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The COVID-19 pandemic and induced economic and social constraints have significantly impacted the confidence of both consumers and businesses. Despite that, comprehensive studies of the impact of the COVID-19 pandemic on the consumer and business sentiment are still lacking. Thus, in our research we aim to identify consumer and business confidence indicators’ reaction to the spread of the COVID-19 pandemic in the Eurozone, the United States, and China. For this purpose, we used the method of correlation–regression analysis. We chose the consumer-confidence index, manufacturing purchasing manager’s index, and services purchasing manager’s index as dependent variables; and the number of confirmed cases of COVID-19, the number of deaths caused by COVID-19, and the mortality rate of COVID-19 infections as independent variables. The results showed a relatively rapid and robust effect of COVID-19 in the short period, but longer-term results depended on the region and were not so unambiguous: in the case of the Eurozone, the spread of COVID-19 pandemic did not affect the consumer-confidence index (CCI) or, in the cases of the United States and China, affected this index negatively; the purchasing managers’ index (PMI) in the services sector was significantly negatively affected by the mortality risk of COVID-19 infection; and the impact on the purchasing managers’ index (PMI) in the manufacturing industry appeared to be mixed.

In this research, trade credit is analysed form a seller (supplier) perspective. Trade credit allows the supplier to increase sales and profits but creates the risk that the customer will not pay, and at the same time increases the risk of the supplier’s insolvency. If the supplier is a small or micro-enterprise (SMiE), it is usually an issue of human and technical resources. Therefore, when dealing with these issues, the supplier needs a high accuracy but simple and highly interpretable trade credit risk assessment model that allows for assessing the risk of insolvency of buyers (who are usually SMiE). The aim of the research is to create a statistical enterprise trade credit risk assessment (ETCRA) model for Lithuanian small and micro-enterprises (SMiE). In the empirical analysis, the financial and non-financial data of 734 small and micro-sized enterprises in the period of 2010–2012 were chosen as the samples. Based on the logistic regression, the ETCRA model was developed using financial and non-financial variables. In the ETCRA model, the enterprise’s financial performance is assessed from different perspectives: profitability, liquidity, solvency, and activity. Varied model variants have been created using (i) only financial ratios and (ii) financial ratios and non-financial variables. Moreover, the inclusion of non-financial variables in the model does not substantially improve the characteristics of the model. This means that the models that use only financial ratios can be used in practice, and the models that include non-financial variables can also be used. The designed models can be used by suppliers when making decisions of granting a trade credit for small or micro-enterprises.

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All countries worldwide faced the COVID-19 pandemic and had to take actions to lower the economic shock. Financial authorities play an especially significant role in economics and can help to manage the negative consequences. This article focuses on the European central bank monetary policy and actions taken for COVID-19 risk management. This research aims to identify the significant factors influencing the long-term loans for enterprises’ credit conditions in a forward-looking approach and determine the impact of the spread of COVID-19 pandemic on banking sector credit risk, financial distress, lending growth, and financial soundness indicators. This research is focused on the credit transmission channel and the role of the Pandemic Emergency Purchase Program in different countries of the euro area. To reach the main goal, panel data regression models are used. Our findings showed that the banks’ risk tolerance is a principal factor influencing long-term loan credit standards. We also identified that the spread of the COVID-19 pandemic has a statistically significant negative effect on banking sector credit risk, financial distress, banking sector profitability, and solvency. Furthermore, after analyzing the euro area banking sector, we found that liquidity increased. Hence, it means that banks have enough funds to support sustainable economic growth, but on the other side, commercial banks do not want to take credit risk because of their risk tolerance. Our research findings show the mixed effect of the COVID-19 pandemic on financial stability: while the overall financial distress decreased and banking sector liquidity increased, the profitability and solvency decreased some extent.