The impacts of oil price volatility on financial stress: Is the COVID-19 period different?

This study analyses the effects of oil price volatility on financial stress with various measures for a large panel of countries. The study places a special focus on comparing the pattern of these effects during the Great Recession period and the COVID-19 recession period. Using the local projection approach, the paper finds that oil price volatility has a positive and persistent effect on financial stress. However, the magnitude and the degree of persistency of oil price volatility impacts on financial stress are much greater for the Great Recession period than for the COVID-19 recession period. A possible explanation for this result would be that COVID-19 is better thought of as a "natural disaster” in which companies under stress were not being mismanaged. Another explanation would be that active intervention by the government through monetary and fiscal channels reduces the sensitivity of financial instability to oil price volatility during the COVID-19 period.

SA-FEM: Combined Feature Selection and Feature Fusion for Students' Performance Prediction.

Around the world, the COVID-19 pandemic has created significant obstacles for education, driving people to discover workarounds to maintain education. Because of the excellent benefit of cheap-cost information distribution brought about by the advent of the Internet, some offline instructional activity started to go online in an effort to stop the spread of the disease. How to guarantee the quality of teaching and promote the steady progress of education has become more and more important. Currently, one of the ways to guarantee the quality of online learning is to use independent online learning behavior data to build learning performance predictors, which can provide real-time monitoring and feedback during the learning process. This method, however, ignores the internal correlation between e-learning behaviors. In contrast, the e-learning behavior classification model (EBC model) can reflect the internal correlation between learning behaviors. Therefore, this study proposes an online learning performance prediction model, SA-FEM, based on adaptive feature fusion and feature selection. The proposed method utilizes the relationship among features and fuses features according to the category that achieved better performance. Through the analysis of experimental results, the feature space mined by the fine-grained differential evolution algorithm and the adaptive fusion of features combined with the differential evolution algorithm can better support online learning performance prediction, and it is also verified that the adaptive feature fusion strategy based on the EBC model proposed in this paper outperforms the benchmark method.

Moderating Role of Resilience Between Depression and Stress Response of Vocational Middle School Students During the COVID-19 Pandemic.

Object: In this study, we aimed to explore the influences of stress responses and psychological resilience on depression of vocational middle school students during the initial COVID-19 outbreak in China. Methods: An online questionnaire survey on the students of a medical school in Jiangxi Province, China, and obtained 3,532 valid questionnaires. A self-compiled general situation questionnaire, Stress Response of COVID-19 Questionnaire, the Resilience Scale for Chinese Adolescents and Center for Epidemiological Studies Depression Scale (CES-D) were used. Hierarchical regression analysis was used to explore the regulatory role of psychological resilience between stress response and depression. Results: (1) There were significant differences in gender between vocational middle school students' evaluation (t = 3.07, P = 0.002) and defense (t = 3.28, P = 0.001) of the pandemic. Males had higher cognitive evaluation of the pandemic than females, and females had more defense against the pandemic than males. (2) There is a significant difference between vocational middle school students from different grades in depression level (F = 3.62, P = 0.03), pneumonia defense (F = 13.65, P < 0.001) and pneumonia panic (F = 3.10, P = 0.045). (3) Depression level (F = 7.17, P < 0.001), pneumonia evaluation (F = 2.78, P = 0.04) and pneumonia panic (F = 3.32, P = 0.02) of the students concerning the spatial distance of the pandemic. (4) The severity of urban pandemic affects the evaluation of pneumonia among vocational middle school students. (5) Depression was negatively correlated with psychological resilience and pneumonia evaluation, and positively correlated with pneumonia panic. Psychological resilience was positively correlated with pneumonia evaluation and pneumonia defense, and negatively correlated with pneumonia panic. (6) Psychological resilience could reduce the level of depression caused by pneumonia evaluation and pneumonia panic. Conclusion: There were significant differences in depression level and stress responses in grades, gender and spatial distance of pandemic. Resilience has a significant negative moderator effect on the relationship between pandemic panic and depression. Resilience has a significant positive moderator effect on the relationship between pandemic evaluation and depression.

Time-varying impact of pandemics on global output growth.

This paper analyses the dynamic impact of uncertainty due to global pandemics (SARS, H5N1, H1N1, MERS, Ebola, and COVID-19) on global output growth, using a TVP-SVAR model. We find that the negative effect of the coronavirus on the growth rate of output is unprecedented, with the emerging markets being the worst hit. We also find that since 2016, the comovement among the growth rates has increased significantly. Our results imply that policymakers would need to undertake massive expansionary policies, but it is also important to pursue well-coordinated policy decisions across the economic blocs.