Using a newly built soft power index, we examine whether and how soft power affects Chinese firm-level export to the Belt and Road (B&R) countries from 2000 to 2016. We find that soft power has significantly positive effects on both export value and export product types for the B&R countries. These effects are more pronounced than those for non-B&R countries and differ not only between the "Belt" and the "Road" countries but also regional groups, firm ownerships, modes of trade, and sectors. Further analysis shows that soft power increases the intensive margin of exports by approximately three times that of the extensive margin. Thus, our findings provide a new perspective for understanding both the Belt and Road Initiative (BRI) and the contemporary economic evolution occurring in China.

We study the impact of the COVID-19 pandemic shock on household consumption in China. Using household survey data, we find that the proportion of liquidity-constrained households increases quickly, but the constraint levels vary across distinct groups. We build a heterogeneous agent life cycle incomplete market model to analyze the long-run and short-run effects of the pandemic shock. The quantitative results reveal a slow recovery of consumption due to three reasons: hiking unemployment rate, declining labor productivity, and worsening income stability. The hiking unemployment rate plays the key role in households’ consumption reduction since it simultaneously leads to a negative income effect and upsurging precautionary saving motives. Our paper highlights the importance of maintaining a stable labor market for faster recovery.

Given the enormous impact that the COVID-19 pandemic had on China’s economy, helping companies to revitalize post-pandemic economic activities promptly is a priority for the whole society. This necessitates the smooth circulation of production-factors among different economic entities, departments, and regions. The pandemic’s huge impact on the economy is evident in the severely hampered flow of these factors, including labor, materials, and capital. Therefore, using data and digital technology, combined with a contact-free allocation of labor, capital, and materials, to accelerate the flow of production-factors is critical to the post-pandemic economy’s restoration. Such a policy can not only provide a short-term stimulus but also a momentum for China’s mid- and long-term sustainable economic development.

This paper studies the impact of an increase in higher education tuition on intergenerational mobility in China. We develop a theoretical model for the parental decision about the investment on education of children to illustrate the impact from the perspective of borrowing constraint. We consider the Chinese college tuition and subsidy reform around 1986 as a quasi-natural experiment for identifying the policy effect of the reform on intergenerational educational mobility by using the data from the census of 2000 and the China Family Panel Studies (CFPS). We find that an increase in the education burden induced by the reform of college tuition has reduced intergenerational educational mobility, and it is more noticeable in regions with a relatively higher increment in the tuition fee. Our results are robust with consideration of the co-residence bias, government investment in elementary education, and the higher education expansion.

This study analyzes the relationship between the age of first migration and the probability of repeat migration focusing on rural to urban migrants in China. It is based on the data of the 2015 Migrant Dynamics Monitoring Survey (MDMS). The data shows that 52.64% of migrants had experienced repeat migration before 2015, the amount of which is huge. The empirical results indicate an inverted U-shaped connection between age of first migration and the probability of repeat migration. The probability of making repeat migration from rural to urban areas reaches its peak if an individual experienced his/her first migration at around 16 years old. The probability for repeat migration continues to increase before the age of 16 and keeps dropping afterward. Additionally, this study explores the reason for this inverse U-shaped relationship, and it finds that reasons for first migration have great impacts. Specifically, the probability of repeat migration goes up with age if an individual first migrates before age 16 and is accompanied by parents. This probability decreases with age, if an individual first migrates after or at age 16, because of work.