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A banking system is essential for financial stability, especially economic growth and development. The authors investigate the dynamic linkage of key banking system stability measures, namely, liquidity, capital, profitability, and credit risk. To this end, the authors employ Panel Vector Autoregressive (VAR) to a panel data set of country-level banking system indicators from seven developing countries; from March 2010 to December 2020 (308 country quarter observations). A nation is selected on the basis of similar characteristics large and bank-based economy with the considerably same stage of economic development. The authors find a remarkable resilient feature of the banking system in which both liquidity risk and credit risk appears significant only in the short run (within three quarters). Shocks from both risk sources dissipate quickly, suggesting an internal mechanism is at work. This study provides evidence of how a good performance of financial safety net should be.

This Chapter undertakes an empirical analysis of the relationship between air transport demand and economic growth in Uruguay, Brazil, Argentina, and Chile, using annual data from 1970 to 2019. The results indicate a cointegration relationship between air passenger movements, real exchange rate, and GDP for Brazil and Uruguay, but not for Argentina, while for Chile bivariate cointegration exists. Moreover, exogeneity analysis and impulse response simulations show that in the long run there is a bidirectional causality between transport and economic growth for Uruguay, but for Brazil air transport is not influenced by GDP growth. Air transport is, however, positively affected in the long run by Chile's GDP growth. For Argentina, the probability of causality from air transport to economic growth is low and conversely is not significant.

Introduction: One of the main goals of the 2030 Agenda for Sustainable Development is to represent gender equality due to its essential role in sustainable progress. At the same time, the balance between women and men in management is explicitly mentioned as a desideratum, given that more women in leadership roles positively impact business performance and sustainability.

Purpose: The study investigates the dynamic relationship between gender inequalities in management positions and sustainable competitiveness. Our contribution is twofold: we examine this interrelationship and its causality.

Methodology: We used panel data of 350 observations for 2012–2021, and we employ a Vector Auto-Regression model and Granger causality method to examine the relationship between the gender gap in management and sustainable competitiveness. The panel VAR for analysing the impulse response function was enriched using Monte Carlo simulations with 5% and 95%.

Findings: The results highlighted that a bidirectional causality between the gender gap in management and sustainable competitiveness is manifested in the European countries. Our results are similar to other studies found in the literature, with gender equality and sustainability positively associated. As an element of originality, our study demonstrates that gender equality in management contributes to sustainable performance, and, on the other hand, a more competitive and sustainable environment contributes to eliminating the gap between men and women in management.

This chapter is devoted to sustainable human resource management that leads to sustainable competitiveness. It features the ways human resources can be managed to carry out sustainable goals and the impact of sustainability on employees' attitudes and behaviours. The aim of this study is to explore the complex objectives of sustainability and human resource management and empirically investigate the dynamic relationship between human resources in science and technology and sustainable competitiveness in the case of 35 European countries. Our contribution emphasizes this interrelationship and its causality. For this research, we applied a vector auto-regression (VAR) model, and the Granger causality method to examine the relationship between human resources in science and technology and sustainable competitiveness. A panel data included 314 observations between 2012 and 2021. The panel VAR for analysing the impulse response function was enriched with the 5% and 95%, using Monte Carlo simulations. The research results revealed bidirectional causality in the European countries between human resources in science and technology and sustainable competitiveness. Human resources in science and technology trigger sustainable competitiveness and vice versa. As an element of originality, our study demonstrates that human resources in science and technology contribute to sustainable performance, and, on the other hand, a more competitive and sustainable environment contributes to the development of human resources in science and technology. Thus, the chapter outlines the role of human resources in science and technology with regard to sustainable human resource management (HRM), and how to navigate these objectives so that they can positively influence sustainable competitiveness.

This chapter examines the impact of sectoral indebtedness on GDP in Czechia, initially a low-indebted small open economy in which debt dynamics are becoming a major concern. The impact of household debt, non-financial corporation debt and public debt is analysed with the use of local projections based on instrumental variable estimations. The results show a more pronounced influence of household debt compared to non-financial corporation and government debt. Initially, increasing household debt stimulates short-run economic activity, but in the medium run, it limits household consumption and negatively affects output. This negative impact gradually turns into a positive effect in the long run. Non-financial corporation debt has a negative short- to medium-run impact but can have a small positive effect in the long run due to the prevalence of tradable industries. Public debt initially has a short-run negative impact, but then gradually becomes positive. Overall, the findings have implications for macroeconomic policies and the importance of monitoring financial stability.

The COVID-19 pandemic has recently had an impact on the stock market all over the globe. A thorough review of the literature that included the most cited articles and articles from well-known databases revealed that earlier research in the field had not specifically addressed how the BRIC stock markets responded to the COVID-19 pandemic. The data regarding COVID-19 were collected from the World Health Organization (WHO) website, and the stock market data were collected from Yahoo Finance and the respective country’s stock exchange. A random forest regression algorithm takes the closing price of respective stock indices as target variables and COVID-19 variables as input variables. Using this algorithm, a model is fit to the data and is visualised using line plots. This study’s findings highlight a relationship between the COVID-19 variables and stock market indices. In addition, the stock market of BRIC countries showed a high correlation, especially with the Shanghai Composite Stock Index with a correlation value of 0.7 and above. Brazil took the worst hit in the studied duration by declining approximately 45.99%, followed by India by 37.76%. Finally, the data set’s model fit, which employed the random forest machine learning method, produced R² values of 0.972, 0.005, 0.997, and 0.983 and mean percentage errors of 1.4, 0.8, 0.9, and 0.8 for Brazil, Russia, India, and China (BRIC), respectively. Even now, two years after the coronavirus pandemic started, the Brazilian stock index has not yet returned to its pre-pandemic level.