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Han-Yu Zhu

Publications and source records attributed to Han-Yu Zhu.

3 recordsLinked to original sources

Import dependence and per capita production are main determinants of economies' food supply robustness under production shocks

Food supply shocks in major producing economies can propagate through trade networks and generate uneven impacts across the global food system. This study examines the robustness of economies' food supply under production shocks to major producers in the global staple food system. Using 2023 production, reserve, and bilateral trade data for wheat, rice, maize, and soybean, we construct a calorie-based global food supply network across economies. We extend a dynamic shock propagation framework and then simulate production shocks to major producing economies, tracing how supply losses propagate. The results show substantial heterogeneity in robustness across crops and economies. Wheat exhibits the highest overall robustness, whereas soybean shows the lowest. Economies with high robustness tend to be either relatively isolated from the trade network or actively engaged in trade while maintaining strong and stable domestic production, whereas low-robustness economies are predominantly those with high import dependence. Import dependence and per capita production emerge as the most important determinants of robustness. Based on these findings, we design two counterfactual policies targeting highly import-dependent economies: increasing reserve availability and adjusting trade linkages. Counterfactual experiments show that the two policies yield only modest overall improvements, with effects varying substantially across crops. Both policies improve robustness in the aggregated system and wheat, trade adjustment is more effective for rice, and it brings limited or even negative effects for maize and soybean.

econ.GN

Structural robustness of the international food supply network under external shocks and its determinants

The stability of the global food supply network is critical for ensuring food security. This study constructs an aggregated international food supply network based on the trade data of four staple crops and evaluates its structural robustness through network integrity under accumulating external shocks. Network integrity is typically quantified in network science by the relative size of the largest connected component, and we propose a new robustness metric that incorporates both the broadness p and severity q of external shocks. Our findings reveal that the robustness of the network has gradually increased over the past decades, punctuated by temporary declines that can be explained by major historical events. While the aggregated network remains robust under moderate disruptions, extreme shocks targeting key suppliers such as the United States and India can trigger systemic collapse. When the shock broadness p is less than about 0.3 and the shock severity q is close to 1, the structural robustness curves S(p,q) decrease linearly with respect to the shock broadness p, suggesting that the most critical economies have relatively even influence on network integrity. Comparing the robustness curves of the four individual staple foods, we find that the soybean supply network is the least robust. Furthermore, regression and machine learning analyses show that increaseing food (particularly rice and soybean) production enhances network robustness, while rising food prices significantly weaken it.

econ.GN

Uncovering the Sino-US dynamic risk spillovers effects: Evidence from agricultural futures markets

Agricultural products play a critical role in human development. With economic globalization and the financialization of agricultural products continuing to advance, the interconnections between different agricultural futures have become closer. We utilize a TVP-VAR-DY model combined with the quantile method to measure the risk spillover between 11 agricultural futures on the futures exchanges of US and China from July 9,2014, to December 31,2022. This study yielded several significant findings. Firstly, CBOT corn, soybean, and wheat were identified as the primary risk transmitters, with DCE corn and soybean as the main risk receivers. Secondly, sudden events or increased economic uncertainty can increase the overall risk spillovers. Thirdly, there is an aggregation of risk spillovers amongst agricultural futures based on the dynamic directional spillover results. Lastly, the central agricultural futures under the conditional mean are CBOT corn and soybean, while CZCE hard wheat and long-grained rice are the two risk spillover centers in extreme cases, as per the results of the spillover network and minimum spanning tree. Based on these results, decision-makers are advised to safeguard against the price risk of agricultural futures under sudden economic events, and investors can utilize the results to construct a superior investment portfolio by taking different agricultural product futures as risk-leading indicators according to various situations.

econ.GN