The effects of climate change, in combination with the recent energy crisis, have brought the energy efficiency issues of hospitals markedly to the fore. Hospitals are considered among the most energy-intensive buildings, which is why they have become a top priority for governments wishing to upgrade their energy efficiency. Given the critical nature of the work of hospitals and the model of healthcare provision (nursing cover 24 h per day, 7 days a week) it is very hard to achieve energy cuts. The international literature shows that the energy efficiency of hospitals is a complex process that requires further research. This need is covered by the present systematic literature review, which captures the existing knowledge on energy monitoring strategies, assessment, and upgrading through technology, resources-saving strategies, and the relationship between energy efficiency and the quality of the service provision, while also identifying future research considerations and the potential for supporting researchers’ work. Additionally, this study adds aggregated data to the literature, as far as the energy performance of buildings is concerned, and allows investors to have data exported from energy surveys at their disposal. At the same time, it suggests the further exploration of alternative energy technologies, based on all renewable energy sources rather than only solar power systems. This highlights the need for a comparative examination of hospitals with different climatic and socio-economic environments, to better determine what technologies effectively serve the energy needs of each region. Finally, this survey considers it necessary to connect the energy efficiency of hospital units with the awareness of the management and workforce in the saving of energy resources. Due to the fact that most studies are oriented toward the energy performance of very large-sized hospitals, it is suggested that in the future, the research lens should also be focused on the smaller private and public sectors’ health units.

Purpose: The research documented in this paper aims to examine multiple factors related to borrowers' default in peer-to-peer (P2P) lending in the USA. This study is motivated by the hypothesis that both P2P loan characteristics and macroeconomic variables have influence on loan performance. The authors define a set of loan characteristics, borrower characteristics and macroeconomic variables that are significant in determining the probability of default and should be taken into consideration when assessing credit risk.Design/methodology/approach: The research question in this study is to find the significant explanatory variables that are essential in determining the probability of default for LendingClub loans. The empirical study is based on a total number of 1,863,491 loan records issued through LendingClub from 2007 to 2020Q3 and a logistic regression model is developed to predict loan defaults.Findings: The results, in line with prior research, show that a number of borrower and contractual loan characteristics predict loan defaults. The innovation of this study is the introduction of specific macroeconomic indicators. The study indicates that macroeconomic variables assessed alongside loan data can significantly improve the forecasting performance of default model. The general finding demonstrates that higher percentage change in House Price Index, Consumer Sentiment Index and S&P500 Index is associated with a lower probability of delinquency. The empirical results also exhibit significant positive effect of unemployment rate and GDP growth rate on P2P loan default rates.Practical implications: The results have important implications for investors for whom it is of great importance to know the determinants of borrowers' creditworthiness and loan performance when estimating the investment in a certain P2P loan. In addition, the forecasting performance of the model could be applied by authorities in order to deal with the credit risk in P2P lending and to prevent the effects of increasing defaults on the economy.Originality/value: This paper fulfills an identified need to shed light on the association between specific macroeconomic indicators and the default risk from P2P lending within an economy, while the majority of the existing literature investigate loan and borrower information to evaluate credit risk of P2P loans and predict the likelihood of default.

Purpose: The authors examine the short-term stock market reaction surrounding US layoffs during the coronavirus disease 2019 (COVID-19) period. The authors’ specific interest is on any changes that may be observed in US stock markets during the COVID-19 outbreak. This information will help us assess the extent to which policymakers adopted at time revenue and expenditures measures to minimize its negative impact.Design/methodology/approach: The authors study the linkage between layoffs announced by firms and stock markets in US for the COVID-19 period between March 2020 and October 2020. This period shows important economic figures; a huge number of job cuts announced by blue-chip companies listed in the New York Stock Exchange (NYSE) due to widespread economic shutdowns. The authors examine whether and to what extent stock markets in US have reacted to layoff announcements during the COVID-19 pandemic using an event-study methodology.Findings: The study’s results show that US layoffs during the pandemic did not cause any abnormalities on the stock returns, either positive or negative. Based on the mean-adjusted volume, the authors find that layoffs increase the stocks' trading volume, especially on the event date and the day following the event. US stocks become more volatile on the days following the event. Interestingly, on the event date, the authors find that stocks get the highest abnormal volatility; however, the result is statistically insignificant.Practical implications: The authors suggest that layoffs announcements follow the business cycle quite closely in most industries. The study’s results have implications for investors, regulators and policymakers as they permit to examine the effectiveness of the measures adopted.Social implications: The study’s results show that policymakers reduced uncertainty implementing intensive measures quickly and should follow similar policy in the future pandemic and/or unexpected events.Originality/value: This paper contributes to the literature in two directions: First, to the best of the authors’ knowledge this is the first study that provides empirical evidence and assesses the extent to which a major global shock such as the COVID-19 pandemic may have altered the reaction of US stock markets to layoff announcements. Second, this is the first study on this topic that examines volume and volatility abnormalities, while the authors check the robustness of the findings with different methods to calculate abnormal returns.

The article examines the determinants of sovereign risk for European Monetary Union countries taking into consideration the global financial crisis, which emerged as a sovereign debt crisis in Europe. Using CDS prices, as a proxy of sovereign risk, this study finds that bond yields, equity prices and exchange rate are the key drivers of CDS prices. Moreover, our findings support models with dynamic components and regional effects between core and peripheral Eurozone countries, providing evidence of major differences in risk evaluation.

In this paper, we investigate the influential factors of Federal Housing Administration (FHA) mortgage loans, focusing our research interest on peer-to-peer (P2P) lending, the most successful FinTech lending model. We consider P2P lending an alternative source of financing that marginal borrowers use to pay the increased mortgage down payment, making them eligible to receive a mortgage from conventional banks. In other words, we examine whether and to what extent P2P lending has a positive impact on the FHA loans volume by providing the ability to circumvent the loan-to-value (LTV) cap policy. As a result, P2P lending can be seen as a means for ”rationed” borrowers to have access to the market by reducing inequalities and promoting financial inclusion, thus achieving Sustainable Development Goals (SDGs). We employ hand-collected data from FHA mortgages, P2P loans, and other economic factors from all 50 U.S. states during 2007–2017 and use panel data techniques for this purpose. Research shows that P2P lending, GDP per capita, population growth, broad money growth rate, interest rate, unemployment rate, new housing units, and consumer confidence Index produce effects on FHA loans. We show that P2P lending, a nonconventional determinant, is causally associated with a significant increase in the count and volume of FHA loans, implying that P2P lending has a positive impact on them. The ability of P2P to bypass mortgage supply constraints (tightened LTV caps) by providing small loans to borrowers to meet the increased down payment requirements is very important to policy-makers, as it shows that constraining the volume of mortgage loans may be not achieved. Macroprudential tools designed to control credit growth may prove ineffective, as the use of alternative forms of lending helps circumvent them and ultimately leads to excessive household leverage with all the risks that it poses to the financial system.