The United Nations included reducing harvest losses as a Sustainable Development Goal in 2015, sparking heightened research and policymaker interest in reducing losses to ensure food security. High-standard farmland construction plays a crucial role in ensuring food security. Few studies have combined high-standard farmland construction with grain harvest losses. Drawing on the data from the 2022 Chinese Post-Harvest Loss Survey (CPHLS 2022), the study utilizes OLS (ordinary least square) and quantile regression models to explore the impact of high-standard farmland construction on grain harvest losses. Empirical results show that high-standard farmland construction can significantly reduce grain harvest losses. The research conclusions are still valid after passing a series of robustness tests. The heterogeneity analysis shows that high-standard farmland construction significantly impacts on grain harvest losses for farmers in major grain-producing areas, plain areas, and eastern regions. Mechanism analysis reveals that high-standard farmland construction mainly reduces grain harvest losses by expanding operational scale and enhancing mechanization application. Based on research findings, the Chinese government should formulate a targeted high-standard farmland construction policy, optimize the agricultural machinery operating environment, and promote appropriate operational scale to ensure national food security.

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.

This study utilizes a national database derived from large-scale surveys to examine the impact of staple food consumption patterns on household food waste in rural China. Using the Tobit model, the findings show that staple food consumption significantly influences food waste. Specifically, southern households, where rice is the staple food, waste 44% more food than their northern counterparts, where wheat is the staple. To address potential self-selection bias, the study employs the propensity score matching (PSM) model to validate the robustness of these results. Further heterogeneity analysis shows that the effect of staple food consumption on food waste is more pronounced in larger rural households with children. These results underscore the importance of dietary culture in explaining regional disparities in food waste across China.

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.