The impact of environmental pollutants and climate indicators on the outbreak of COVID-19 has gained considerable attention in the recent literature. However, specific investigation of industrial economies like Germany is not available. This provides us motivation to examine the association between environmental pollutants, climate indicators and the COVID-19 cases, recoveries, and deaths in Germany using daily data from February 24, 2020, to July 02, 2020. The correlation analysis and wavelet transform coherence (WTC) approach are the analytical tools, which are used to explore the association between variables included in the study. Our findings indicate that PM2.5, O₃, and NO₂ have a significant relationship with the outbreak of COVID-19. In addition, temperature is the only significant climate indicator which has significant correlation with the spread of COVID-19. Finally, PM10, humidity, and environmental quality index have a significant relationship only with the active cases from COVID-19 pandemic. Our findings conclude that Germany’s successful response to COVID-19 is attributed to environmental legislation and the medical care system, which oversaw significant overhaul after the SARS and MERS outbreaks. The current study implicates that other industrial economies, especially European economies, that are still facing COVID-19 outbreak can follow the German model for pandemic response.

Introduction: In the current context of the COVID-19 pandemic, researchers are working with health professionals to inform governments to slow the virus’s spread. The extant research contribution has been dedicated to examining the impact of climate indicators such as temperature, humidity, and rainfall. However, there is a lack of evidence regarding their combined association between environmental quality and climate indicators to combat COVID-19 in the South American context. Methods: In this study, we collected data for environmental pollution indicators for the South America region, and correlation analysis and wavelet transform coherence were used as the analytical tools. Results: Empirical estimates conclude that PM₁₀, NO₂, CO, and O₃ are significant factors in the fight against the COVID-19 pandemic in South America. Implications: Our findings will serve as policy implications for the state, health officials, and regulators to combat the COVID-19 pandemic outbreak in South America.

Financing of sustainable development is a sophisticated and long-term process determined by a number of economic and non-economic factors. Financial instruments, private and public nature, exist that can be a source of financing of sustainable development. The choice of finance sources and instruments has an impact on the stability of economic systems and the efficiency of public expenditure with respect to sustainable development goals. The choice of financial instruments for financing development impact on financial stability and results in outcomes performed. The goal of the chapter is to examine relationships between financial stability reflected by public debt to gross domestic product (GDP) and sustainable development described by variables represented by three pillars of sustainable development: economic, social, and environmental. The role of environmentally related tax revenue has been identified as crucial for financing sustainable development goals.

Political risk factors have been considered as important factors which impact the foreign direct investment (FDI). But, the relationship between the political risk and FDI still not highly covered as expected. In this context, it is crucial to measure the political risk factors impact on the FDI especially for the Arab Spring countries which embraced radical political change after the revolution in 2011. This article aims to investigate the relationship between political risk and the FDI in Tunisia for the case of service sectors. The research is based on aggregate variables that represent six pillars of Governance Indicators. The data was extracted from the Worldwide Governance and the Tunisian Central Bank websites, the data frequency is yearly from 2004 to 2016. The research confirms that the political factors notably the government effectiveness and voice and accountability have significant impact on the FDI and on the FDI in the services sector.

In the last four decades, the female participation in the economic scene has registered a significant increase in all EU countries. However, on the one hand, men labour participation is higher than women's and on the other hand, there are gaps regarding pay and earnings by gender because women tend to work fewer hours and work in lower-paying sectors than men. The goal of this article is to point out the role of women in fostering the framework in the economy, with a special emphasis on the female labour force and entrepreneurship to support this scope and to provide evidence that the women have a positive impact on economic development. The article argues that the women contribute significantly in the economy development. The research sample consists of the European Union countries and the research was carried out for the period 1968-2017. The empirical part of the study is based on vector autoregressive model analysis.

Wavelets analysis has become a powerful mathematical tool to decompose a series and to provide its frequent and temporal features. Despite the fact that many researchers have begun testing this approach on financial and economic data to detect and treat outliers, it still not widely applied for longitudinal data. Therefore, this article proposes two algorithms for improving the accuracy of outlier detection in longitudinal data using Wavelets Decomposition, namely, Wavelets Decomposition for Outliers Detection and Handling across Subjects (WDODHAS), and Wavelets Decomposition for Outliers Detection and Handling within Subjects (WDODHWIS). The results show that Wavelets Decomposition is capable of detecting and handling outliers without erasing them, as well as highlighting hypothetical scenarios when these observations cannot be handled.