Expanding employment channels for rural households is a crucial means of enhancing the income of rural residents and enhancing the quality of rural employment. This study examines the impact of digital skills on rural laborers’ employment choices and explores the underlying mechanisms by using data from the China Family Panel Studies (CFPS) spanning 2014–2018. By employing various models, including the Probit, IV, mediated effects, and propensity-score-matching methods, the study reveals that digital skills have a significant impact on rural laborers’ employment choices. Specifically, digital skills increase rural labor’s employment opportunities in nonfarm and employed employment while reducing the proportion of informal employment. Additionally, the analysis indicates that the main channels through which digital skills influence rural labor’s employment choices are human and social capital. A heterogeneity analysis further reveals that work-study and social-entertainment skills have a more significant effect on rural laborers’ nonfarm and employed employment opportunities while inhibiting informal employment. Hence, to enhance the quality of future rural employment, the government must encourage rural workers to enhance their digital literacy and digital application skills while improving digital infrastructure.

With global warming, China’s agricultural products are facing severe production conditions and a complex international trade situation. In order to clarify the relationship between climate change and China’s agricultural trade, this paper uses the GTAP model to explore the impact of climate change on China’s agricultural trade from the perspectives of agricultural production and supply, energy substitution and trade policy. The results show that: (1) From the overall effect, the production supply risk and energy substitution risk caused by climate change have a positive impact on China’s import trade, among which the energy substitution risk has brought about an import trade growth of 38.050%, the production supply risk has brought about an import trade growth of 12.635%, and the trade policy risk has a negative impact, bringing about an import trade decline of 12.589%. (2) Under the impact of production and supply risks caused by climate change, the import volume of different industrial sectors has increased by varying degrees, including livestock products (16.521%) > food crops (14.162%) > cash crops (7.220%). The increase in import trade mainly comes from the United States (10.731%), Canada (10.650%) and Australia (9.455%). (3) Under the impact of energy substitution risk caused by climate change, the increase in import trade was concentrated in food crops (48.144%) and livestock products (42.834%), mainly from the United States (57.098%), the European Union (55.014%) and Canada (53.508%). (4) Under the impact of trade policy risks caused by climate change, the import trade of different industrial sectors showed a downward trend, with cash crops (13.039%) > livestock products (12.588%) > cash crops (12.140%). The countries and regions with significant decline in import trade were ASEAN (−46.131%) and the United States (−28.028%). The trade deficit shifted to surplus, and the terms of trade were improved. Therefore, this paper suggests that we should deal with the impact of climate change on agricultural trade by developing “climate smart” agriculture, actively responding to low-carbon trade measures, and establishing an agricultural trade promotion mechanism to address the risk of climate change.

As the digital economy increasingly integrates with the real economy, the goal of high-quality economic development in China has become increasingly clear. Promoting high-quality regional economic development through the integration of the digital and real economies holds significant practical importance for achieving Chinese modernization. This study selects panel data from 2013 to 2023 for 31 provinces, autonomous regions, and municipalities directly under the central government in China. It employs the entropy method to measure the development levels of both the digital and real economies in each province. It uses a coupling coordination degree model to gauge their level of integration. By constructing bidirectional fixed-effects models, mediating effect models, and spatial econometric models, this study explores the impact of Digital–real Integration (DRI) on regional High-Quality Development (HQD). The findings reveal that DRI promotes high-quality regional economic development, with a 1% increase in DRI leading to a 4.810% increase in high-quality regional economic development. Meanwhile, this effect exhibits significant regional disparities. During this process, industrial structure upgrading and scientific and technological innovation serve as mediating factors, with coefficients of 1.249 and 10.562, respectively, for every 1% increase in DRI. Moreover, DRI exhibits significant spatial spillover effects, benefiting neighboring regions. Based on these findings, the paper proposes targeted recommendations, including strengthening digital infrastructure to lay a solid foundation for integrated development, implementing an innovation-driven strategy to master core technologies, optimizing production factor allocation to amplify DRI’s driving force, breaking regional economic barriers, and adopting dynamic, differentiated development strategies tailored to local conditions. These measures aim to fully harness DRI’s potential in advancing high-quality regional economic growth, offering empirical insights for coordinated regional development.

Appropriate-scale operation is important for integrating ordinary farm households into modern agriculture, yet the appropriate scale may differ substantially across producer types. Using micro-level data from the nationally representative 2021 China Household Finance Survey, this study develops an analytical framework integrating efficiency and resilience perspectives to compare ordinary farm households and family farms. Efficiency is the core empirical dimension and is assessed using cost–benefit analysis, the DEA-BCC model, and multivariate econometric methods. Resilience is treated as a theoretical perspective and a constraint on scale decisions; it is interpreted indirectly through the scale responses of the two groups to disaster shocks rather than measured using a standalone resilience index. The results identify distinct efficiency-based appropriate-scale ranges: 1–3 mu (approximately 0.07–0.20 hm²) for ordinary farm households and 100–200 mu (approximately 6.67–13.33 hm²) for family farms, with lower net profit per unit area at intermediate scales. Economic rationality and institutional constraints show marked heterogeneity across producer types: commercialization, land titling, subsidies, and credit access are more strongly associated with the scale expansion of family farms, whereas non-farm employment opportunities play a more decisive role for ordinary farm households; household labor and social networks contribute to scale expansion in both groups, and their between-group differences are not statistically significant. Disaster impact is associated with a significant reduction in the operational scale of ordinary farm households, whereas in the subgroup estimates the operational scale of family farms shows no significant association with disaster impact, suggesting that family farms are better able to maintain their operational scale. Digital technology also operates through differentiated pathways: it primarily alleviates information and factor constraints among ordinary farm households while strengthening efficiency, financial access, and organizational coordination among family farms. These findings support differentiated scale and digital-agriculture policies in economies characterized by heterogeneous farm structures.

Ecological efficiency is fundamental to the sustainable development of the livestock industry. Understanding how the digital economy enhances this efficiency is critical for promoting high-quality sectoral development. Using panel data from 30 Chinese provinces during 2011–2023, this study measures livestock ecological efficiency with a Super-SBM model and conducts empirical analyses using two-way fixed effects, mediation, spatial econometric, and panel threshold models. The results show that digital economic development significantly improves livestock ecological efficiency. This effect is realized through the expansion of livestock farming scale and the upgrading of the industry’s structure. Spatial panel analyses further indicate that digital economic development generates significant spatial spillover effects, which positively enhance ecological efficiency in neighboring regions. Further analyses reveal clear regional heterogeneity. Both the direct and spatial spillover effects decline progressively from eastern to western China. In addition, a significant single-threshold effect is identified. Based on these findings, this study proposes establishing cross-regional coordination mechanisms linking digital economy development with ecological compensation, implementing region-specific development policies, and strengthening ecological infrastructure within the livestock sector. These measures would help fully leverage the digital economy in improving livestock ecological efficiency.

Introduction: Agricultural green and low-carbon development constitutes a crucial component of sustainable human development and has become a focal concern for governments, the public, and the academic community alike. Environmental regulation is widely recognized as an important instrument for advancing agricultural green development. However, research remains limited on how different combinations of environmental regulations jointly enhance agricultural ecological efficiency. Methods: Based on a “government-market-public” analytical framework and using panel data from 31 provinces in China, this study employs a dynamic QCA approach to examine, from both spatial and temporal perspectives, the configurational effects through which combinations of government-based, market-based, and public-participation environmental regulations improve agricultural ecological efficiency, thereby identifying multiple pathways toward agricultural green development. Results: The results show that: (1) no single type of environmental regulation constitutes a necessary condition for improving agricultural ecological efficiency; nevertheless, adequate government support plays a pivotal role. Achieving high agricultural ecological efficiency requires the joint participation and coordinated functioning of multiple environmental regulatory actors. (2) Four configurational pathways leading to high agricultural ecological efficiency are identified: the government-market-public synergistic promotion pattern, the government-led pattern, the government-market dual-driven pattern, and the government-public driven pattern. By contrast, the government-market-public deficiency-induced inhibition pattern constitutes the principal pathway leading to low agricultural ecological efficiency. (3) The consistency levels of all six configurations exhibited a declining trend in 2020, which may have been influenced by the COVID-19 pandemic and the broader economic environment; moreover, the coverage of these six configurations shows pronounced regional heterogeneity. (4) Under certain conditions, high market-based incentives and strong public participation can substitute for high-intensity government regulation. In addition, the scale of agricultural operations should be developed in a manner suited to local conditions and aligned with new-type urbanization and agricultural technological innovation. Conclusion: These findings provide empirical evidence for identifying which combinations of environmental regulations can be adopted across different regions of China to improve agricultural ecological efficiency.