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This paper aims to improve the debate linking the business models of banks to their riskiness by checking if diversification exerts different impacts on the probability of bank distress depending on the level of capital buffers.

The paper focuses on a sample of listed bank holding companies observed between 2007:Q3 and 2022:Q4. The authors use three subindexes of bank diversification. The authors estimate a dynamic model specification using a system generalized method of moments with robust standard errors and consistent estimators under heteroskedasticity and autocorrelation within a panel. Sensitivity and robustness checks are performed.

Asset and income diversification increase the probability of distress in low-capitalized banks during normal periods (excluding periods of crises and high uncertainty). Concerning crisis periods, a marginal increase in asset diversification during the global financial crisis (GFC) and the COVID-19 pandemic crisis induces a more important increase in the probability of failure of well-capitalized banks relative to low-capitalized ones. Contrary to the results obtained for the GFC period, well-capitalized banks were found to pursue more careful funding diversification in reaction to the sudden increase of uncertainty during the Russia–Ukraine war.

Prudential supervision should concentrate on well-capitalized banks to encompass unexpected excessive risk-taking during crisis periods. Regulatory requirements should constrain fragile banks to avoid pursuing assets and income diversification strategies that increase earnings volatility.

The main originality of this paper is to consider the interaction between three different dimensions of bank diversification and capital regulation during stable and unstable periods using the marginal effect analysis. Moreover, this paper uses, initially, the GFC as the reference crisis period to study the impact of capital buffers and diversification interactions on the probability of bank distress. Then, the authors extend the observation period until 2022:Q4 to include two additional major events, namely, the COVID-19 pandemic and the Russia-Ukraine war.

This paper aims to contribute to the literature on the earnings management (EM)–corporate social responsibility (CSR) relationship as most of the previous studies have been carried out in non-turbulent periods. This study investigates whether CSR affects EM during the pandemic period by testing two hypotheses: the cognitive biases hypothesis and the resilience hypothesis

The difference-in-difference and triple difference approaches are used for a sample of 536 US firms (268 socially responsible firms and 268 matched non-socially responsible counterparts) during the 2017–2021 period. Socially responsible firms are selected from the MSCI KLD 400 Social Index, and matched firms are identified through the propensity score matching method.

The authors find an income-increasing practice for both socially responsible firms and control firms for the whole period and each sub-period. Moreover, socially responsible firms are more likely to manage their earnings (income increasing) than their counterpart. Furthermore, the authors show that CSR commitment exacerbated EM in line with the cognitive biases hypothesis.

This study is the first shed light on the dark side of CSR during pandemic periods.

This study aims to reveal to what extent successful European listed firms depend on their intellectual capital investment in achieving business success during the global financial crisis.

This study used value added intellectual coefficient (VAIC) methodology to measure the effect of intellectual capital on financial performance of business, which consist of 683 the sample listed firms. To examine the nexus between intellectual capital, legal origin and firm performance, estimated panel test and ordinary least squares regression model is used to data obtained from a sample of European countries.

The finding of this study suggests that there exists a positive relationship between intellectual capital and firm performance with return on assets (ROA) before the financial crisis, while firm performance with return on equity did not contribute to intellectual capital before and after the crisis period. Additionally, common law countries have a positive and statistically significant impact on firm performance with ROA for the before-crisis period, while code law countries have positively significant effect with VAIC on ROA.

The VAIC method has played a critical role in the management decision-making process to integrate the intellectual capital in the financial crisis period.

This study examines intellectual capital components such as human capital, structural capital and process capital efficiencies and firm performance in the legal origin context. The empirical evidence shows that there are significant impacts of legal origin on the nexus between intellectual capital and performance of listed firms during the global financial crisis.

In periods of economic distress, expectations for businesses change and there is a heightened need for reporting quality. This study investigates the impact of crises on earnings management in the real estate sector.

The data consisted of financial statements from 2005 to 2021 from real estate firms listed on 10 European stock exchanges. Estimated discretionary accruals from four standard accruals models were used as a proxy for earnings management, using cross-sectional industry and firm fixed effects models. The authors examined earnings management during three crises: the financial crisis (2008–2009), the debt crisis (2011–2012) and the COVID-19 pandemic (2020–2021).

The results showed less earnings management during the COVID-19 crisis and more earnings management during the financial crisis, though with slightly weaker evidence. The authors did not find significant evidence of earnings management related to the debt crisis. These results suggest that stakeholders in the real estate sector should be extra vigilant in crisis periods.

This study is the first to investigate earnings management in European real estate firms, focusing on the impact of crises.

This study is the first that aims to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

Multiple spatial weight matrices can capture the contiguity of spatial units from various dimensions, which could be exploited to improve the precision of inference as well as prediction accuracy. To the best of the authors’ knowledge, this is the first study to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

With network structure analysis, this study finds that they contain different information content from the perspective of graphical display, node strength and correlation. Developed and emerging countries all play major roles in trade connection, while only developed countries play major roles in financial linkage. Second, by applying the multidimensional SAR model, only the spatial autocorrelation coefficients for trade and financial linkages are significant during the full sample period, which is in sharp contrast to published studies using the SAR model with a single matrix. Third, the spillover channels that play major roles in various periods are different. Only trade channel plays a role during crisis periods and it is the most important. Fourth, the spatial correlation among countries greatly amplifies the shock’s impacts on one market. And spatial effect for developed countries is larger than those for emerging countries, while the mean spatial effect of a unit shock in the USA on emerging countries is slightly greater than that on developed countries.

Multiple spatial weight matrices can capture the contiguity of spatial units from various dimensions, which could be exploited to improve the precision of inference as well as prediction accuracy. To the best of the authors’ knowledge, this is the first study to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

This study analyses the impact of the Covid-19 on stock market performance of BRICS nations together. BRICS countries comprise almost 30% of the global GDP and around 50% of the world’s economic growth. As BRICS nations have gained the attraction as financial investment destinations, their financial markets have apparently been as potential opportunities for foreign portfolio investors. While there is extensive research on the impact of the Covid-19 pandemic on individual economies and global financial markets, this paper is among the first to systematically investigate the dynamic connectedness of these emerging economies during the pandemic using the Time-Varying Parameter Vector Autoregressions (TVP-VAR) approach.

We categorise our data into two distinct periods: the pre-Covid period spanning from January 1, 2018, to March 10, 2020, and the Covid crisis period extending from March 11, 2020, to June 4, 2021. To achieve our research objectives, we employ the Time-Varying Parameter Vector Autoregressions (TVP-VAR) approach to assess dynamic connectedness.

Our findings reveal that among the BRICS nations, Brazil and South Africa serve as net transmitters of shocks, while China and India act as net receivers of shocks during the Covid crisis. However, the total connectedness index (TCI) has exhibited a notable increase throughout this crisis period. This paper makes several notable contributions to the academic literature by offering a unique focus on BRICS economies during the Covid-19 pandemic, providing practical insights for stakeholders, emphasising the importance of risk management and investment strategy, exploring diversification implications and introducing advanced methodology for analysing interconnected financial markets.

The results have important implications for the investors, the hedge funds, portfolio managers and the policymakers in BRICS stock markets. The investors, investment houses, portfolio managers and policymakers can develop investment strategies and policies in the light of the findings of this study to cope up the future pandemic crisis.

This study is one of its kind that examines the dynamic connectedness of BRICS with recently developed TVP-VAR approach across pandemic crisis.

By conducting a longitudinal study, this study aims to investigate how the role of hotel attributes in destination competitiveness changed through the stages of pre-, amid and recovery from the crisis.

First, the latent Dirichlet allocation method was used to identify hotel attributes from 15,137 online reviews, and then a sentiment analysis was performed to determine tourist satisfaction with the subject attributes. Second, separate asymmetric impact competitor analyses were conducted for the three stages of the crisis, and their results were compared with understand how the role of the hotel attributes changed throughout the crisis.

The results revealed that the impacts of hotel attributes on tourist satisfaction and destination competitiveness differed significantly at each stage of the crisis.

This research expands the existing literature by offering valuable insights by elucidating the changing characteristics of hotel attributes at each crisis stage. The results extend the body of knowledge in destination management by providing evidence on the validity of asymmetric impact competitor analysis.

To fully understand the impact of a crisis (e.g. COVID-19) on destination competitiveness with a focus on the hotel sector, this research conducted a longitudinal study that covers three stages of the crisis (i.e. pre-, amid and post-crisis). Moreover, unlike previous studies, this research considers the asymmetric relationships between service attributes and overall tourist satisfaction, as well as competitors’ information.

This study aims to investigate the possibilities of cryptocurrencies as hedges and diversifiers in the Indian stock market before and during financial crisis due to the pandemic and the Russia–Ukraine war.

Researchers have used daily data on cryptocurrencies and Indian stock prices from March 10, 2015 to August 26, 2022. The researchers have used the dynamic conditional correlations (DCC)-GARCH model to determine the volatility spillover and dynamic correlation between stocks and digital currencies. Further, researchers have explored hedge ratio, portfolio weight and hedging effectiveness using the estimates of the DCC-GARCH model.

The findings indicate a negative conditional correlation between equities and cryptocurrencies before the crisis and a positive conditional correlation except for Tether during the crisis. Which implies that cryptocurrencies serve as a hedging asset in the stock market before a crisis but are not more than a diversifier during the crisis, except for Tether. Notably, Tether serves as a safe haven during times of crisis. Finally, the study suggests that Bitcoin, Ethereum, Binance Coin and Ripple are the most effective diversifiers for Indian stocks during the crisis.

This study makes several contributions to the existing literature. First, it compares the hedge and diversification roles of cryptocurrencies in the Indian stock market before and during crisis. Second, the study findings provide insights on risk hedging and can serve as a guide for investors. Third, it may help rational investors avoid underestimating risk while constructing portfolios, particularly in times of financial turmoil.

This study examines the impact of economic policy uncertainty (EPU) on the investment-cash flow sensitivity (ICFS) of Indian manufacturing firms.

This study uses the fixed-effect method to investigate the effect of EPU on ICFS from 2004 to 2019.

This study finds that EPU increases ICFS, which is more (less) during the crisis (before and post-crisis) period. The authors also find that the effect of EPU on ICFS is more for smaller, younger and standalone (SA) firms than the larger, matured and business group affiliated (BGA) firms. This study also reveals that EPU reduces corporate investment (CI). Further, the authors find that cash flow is more significant for the investment of financially constrained firms and the negative effect of EPU is more for these firms.

This study considers the Indian manufacturing sector. Therefore, this study can be extended by analyzing the relationship between EPU and ICFS for the service sector.

First, this study can be useful for corporates, academicians and government bodies to understand the effect of EPU on ICFS and CI. Second, this study will help corporates to focus on internal funds to finance corporates' investment during the crisis period because EPU increases the cost of external finance which may increase ICFS and reduce CI. Third, lending agencies, investors and stakeholders should also focus on the firm's nature, ownership, size and age because these factors play a crucial role to reduce or increase the negative effect of EPU on ICFS. Fourth, the Government should make appropriate policy measures in terms of concessional interest rates to increase the easy availability of external finance for SA, small size, and young firms to reduce the negative effect of EPU on CI because these firms are considered as more financially constrained firms.

This study adds new inputs to the current literature of EPU in several ways. First, this study is one of the main studies focused on the relationship between EPU and ICFS (CI). Especially in emerging countries like India, examining this relationship extends previous research. Second, this study also examines the impact of EPU on ICFS for BGA, SA, small, large, matured and young firms as well as crisis and non-crisis periods. Third, this study uses the sample of the Indian manufacturing sector which has emerged the qualities to become a global manufacturing hub and attracting global investors. Therefore, examining the effect of EPU on ICFS for these firms will be more interesting.

The purpose of this study is to examine the determinants of the level of indebtedness in the health sector in Portugal, taking into account the effects of the COVID-19 pandemic. At the same time, an attempt is made to understand whether the effect of a pandemic crisis is similar to that of a financial crisis.

To achieve this aim, two subperiods were analyzed: a global period between 2011 and 2020 that includes the pandemic crisis and the period between 2011 and 2014, designated as the financial assistance period by the “Troika” in Portugal. For a sample of 514 companies belonging to the NACE code: 86100 – activities of the health sector with hospitalization, the panel data methodology was applied, specifically, the generalized method of moments system proposed by Arellano and Bover (1995) and Blundell and Bond (1998).

The results of the study are in line with the Pecking-order explanatory theory, demonstrating that companies in this sector follow a financing hierarchy, preferentially resorting to internally generated funds and external debt. Additionally, the results reveal that the capital structure of companies has changed due to the COVID-19 pandemic. As for the period of financial assistance, there are no major differences in evidence when the total debt ratio is considered. The results suggest different impacts when it comes to a bear market period caused by a health crisis or a period of growing economic slowdowns.

As far as we know, this is the first study that analyses the debt levels in the context of the health sector in a country with a financial system based on the bank sector, using short- and long-term debt ratios, taking into account the particularities of two different moments considered to be bear market that may eventually be useful for comparison with other bear market moments in other macroeconomic environments.

El objetivo principal de este estudio es examinar los determinantes del nivel de endeudamiento en el sector de la salud en Portugal, teniendo en cuenta los efectos de la pandemia de COVID-19. Al mismo tiempo, se intenta comprender si el efecto de una crisis pandémica es similar al de una crisis financiera.

Para lograr este objetivo, se analizaron dos subperíodos: un período global entre 2011 y 2020 que incluye la crisis pandémica y el período entre 2011 y 2014, designado como el período de asistencia financiera por la “Troika” en Portugal. Para una muestra de 514 empresas pertenecientes al código NACE: 86100 – actividades del sector de la salud con hospitalización, se aplicó la metodología de datos de panel, específicamente, el método generalizado de momentos (GMM)-sistema propuesto por Arellano y Bover (1995) y Blundell y Bond (1998).

Los resultados del estudio están en línea con la teoría explicativa del “Pecking-order”, demostrando que las empresas en este sector siguen una jerarquía de financiamiento, recurriendo preferentemente a fondos generados internamente y deuda externa. Además, los resultados revelan que la estructura de capital de las empresas ha cambiado debido a la pandemia de COVID-19. En cuanto al período de asistencia financiera, no hay diferencias significativas en la evidencia cuando se considera la proporción total de deuda. Los resultados sugieren impactos diferentes cuando se trata de un período de mercado bajista causado por una crisis de salud o un período de crecimiento económico más lento.

Hasta donde sabemos, este es el primer estudio que analiza los niveles de deuda en el contexto del sector de la salud en un país con un sistema financiero basado en el sector bancario, utilizando ratios de deuda a corto y largo plazo, teniendo en cuenta las particularidades de dos momentos diferentes considerados como momentos de mercado bajista que eventualmente pueden ser útiles para comparar con otros momentos de mercado bajista en otros entornos macroeconómicos.

O principal objetivo deste estudo é examinar os determinantes do nível de endividamento no setor de saúde em Portugal, levando em consideração os efeitos da pandemia de COVID-19. Ao mesmo tempo, tenta-se compreender se o efeito de uma crise pandêmica é semelhante ao de uma crise financeira.

Para atingir esse objetivo, foram analisados dois subperíodos: um período global entre 2011 e 2020, que inclui a crise pandêmica, e o período entre 2011 e 2014, designado como o período de assistência financeira pela “Troika” em Portugal. Para uma amostra de 514 empresas pertencentes ao código NACE: 86100 – atividades do setor de saúde com hospitalização, foi aplicada a metodologia de dados em painel, especificamente o método generalizado de momentos (GMM)-sistema proposto por Arellano e Bover (1995) e Blundell e Bond (1998).

Os resultados do estudo estão de acordo com a teoria explicativa da ordem de preferência (“Pecking-order”), demonstrando que as empresas neste setor seguem uma hierarquia de financiamento, recorrendo preferencialmente a fundos gerados internamente e dívida externa. Além disso, os resultados revelam que a estrutura de capital das empresas mudou devido à pandemia de COVID-19. No que diz respeito ao período de assistência financeira, não há diferenças significativas na evidência quando se considera a proporção total de dívida. Os resultados sugerem impactos diferentes quando se trata de um período de mercado em baixa causado por uma crise de saúde ou um período de desaceleração econômica.

Até onde sabemos, este é o primeiro estudo que analisa os níveis de dívida no contexto do setor de saúde em um país com um sistema financeiro baseado no setor bancário, utilizando índices de dívida de curto e longo prazo, levando em consideração as particularidades de dois momentos diferentes considerados como momentos de mercado em baixa que eventualmente podem ser úteis para comparação com outros momentos de mercado em baixa em outros ambientes macroeconômicos.