Legal knowledge involves multidimensional heterogeneous knowledge such as legal provisions, judicial interpretations, judicial cases, and defenses, which requires extremely high relevance and accuracy of knowledge. Meanwhile, the construction of a legal knowledge reasoning system also faces challenges in obtaining, processing, and sharing multisource heterogeneous knowledge. The knowledge graph technology, which is a knowledge organization form with triples as the basic unit, is able to efficiently transform multisource heterogeneous information into a knowledge representation form close to human cognition. Taking the automated construction of the Chinese legal knowledge graph (CLKG) as a case scenario, this paper presents a joint knowledge enhancement model (JKEM), where prior knowledge is embedded into a large language model (LLM), and the LLM is fine-tuned through the prefix of the prior knowledge data. Under the condition of freezing most parameters of the LLM, this fine-tuning scheme adds continuous deep prompts as prefix tokens to the input sequences of different layers, which can significantly improve the accuracy of knowledge extraction. The results show that the knowledge extraction accuracy of the JKEM in this paper reaches $90.92\%$. Based on the superior performance of this model, the CLKG is further constructed, which contains 3480 knowledge triples composed of 9 entities and 2 relationships, providing strong support for an in-depth understanding of the complex relationships in the legal field.

This paper investigates the relationship between China’s trade agreements (TAs) and partner countries’ upgrade in global value chains (GVCs). We focus on the experience of China and relate China’s TAs with one belt and one road (OBOR) initiative. A structural equation model (SEM) is applied on a dataset including 216 countries and regions to identify the direct and indirect effects of China’s TAs and OBOR initiative on its export, outwards foreign direct investment (OFDI) and partner economy’ GVCs upgrade over the period 2010–2015. We find that China’s TA partner countries are more likely to be included in the OBOR initiative than those non-TA partner countries. The positive effects of China’s TAs and OBOR initiative on China’s export, outwards foreign direct investment (OFDI) and partner countries’ upgrade in GVCs differ across country groups at the different locations of GVCs. Both vertical and horizontal spillover effects exist in China’s TAs. Therefore, the partner countries at low end and middle of GVCs might benefit more from TAs with China than those richer countries at the high end of GVCs.

This paper develops a growth model for a country under a Hobbesian environment with international conflicts where national defense is the only way to prevent external predation. Different defense strategies result in different growth paths. The long-run growth path is determined by the equilibrium of a dynamic game with three players: the external predator, the government, and the family. The equilibrium growth path can have different phases: submissive equilibrium, tolerant equilibrium, and complete protection equilibrium. Sustainable growth will endogenously induce an adjustment of the defense strategies. As the economy keeps growing, complete protection will eventually be preferred. The optimal growth path prefers to compress the length of the transitional period between incomplete protection and complete protection. Some interesting features of the transitional dynamics are exhibited by a control model with discontinuity.

We examine the effect of COVID-19 epidemic and the subsequent stay-at-home order on market efficiency in China’s online markets. Through a comparison of price dispersion changes across online retail platforms around the lockdown date with the corresponding period in the 2019 lunar year—with the use of a unique and extensive online retail price dataset—we find a counterintuitive decrease in product price dispersion during the epidemic, which is contrary to conventional economic expectations during adverse events. Our study differentiates products by crisis-time demand elasticity—e.g., food versus clothing—and by online search intensity. This reveals that the lockdown and prolonged stay-at-home period facilitated online searches by consumers, which reduced information costs and enhanced market efficiency. The pandemic-induced decrease in price dispersion can be largely attributed to heightened online search activity: after we adjust for the intensity of search, the remaining pandemic effect on price dispersion becomes positive. China’s resilient online market acted as a protective buffer during the COVID-19 crisis. The transition from offline to online markets and increased search activities bolstered online market functionality and mitigated the epidemic’s repercussions.