of weak ties (friends), using data on 1,064 representative households collected from three provinces (Inner Mongolia, Ningxia, and Shandong).Findings: – The numbers of strong ties and weak ties both have significant impacts on households’ willingness to contribute to SHFs provision, but only the latter has a significant impact on their level of contribution. More specifically, a one standard deviation increase in the number of weak ties (i.e. friends) is associated with a 6.6 percent increase in households’ propensity of contributing more than 550 yuan and a 8.2 percent decrease in their propensity of contributing less than 100 yuan.Originality/value: – This paper is the first to examine the impacts of social networks on households’ contribution to SHFs provision in rural China. Its finding is of great policy relevance-fostering and maintaining social networks (e.g. through rural cooperatives) can significantly increase households’ contribution to public-good provision.