Template-Type: ReDIF-Article 1.0 Author-Name: Sheng Yao Author-Workplace-Name: Institute of Agricultural Economics and Information, Anhui Academy of Agricultural Sciences, Hefei, P.R. China Author-Name: Guosong Wu Author-Workplace-Name: School of Economics and Management, Huzhou University, Huzhou, P.R. China Title: Research on agricultural science and technology advancement enabling the development of rural industrial incorporation from the perspective of decomposition Abstract: Taking China as an example in this study, we aim to reveal the enabling effects of agricultural science and technology advancement on the progress of rural industrial incorporation at a relatively more refined level. The main innovation in this study lies in the decomposition of agricultural science and technology advancement, followed by an analysis of its effect on rural industrial incorporation along both linear and non-linear dimensions. The study results show that, along the linear dimension, agricultural science and technology advancement, agricultural knowledge advancement and agricultural technology advancement play significant driving roles in the progress of rural industrial incorporation. However, although the estimated coefficient of the integration of agricultural knowledge advancement and technology advancement is positive, it is not statistically significant. Along the non-linear dimension, agricultural science and technology advancement, agricultural knowledge advancement and agricultural technology advancement all exhibit significantly positive effects across different intervals. However, although the integration of agricultural knowledge advancement and technology advancement also shows a positive effect, its significance appears only in the second interval, indicating that the effect of this variable in promoting rural industrial incorporation can be realised only under certain conditions Keywords: agriculture, linear, non-linear, science, industry Journal: Agricultural Economics Pages: 308-322 Volume: 71 Issue: 6 Year: 2025 DOI: 10.17221/294/2023-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/294/2023-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202506-0001.txt Handle: RePEc:caa:jnlage:v:71:y:2025:i:6:id:294-2023-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: Meng Qin Author-Workplace-Name: School of Marxism, Qingdao University, Qingdao, P.R. China Author-Workplace-Name: Faculty of Economics and Business Administration, Doctoral School of Economics and Business Administration, West University of Timisoara, Timisoara, Romania Author-Name: Chi-Wei Su Author-Workplace-Name: School of Economics, Qingdao University, Qingdao, P.R. China Author-Workplace-Name: Faculty of Finance, City University of Macau, Macao, P.R. China Author-Name: Jinhao Cui Author-Workplace-Name: Qingdao Tongji Experimental School International Education Center, Qingdao, P.R. China Title: How have global pandemics destabilised the food market? Abstract: The paper explores the influence of global pandemic uncertainty (GPU) on food prices (FP) by using the mixed-frequency vector autoregression (MF-VAR) model. Empirical findings indicate that the influence of GPU on FP varies across different scenarios, exhibiting either positive, negative, or insignificant effects. A positive influence implies that GPU fuels panic-buying and stockpiling behaviours, thereby boosting food demand. Concurrently, disruptions in agricultural production and food export restrictions tighten the market supply, potentially pushing FP upwards. Conversely, a negative effect suggests that the global economic downturn and food safety anxieties stemming from pandemic-related uncertainty may dampen food demand, causing FP to decline. In some instances, FP remains unaffected mainly by GPU due to the competing pressures from adverse climate change risks on the food market. Notably, FP's predictive error variance decomposition underscores that the net impact of GPU on FP is stimulatory. This overall effect aligns with the inter-temporal capital asset pricing model (ICAPM), which posits a positive influence of GPU on FP. The findings recommend that consumers and investors diversify their food sources, while policymakers should bolster food supply chain resilience, promote sustainable agriculture, establish emergency reserves and coordinate aid. Keywords: COVID-19, food prices, world pandemic uncertainty, low-frequency model, mixed-frequency model Journal: Agricultural Economics Pages: 323-335 Volume: 71 Issue: 6 Year: 2025 DOI: 10.17221/323/2023-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/323/2023-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202506-0002.txt Handle: RePEc:caa:jnlage:v:71:y:2025:i:6:id:323-2023-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: Xiao Cheng Author-Workplace-Name: Institute of Chengdu-Chongqing Economic Circle Construction, Chongqing Technology and Business University, Chongqing, P.R. China Author-Workplace-Name: School of Economics, Chongqing Technology and Business University, Chongqing, P.R. China Title: Structural characteristics and determinants of the patent collaboration network in China's agricultural sector Abstract: Drawing upon data on co-signed patents in China's agricultural sector between 2015 and 2022, this paper explores the structural characteristics and determinants of the patent collaboration network in agricultural technology involving universities (U), enterprises (E) and research institutes (R). The results of social network analysis (SNA) revealed that the patent collaboration network is expanding in scale, but innovators are sparsely connected to others. Although the subnetwork linked by enterprises is the largest, universities and research institutes are more likely to play roles as hubs and bridges in the network. Furthermore, quadratic assignment procedure (QAP) regression revealed that prior collaboration experience and geographical proximity are key factors that promote co-patenting in the agricultural sector. Compared with U-U partnerships, E-E and E-R partnerships are associated with decreased patent collaboration. In the agriculture and forestry industries, the U-U and U-R partnerships are most likely involved in co-patenting, followed by the R-R and U-E partnerships. In the animal husbandry and fishery industries, no significant difference was found between the partnerships of U-U, R-R, U-E and U-R in their collaborative propensity. Keywords: patents, collaborative innovation, agriculture, proximity, social network analysis Journal: Agricultural Economics Pages: 285-297 Volume: 71 Issue: 6 Year: 2025 DOI: 10.17221/369/2024-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/369/2024-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202506-0003.txt Handle: RePEc:caa:jnlage:v:71:y:2025:i:6:id:369-2024-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: Xinyi Gu Author-Workplace-Name: School of Economics and Management, Jiangsu University of Science and Technology, Jiangsu, P.R. China Author-Name: Jianmin Li Author-Workplace-Name: School of Economics and Management, Jiangsu University of Science and Technology, Jiangsu, P.R. China Author-Name: Farzan Yahya Author-Workplace-Name: School of Economics and Management, Nanchang Institute of Technology, Jiangxi, P.R. China Author-Name: Muhammad Waqas Author-Workplace-Name: School of Economics and Management, Jiangsu University of Science and Technology, Jiangsu, P.R. China Author-Name: Amad Rashid Author-Workplace-Name: School of Management, Forman Christian College University, Lahore, Pakistan Title: Unintended consequences of trade in environmental innovation: Agricultural emissions, sectoral leakage, and the Kuznets curve hypothesis Abstract: Mitigating emissions from the agricultural sector is crucial for achieving sustainable development goals. However, controlling emissions in one sector can lead to unintended consequences in others through leakage effects. Grounded in the theoretical propositions of sectoral shift theory (SST), the rebound effect, and leakage effects, this study investigates the asymmetric impact of environmentally sound technology (EST) imports and exports on agricultural emissions (N₂O and methane) within the framework of the agricultural Kuznets curve (AKC). Utilising a balanced panel dataset of 105 countries from 2010 to 2020, we employ the Westerlund cointegration test to establish long-run relationships among variables. Method of Moments Quantile Regression (MMQR) estimations reveal a positive effect of EST imports and exports on agricultural N₂O emissions, intensifying the impact at higher quantiles. This suggests that industrial emission reductions through EST may have unintended consequences in agriculture via two mechanisms: emission leakage from industry to agriculture and increased agricultural emissions resulting from productivity improvements through the rebound effect. Nevertheless, in line with SST, our results indicate that sustainable agricultural trade can contribute to mitigating agricultural emissions. The AKC hypothesis holds across almost all models. These findings underscore the importance of developing tailored policies to design EST specifically for the agricultural sector, ensuring more effective emission reductions. Keywords: greenhouse gas emissions, environmental technology, quantile regression, rebound effect, carbon leakage, sustainable agriculture Journal: Agricultural Economics Pages: 298-307 Volume: 71 Issue: 6 Year: 2025 DOI: 10.17221/399/2024-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/399/2024-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202506-0004.txt Handle: RePEc:caa:jnlage:v:71:y:2025:i:6:id:399-2024-AGRICECON