Abstract: This paper studies how Chinese state aid affects U.S. soft power. We construct an annual, country-level measure of United States (U.S.) soft power based on UN General Assembly (UNGA) voting. For each country-year observation, we compare the ideal-point distance from the U.S. computed over all resolutions with the distance computed only over resolutions on which the U.S. State Department lobbied other countries. The difference between these two distances reflect the effect of U.S. influence on salient issues. To address possible endogeneity issues, we instrument with the cyclical overproduction of construction-related raw materials in China interacted with pre-determined cross-country differences in industrial structure. Estimates indicate that higher Chinese aid significantly reduces U.S. soft power: a one–standard-deviation increase in Chinese aid lowers our soft power index by roughly 60 percent of a standard deviation. This effect is substantially weaker in countries hosting U.S. troops, in countries that historically recognized Taiwan, and in countries more deeply integrated with the United States through trade, and it is stronger where long-run UNGA voting patterns reveal greater historical political distance from Washington. Taken together, the evidence suggests that Chinese financing erodes U.S. soft power primarily where the web of U.S. security, diplomatic, and economic ties is thin, while strong pre-existing ties anchor alignment and limit the extent to which Chinese resources can be converted into political influence at the expense of the United States.
Abstract: The paper presents a three-period model in which a bank aiming to minimize liquidation losses allocates deposits between two risky assets. Market liquidity conditions and depositors’ liquidity demand depend on the return of one of the two assets. In the event of a low return of this asset, a run on a solvent institution may occur, thereby creating liquidity risk. The model characterizes conditions such that the bank overweights the asset affecting market liquidity and depositors’ liquidity demand relative to the minimum variance portfolio. Although stylized, the model offers insight into the relationship between banks’ liquidity risk and asset allocations.