This paper examines the relationship between financial literacy, an important factor in determining the financial behavior of households, and the borrowing behavior of Chinese households whose debt has been rapidly expanding. By using data from the China Household Finance Survey and dividing debt into different categories (business debt, housing debt, and consumer debt), this paper shows how financial literacy affects actual household debt accumulation and distribution. The main findings of this paper are as follows: (1) higher financial literacy is linked to household debt, while lower financial literacy is correlated with excessive debt, suggesting that financial literacy helps households to rationally manage their assets such as by effectively controlling household debt risk and reducing the risk of excessive debt; (2) financial literacy does not affect housing-related debt because the housing loan market in China is not competitive; and (3) financial literacy has a strong positive effect on consumption debt.

This paper demonstrates the important role that financial literacy plays in the rapidly expanding household finance market in China. Along with digital banking services provided by conventional commercial banks as well as borrowing services from small loans platforms such as Alibaba and Tencent, financial literacy is expected to become increasingly essential for consumers. Therefore, improving financial literacy can promote healthy borrowing behavior and reduce the risks associated with consumer finance and financial markets as a whole.

Mass organizations in Vietnam played a key role in the country’s achievement of independence from France, and since then, they have been assigned various tasks in different periods. However, the underlying rationale for their activities has remained essentially unchanged: to support the Communist one-party regime as an integral component of its political system. In the Doi Moi era, when there was decreasing need for mass mobilization for revolution, war, or collective production, mass organizations acquired some seemingly democratic or developmental functions, including representing their members’ interests or promoting mutual help activities among their members. In this way, these organizations are expected to remain relevant to their members and earn their loyalty as well as to continue to play their more traditional roles such as disseminating the Party line and informing the authorities about local situations, thus promoting the stability of the political regime. This paper focuses on the case of Vietnam’s largest and arguably the most active mass organization, the Vietnam Women’s Union. Based on a survey of its grassroots-level units, we attempt to show how it carries out its multiple tasks on a day-to-day basis and what challenges it faces, and provide a preliminary assessment of its ability to contribute to the stability of Vietnam’s socialist political regime.

Over the past few decades, comparativists have been increasingly combining cross-national statistical analysis with within-country case studies as a multi-method research design. This paper methodologically and empirically explores this mixed-method approach by focusing on issues such as (1) its methodological advantages and problems, (2) changes in the frequency of adoption, and (3) possible solutions to its problems. First, I identify where this type of mixed method currently stands in the field of comparative politics by reviewing Lieberman’s (2005) “nested analysis” design as well as the subsequent debates over this approach. Second, I investigate time trends of various mixed methods and their impacts on political science by analyzing new datasets of political science monographs and journal articles covering the period of 1995-2018. My analysis finds that, although there are remarkable differences in trends between monographs and journal articles, the nested analysis type of research has tended to increase over time, especially in the case of monographs. Lastly, while introducing cutting-edge research on comparative politics in the developing world, this article suggests that problems with the nested analysis design can be mitigated by applying causal inference techniques and big data methods to cross-national data analysis.