This paper introduces novel data on public sentiment towards economic sanctions based on nearly 1 million social media posts in 108 countries during the Russia–Ukraine war by using machine learning. We show the geographical heterogeneity between government stances and public sentiment. Finally, we show how political regimes, trading relationships and political instability can predict how people perceive this war.

The impact of monetary policy on bank performance and risk is driven by bank individual characteristics and the COVID-19 pandemic, and the joint effect of bank individual factors and the coronavirus has been under-researched so far. To fill this void, this research applies the dynamic two-step system generalized method of moments (S-GMM) estimator to a sample of representative commercial banks on a quarterly basis for a small open emerging market such as Vietnam. We find that monetary policy expansion stimulates both banks’ performance and risk in a COVID-19 pandemic. Interestingly, the effectiveness of monetary policy expansion on banks’ operating outcomes is dependent on the interaction between the heterogeneity of the bank’s balance sheet items and the COVID-19 outbreak. More specifically, the performance-decreasing effects of monetary policy loosening are more pronounced in banks with small size, high liquidity, low capitalization, and high credit risk in the shadow of the COVID-19 crisis. Meanwhile, the risk-increasing impacts of monetary policy easing are conspicuous in well liquid, less capitalized, and high credit risk banks in an uncertain time of the COVID-19 crisis. These results are robust to alternative proxies of monetary policy instruments.