Analyzing the influence of external shocks on the pricing dynamics of the live pig industry chain is essential for effective macroeconomic control. Utilizing monthly data spanning from January 2010 to August 2023, this study employs the TVP-SV-VAR (Time-Varying Parameter—Stochastic Volatility—Vector Autoregression) model to analyze the effects of EPU (Economic Policy Uncertainty) and INU (Live Pig Industry News Uncertainty) on industry pricing. The findings are as follows: Firstly, the impacts of EPU and INU on industry prices exhibit time variability and distinct characteristics. Specifically, the impact magnitude of EPU ranges between [−0.025, 0.025], and that of INU between [−0.01, 0.01]. These differences in impact magnitude elicit varied responses from manufacturers and consumers to the indices. Secondly, uncertainty shocks at particular time points show high consistency, suggesting a patterned influence of external shocks on industry pricing that aligns with historical trends. Thirdly, robustness tests with alternative explanatory variables confirm the reliability of the findings. An uncertainty index, crafted from more comprehensive information sources, more accurately captures the effects of external shocks on industry pricing. Additionally, the volume of live pig slaughters illustrates the potential interaction between external shocks and pricing dynamics. In an era marked by increasingly frequent external shocks, this research offers valuable insights for policymakers to implement macro-control and foster high-quality industrial development.

Although many research has been done to understand the consequence of network structure on performance at the firm level, we have limited knowledge regarding how network structures influence alliance performance and how they interplay with partner attributes in this process. Focusing on the venture capital (VC) syndicate networks, we argue and show evidence for the positive influences of internal network density and external network structural hole on the performance of the investee startups. Moreover, we investigate how the features of lead and non-lead VC firms interact with the two network structural variables. The findings suggest that a big syndicate team augments the benefits of cooperation and coordination from a dense internal network, but a lead VC firm with high network status strengthens the information benefits from a high level of external network structural holes. Our cross-level research offers important implications on partner selection in strategic alliance research and the roles of lead and non- lead VC firms in VC studies.

The adoption of conservation agriculture techniques plays a crucial role in preventing soil erosion and guaranteeing food security. The purpose of this paper is to examine the impact of the adoption of conservation agricultural technologies on income. Based on the survey data of 922 households in five provinces and cities in the Bohai Rim region in 2023, the study analyzes the impact of different attributes of technology adoption on farm household income through ESR (endogenous switching regression) models and different forms of mediated effects models. The empirical results show the following: (1) The income effects generated by different adoption statuses of conservation agriculture (CA) technologies vary, and the income effects for farmers who adopt multiple conservation agriculture (CA) technologies jointly are even worse. (2) Farmers’ time allocation mediates the effects of technology attributes on adoption. Specifically, farm work is the main mediating variable, while off-farm work plays a moderating role between the yield effect and income. (3) The complex technology adoption chain inhibits farmers from increasing production and income, while the farmers’ jobs in the non-agricultural sector have reduced this impact to a certain extent. In terms of policy recommendations, governments should enhance technical training programs for farmers, improve the market environment, and offer access to highly mechanized agricultural production trusteeship services to encourage the greater adoption of conservation agriculture (CA) technology among farmers.

The quantity and quality of arable land are the basic prerequisites for food security; the arable land balance policy is a key measure to strictly protect farmland, and plays an important role in ensuring arable land use control, sustainable land use and reducing the contradiction between people and land. Drawing on panel data from 26 Chinese provinces spanning 2004 to 2017, this study employs the Nerlove supply response model to empirically examine the impact mechanism and regional heterogeneity of the arable land balance policy on the structure of grain crop cultivation, considering variations in land use following farmland supplementation. The findings reveal that the policy has induced fluctuations in grain crop structure, oscillating between “grain-oriented” and “non-grain-oriented” patterns. These shifts are primarily driven by the heterogeneous technological effects associated with farmland supplementation, which influence farmers’ planting decisions. Nonetheless, the policy has helped mitigate the adverse effects of farmland development on grain production, with the mitigation effect being more pronounced in non-major grain-producing regions. Furthermore, supporting measures such as land consolidation, outsourcing of agricultural services, and cross-regional mechanized operations have contributed to maintaining grain crop cultivation after land supplementation. Based on these findings, optimizing the arable land balance policy requires greater alignment with crop-specific production characteristics and regional farming practices. This includes refining the farmland supplementation coefficient and enhancing the policy’s differentiation mechanisms. Policy adjustments should also reflect the economic development levels and natural resource endowments of both major and non-major grain-producing regions, to promote a functional equilibrium in farmland utilization. Additionally, efforts to improve soil fertility and mechanization capabilities following land supplementation are essential to sustaining stable grain production. This study provides decision-making information support for optimizing the arable land balance policy and improving crop planting structure.

Exploring the influence of external shocks on the pricing dynamics of the live pig industry chain is essential for effective macroeconomic control. Utilizing monthly data spanning from January 2010 to August 2023, this study employs a Time-Varying Parameter - Stochastic Volatility - Vector Autoregression (TVP-SV-VAR) model to analyze the effects of Economic Policy Uncertainty (EPU) and Live Pig Industry News Uncertainty (INU) on industry pricing. The findings are as follows: Firstly, the impacts of EPU and INU on industry prices exhibit time variability and distinct characteristics. Specifically, the impact strength of EPU ranges between [-0.025, 0.025], and that of INU between [-0.01, 0.01]. These differences in impact strength elicit varied responses from manufacturers and consumers to the indices. Secondly, uncertainty shocks at particular time points show high consistency, suggesting a patterned influence of external shocks on industry pricing that aligns with historical trends. Thirdly, robustness tests with alternative explanat ory variables confirm the reliability of the findings. An uncertainty index, crafted from more comprehensive information sources, more accurately captures the effects of external shocks on industry pricing. Additionally, the volume of live pig slaughters illustrates the potential interaction between external shocks and pricing dynamics. In an era marked by increasingly frequent external shocks, this research offers valuable insights for policymakers to implement macro-control and foster high-quality industrial development.