Purpose: This paper aims to examine the effects of CO₂emissions, energy consumption, cultivated area and the labour force on the production of cereal crops in Pakistan from the period 1971-2014.Design/methodology/approach: The study used the Johansen cointegration test, the autoregressive distributed lag (ARDL) approach and Granger causality test to estimate the long-run cointegration and direction of the relationship between the dependent and independent variables.Findings: The outcomes of the Johansen cointegration test confirmed the existence of a long-term cointegrating relationship between the production of cereal crops, CO₂emissions, energy consumption, cultivated area and the labour force. The results of the long-run coefficients of CO₂emissions, energy consumption, cultivated area and labour force have a positive impact on cereal crops production. The long-run relationships reveal that a 1 per cent increase in CO₂emissions, energy consumption, cultivated area and labour force will increase cereal crops production by 0.20, 0.11, 0.56 and 0.74 per cent, respectively. Moreover, the findings show that there is a bidirectional causality running from CO₂emissions and cultivated area to cereal crops production. Moreover, there is a unidirectional causality running from energy consumption to cereal crops production.Originality/value: The present study also fills the literature gap for applying the ARDL procedure to examine this relevant issue for Pakistan.

On April 30, 2019, a forest fire broke out in Liangshan Prefecture that resulted in the deaths of 27 firefighters and four local officials, which sparked a heated debate on the Weibo social media site. Therefore, this case was chosen to examine the evolution of disaster-induced public internet opinion in China to reduce the possibility of ‘secondary harm’ to victims and the risk of panic, and to promote administrative transparency. Life cycle theory, social network analysis, and crawler technology were applied to examine the public online discussion, from which it was found that: female contributors were more likely to share information and feelings on social media than males; people in coastal areas contributed more to the conversations than people from the central and western regions; opinion leaders with significant influence played guiding roles in the discussion; and influential users in various fields, and especially internet celebrities and fan leaders, affected the speed of the information dissemination. From the results, some practical recommendations were developed: social media could be used to retrieve valuable information to help determine disaster damage and plan disaster relief, and government agencies need to strengthen their interactions with the general population, rather than only providing one-way communication.

One of the effective ways to crack the “Three Rural Issues” and promote rural revitalization is to improve agricultural labor productivity (ALP). However, at this stage, improving China’s ALP is still facing many obstacles and bottlenecks. Promoting migrant workers returning home for entrepreneurship is an important breakthrough point for solving this problem. This paper regards the pilot policy of migrant workers returning home for entrepreneurship as a quasi-natural experiment and empirically investigates the influence of migrant workers returning home for entrepreneurship on ALP and explores its potential mechanism and heterogeneity using county area panel data from 2011–2019. It found the following: Firstly, the policy of migrant workers returning home for entrepreneurship significantly increases ALP. Secondly, migrant workers returning home for entrepreneurship indirectly leads to a rise in ALP through the promotion of agricultural mechanization production. Thirdly, the heterogeneity test demonstrates that migrant workers returning home for entrepreneurship purposes have a significant influence in enhancing ALP in the eastern areas, plains areas and non-agricultural strong areas. The findings of this paper not only provide an important real-world basis for the government to further support migrant workers returning home for entrepreneurship but also provide useful policy insights for the modernization and development of agriculture and rural areas.

(1) Studying the driving factors and spatiotemporal characteristics of China’s regional animal husbandry emissions is highly relevant to policy formulation. (2) Methods: We calculated the total CO₂ equivalent emissions of animal husbandry across the country and each province separately, and then used the Logarithmic Mean Divisia Index (LMDI) to analyze how the driving forces of animal husbandry emissions changed across the country and in different provinces from 2001 to 2019. (3) Results: ① During the period 2001–2019, national animal husbandry carbon emissions showed an overall downward trend. Economic growth and population contributed positively to the emissions (which means more CO₂), while technological advancement, structural change in agriculture, and change in the national industrial structure had negative effects (which means less CO₂). ② Using aspects of provincial animal husbandry, we categorized 31 provinces into four types: fluctuating rising, fast falling, slow falling, and steadily falling. Then, according to the magnitude of the different driving forces in different provinces, we classified 31 provinces into three types: economic structure adjustment-driven, technological progress-driven, and economic growth-driven. ③ The driving effects of agricultural structural change and population in some provinces are not consistent with the effects shown at the national level.

With the rapid evolution of the rural digital economy, analyzing the impact of digital literacy level on farm households’ formal borrowing is crucial for easing credit constraints and fostering rural economic growth. Leveraging the data from the 2020 China Family Panel Studies (CFPSs) and applying binary probit models and the Karlson–Holm–Breen (KHB) method, this study delineates the positive correlation between the digital literacy level and increased formal borrowing among farm households. The findings, which were robust against endogeneity and robustness tests, underscore the role of digital literacy level in augmenting farmers’ earnings and social networks, with a notably stronger mediation by earnings. The effects are particularly significant for middle-aged and older, less educated males in the central and western regions, in contrast with younger, highly educated females in the east. This research advocates for enhancing rural digital infrastructure and education, alongside financial system reforms, to advance rural financial development and support sustainable rural revitalization.