Using an international sample of banks, we study how differences in religiosity across countries affect earnings management. Given that religiosity is a major source of morality and ethical behavior, it may reduce excessive risk taking and act as deterrence for earnings manipulations. Therefore, we predict lower earnings management in societies that have higher religiosity. Consistent with expectations, our cross-country analysis indicates that religiosity is negatively related to income-increasing earnings management for loss-avoidance and just-meeting-or-beating prior year’s earnings. We also find that (...) religiosity reduces income-increasing earnings management through abnormal loan loss provisions. In additional tests, we document that religiosity increases the information value of bank earnings, with both earnings persistence and cash flow predictability being enhanced by higher religiosity. For the crisis period analysis, our evidence shows that banks in countries with higher religiosity exhibit lower probability of reporting asset deterioration and lower probability of having poor performance. (shrink)

The COVID-19 pandemic has caused tremendous loss starting from early this year. This article aims to investigate the change of anxiety severity and prevalence among non-graduating undergraduate students in the new semester of online learning during COVID-19 in China and also to evaluate a machine learning model based on the XGBoost model. A total of 1172 non-graduating undergraduate students aged between 18 and 22 from 34 provincial-level administrative units and 260 cities in China were enrolled onto this study and asked (...) to fill in a sociodemographic questionnaire and the Self-Rating Anxiety Scale twice, respectively, during February 15 to 17, 2020, before the new semester started, and March 15 to 17, 2020, 1 month after the new semester based on online learning had started. SPSS 22.0 was used to conduct t-test and single factor analysis. XGBoost models were implemented to predict the anxiety level of students 1 month after the start of the new semester. There were 184 and 221 students who met the cut-off of 50 and were screened as positive for anxiety, respectively, in the two investigations. The mean SAS scores in the second test was significantly higher than those in the first test. Significant differences were also found among all males, females, and students majoring in arts and sciences between the two studies. The results also showed students from Hubei province, where most cases of COVID-19 were confirmed, had a higher percentage of participants meeting the cut-off of being anxious. This article applied machine learning to establish XGBoost models to successfully predict the anxiety level and changes of anxiety levels 4 weeks later based on the SAS scores of the students in the first test. It was concluded that, during COVID-19, Chinese non-graduating undergraduate students showed higher anxiety in the new semester based on online learning than before the new semester started. More students from Hubei province had a different level of anxiety than other provinces. Families, universities, and society as a whole should pay attention to the psychological health of non-graduating undergraduate students and take measures accordingly. It also confirmed that the XGBoost model had better prediction accuracy compared to the traditional multiple stepwise regression model on the anxiety status of university students. (shrink)

Figure originale de la pensée chinoise, Wang Chong passe en revue, dans cet ouvrage, les conceptions de son temps. Alors que dans leur majorité les penseurs chinois se préoccupent en priorité de morale, il se donne un programme d'ordre épistémologique : la lutte contre l'erreur et le mensonge.

pt. 1. Philosophical essays -- pt. 2. Miscellaneous essays.

外十一种包括:风俗通义/(汉)应劭撰·封氏闻见记/(唐)封演撰·尚书故实/(唐)李绰撰·灌畦暇语/(唐)不著撰人·春明退朝录/(宋)宋敏求撰·宋景文笔记/(宋)宋祁撰·东原录/(宋)龚鼎臣撰·王氏谈录 /(宋)王钦臣撰·麈史/(宋)王得臣·文昌杂录/(宋)庞元英撰·梦溪笔谈/(宋)沈括撰.

Lun heng / Wang Chong zhuan -- Feng su tong yi / Ying Shao zhuan -- Feng shi wen jian ji / Feng Yan zhuan -- Shang shu gu shi / Li Chuo zhuan -- Guan qi xia yu / bu zhao zhuan ren -- Chun ming tui chao lu / Song Minqiu zhuan -- Song Jingwen bi ji / Song Qi zhuan -- Dong yuan lu / Gong Dingchen zhuan -- Wang shi tan lu / Wang Qinchen zhuan -- (...) Zhu shi / Wang Dechen zhuan -- Wen chang za lu : bu yi / Pang Yuanying zhuan -- Mengxi bi tan : bu bi tan / Shen Kuo zhuan. (shrink)