Implementing the strategy of expanding domestic demand is an inevitable choice for accelerating the formation of a new development paradigm, while optimizing the consumption structure serves as a crucial pathway to expanding domestic demand. Its strategic value has become increasingly prominent in driving economic structural transformation and achieving high-quality development. This paper focuses on analyzing the theoretical logic, practical basis, and implementation pathways through which the optimization of consumption structure contributes to expanding domestic demand. There are three findings. Firstly, the theoretical logic by which the optimization of consumption structure aids in expanding domestic demand lies in the upgrading of demand hierarchies, linkages with industrial structure, and innovation-driven development. Secondly, the practical basis for optimizing the consumption structure to support the expansion of domestic demand includes sustained growth in household incomes, a continuously increasing share of service consumption, ongoing release of demand for upgraded consumer goods, and the synchronization of urban and rural consumption structures. Thirdly, the implementation pathways for optimizing the consumption structure to help expand domestic demand involve enhancing residents ’ consumption capacity and confidence, meeting and creating new demand through innovation, improving institutional safeguards and optimizing the consumption ecosystem, and seeking breakthroughs in key areas while fostering new engines for driving consumption growth. This paper not only provides policy suggestions for expanding consumption demand and improving economic quality and efficiency, but also offers important references for enhancing people’s well- being.
The tariff-jumping theory posits that, when confronted with rising tariff barriers, firms increase their investment in the tariff-imposing country in order to circumvent the tariffs. We integrate data on Chinese firms’ cross-border mergers and acquisitions (M&A), export, and monthly product-level tariff data from 2018 to 2019. By constructing a shift-share instrumental variable (SSIV), we find that trade protectionism suppresses Chinese firms’ cross-border M&A—a finding that contradicts the traditional tariff-jumping hypothesis. This research identifies three potential mechanisms: (1) the Trump tariffs directly reduce firms’ operating performance; (2) the U.S. foreign investment security review process generates a demonstration effect; and (3) uncertainty arising from U.S.-China trade tensions weakens the bargaining power of Chinese firms.
The participation of foreign-invested enterprises in the formulation of national standards is taken as an opportunity to identify standards opening-up, and the impact of standards opening-up on local firms' innovation is examined. It is found that standards opening-up promotes local firms' innovation, works through collaboration between Chinese and foreign firms, market competition, and information transmission mechanism, and influences upstream and downstream innovation along the industrial chain. In addition, standards opening-up promotes firms’ product upgrading and exporting, standards harmonization, and foreign investment stabilization. These findings explain the significance of steady expansion of institutional opening-up.
Using comprehensive firm-level databases, we study the micro-basis of different trends in aggregate and individual labor shares in China's manufacturing sector during 1998-2016. We find that (1) redistributing value added towards the bottom of labor share distribution causes the decline of aggregate labor share; (2) the redistribution effect is driven by firms gradually increasing market share and reducing labor share; and (3) state-owned enterprises contribute significantly to the changes in aggregate labor share. The analysis of this paper enhances the understanding of the changes in China's labor share from the perspective of dynamic change of micro-firms.
Liking it or not, ready or not, we are likely to enter a new phase of human history in which artificial intelligence (AI) will dominate economic production and social life—the AI revolution. Before the actual arrival of the AI revolution, it is time for us to speculate on how AI will impact the social world. In this article, we focus on the social impact of generative LLM-based AI, discussing societal factors that contribute to its technological development and its potential roles in enhancing both between-country and within-country social inequality. There are good indications that the US and China will lead the field and will be the main competitors for domination of AI in the world. We conjecture that the AI revolution will likely give rise to a post-knowledge society in which knowledge per se will become less important than in today's world. Instead, individual relationships and social identity will become more important. So will soft skills, including the ability to utilize AI.
