Green bond market boom: did environmental, social and governance criteria play a role in reducing health-related uncertainty?

Recent years have been characterized by considerable growth of the green bond market in Europe, particularly in the domain of social bond issuance. Considering the recent pandemic, it is also a stylized fact that this growth is positively correlated with the concept of health-related uncertainty, as the green bond market aims to acquire financing in order to allow the development of projects that comply with the so-called environmental (E), social (S) and governance (G) criteria. This study then applies a dynamic spatial econometric analysis and several robustness checks to assess the extent to which each E, S and G criterion contributes to the societal dynamics of health-related uncertainty. The analysis takes advantage of available data on the number of confirmed cases of COVID-19 to measure health-related uncertainty at the municipal level, so that a higher (lower) number of confirmed cases constitutes a proxy for a greater (smaller) degree of uncertainty, respectively. To reinforce the need to evaluate impacts in a context characterized by health-related uncertainty, the time span covers the first wave of COVID-19, which is the period when uncertainty reached its highest peak. Additionally, the geographical scope is mainland Portugal since this country has become a breeding ground for startups and new ideas, being currently one of the world leaders in hosting businesses that reached Unicorn status. The main result of this research is that only the social dimension has a significant, positive and permanent impact on health-related uncertainty. Therefore, this study empirically confirms that the European green bond market has been and can be further leveraged by the need to finance projects with a social scope.

Driving Factors and Scale Effects of Residents' Willingness to Pay for Environmental Protection under the Impact of COVID-19

In recent years, environmental degradation and the COVID-19 pandemic have seriously affected economic development and social stability. Addressing the impact of major public health events on residents' willingness to pay for environmental protection (WTPEP) and analyzing the drivers are necessary for improving human well-being and environmental sustainability. We designed a questionnaire to analyze the change in residents' WTPEP before and during COVID-19 and an established ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), and multiscale GWR to explore driver factors and scale effects of WTPEP based on the theory of environment Kuznets curve (EKC). The results show that (1) WTPEP is 0–20,000 yuan before COVID-19 and 0–50,000 yuan during COVID-19. Residents' WTPEP improved during COVID-19, which indicates that residents' demand for an ecological environment is increasing;(2) The shapes and inflection points of the relationships between income and WTPEP are spatially heterogeneous before and during COVID-19, but the northern WTPEP is larger than southern, which indicates that there is a spatial imbalance in WTPEP;(3) Environmental degradation, health, environmental quality, and education are WTPEP's significant macro-drivers, whereas income, age, and gender are significant micro-drivers. Those factors can help policymakers better understand which factors are more suitable for macro or micro environmental policy-making and what targeted measures could be taken to solve the contradiction between the growing ecological environment demand of residents and the spatial imbalance of WTPEP in the future.

SOCIAL CAPITAL AND SPREAD OF COVID-19 IN POLAND – DO MEMBERSHIP, TRUST, NORMS AND VALUES OR SHARED NARRATIVES MATTER?

The experience of the SARS-CoV-19 pandemic can be a source of valuable information for public health authorities. As we have seen, the incidence is not evenly distributed in space, and the factors influencing it are not fully understood. Aspects of biological, demographic, economic, environmental, and political nature are considered, but it is believed that the social factor may be of critical importance. The density and intensity of social relations, general trust and trust in the authorities, norms and values – i.e., social capital – may have a key impact on the scale of infections. The research conducted so far on this subject does not provide clear conclusions, and the post-communist society, inferior in social capital, has hardly been analyzed. Using data for 73 subregions of Poland and performing regression analysis, we investigate how social capital explains the level of infection rate in the first three waves of the epidemic. The analysis results have shown that the factor of "political leaning” was strongly and negatively related to the infection rate in Poland. The research results indicate that, contrary to the previous studies, structural capital has the same positive effect on reducing the epidemic. However, relational social capital promotes more significant morbidity. © 2022, Centre of Sociological Research. All rights reserved.

International spillover of economic policy uncertainty and its transmission channels: a spatial econometrics method

This paper employs a spatial econometrics method to study the international spillovers of economic policy uncertainty (EPU), and contributes to the literature by exploring the transmission channels. We comprehensively consider bilateral trade, financial investment, and information channels (government liability, trade imbalance, fiscal imbalance, business cycle). Based on a large sample of 21 countries from 2001Q1 to 2021Q4, our analysis indicates that the channels proposed are all significantly effective, and bilateral trade contributes the most. We also investigate the dominant channels during five crisis and non-crisis periods: in the global financial crisis, financial investment and government liability similarity are of utmost importance;in European debt crisis, bilateral trade and information channels of government liability and business cycle are the main channels;before these crises, the dominant channel is financial investment, which turned to be bilateral trade in the post-crises period;in COVID-19 pandemic, financial investment is the most important.

Socio-economic and demographic factors influencing the spatial spread of COVID-19 in the USA

As the COVID-19 pandemic progressed in the USA, ‘hotspots' shifted geographically over time to suburban and rural counties showing a high prevalence of the disease. We analyse population-adjusted confirmed case rates based on daily US county-level variations in COVID-19 confirmed case counts during the first several months of the pandemic (1 March 2020 through 23 May 2020) to evaluate the spatial dependence between neighbouring counties and quantify the overall spatial effect of socio-economic and demographic factors on the prevalence of COVID-19. We indeed find strong evidence of county-level socio-economic and demographic factors influencing the spatial spread such as sex, race, ethnicity, population density, pollution, health conditions, and income. The relevance of the spatial factors suggests that neighbouring counties have a significant and positive effect on the prevalence of COVID-19. Copyright © 2022 Inderscience Enterprises Ltd.

Socio-economic and demographic factors influencing the spatial spread of COVID-19 in the USA

As the COVID-19 pandemic progressed in the USA, 'hotspots' shifted geographically over time to suburban and rural counties showing a high prevalence of the disease. We analyse population-adjusted confirmed case rates based on daily US county-level variations in COVID-19 confirmed case counts during the first several months of the pandemic (1 March 2020 through 23 May 2020) to evaluate the spatial dependence between neighbouring counties and quantify the overall spatial effect of socio-economic and demographic factors on the prevalence of COVID-19. We indeed find strong evidence of county-level socio-economic and demographic factors influencing the spatial spread such as sex, race, ethnicity, population density, pollution, health conditions, and income. The relevance of the spatial factors suggests that neighbouring counties have a significant and positive effect on the prevalence of COVID-19.

Does geographical proximity matter in determining the profitability of banks?

Despite the existence of a burgeoning literature on bank profitability, yet, none of them gave due consideration to geographical proximity. We fulfill such a gap by analyzing the effects of COVID-19 on the profitability of top-rated banks. Findings confirm the prevalence of spatial dependence at both the global and sub-global with feedback effects being systematically higher than spillover effects. Our study uncovers evidence of a COVID-19 induced decline in asset utilization. Findings advocate sharing economy as a potential tool to banks in combating any future pandemic risk with regionalized approach to supervision being deemed better than its globalized counterpart. © 2022 The Society for Policy Modeling

Internet access and its role on educational inequality during the COVID-19 pandemic.

This study investigates the determinants of Internet access and its effect on educational inequality in OECD countries during the period of the Covid-19 pandemic. The spatial panel data model is used to include the neighborhood in the model relating to educational inequality. The findings from the study reveal that despite the increase in Internet access during the Covid-19 period, the response to the pandemic has caused education inequalities. Furthermore, economic development indicators are effective in increasing Internet access and reducing educational inequality. Finally, the study shows that, as improvements in income levels can increase Internet access, which results in a reduction in educational inequality.

Which factors influence mobility change during COVID-19 in Germany? Evidence from German county data

This study analyzes the role of regional demographic, socioeconomic and political factors on changes in mobility during the COVID-19 pandemic in Germany. Spatial econometric models are applied using data from the 401 counties in Germany. The model incorporates measures to reduce potential endogeneity effects. Our results show that mobility change shows significant socioeconomic heterogeneity which could affect future policy measures to contain the pandemic. For example, case numbers and the share of academics are negatively associated with changes in mobility. On the contrary, a region?s mean age and rural location have a positive impact. Political and economic implications of the results are discussed. The findings point to a possible reorganization of spatial, economic, and social activities beyond the course of the pandemic.

Does Government Intervention Ensure Food Safety? Evidence from China.

Food safety is related to public health, social welfare, and human survival, all of which are important and pressing areas of concern all over the world. The government plays an increasingly important role in the supervision of food safety. The role of the government, however, is also controversial. Using provincial panel data of China from 2005 to 2015, the present study intends to shed light on the associations between government intervention and food safety performance under two scenarios of local government-competition and noncompetition. This will be accomplished through an exploratory spatial data analysis and a spatial econometric model. The results reveal negative associations between food safety performance and government intervention without considering local government competition. As was also observed, government intervention not only inhibits the improvement of food safety in the region, but also has a negative spatial spillover effect on food safety in neighboring provinces. This is the result after considering government competition, thus, showing the competitive strategic interaction of the "race to the bottom". Further analysis reveals that, if geographically similar regions are selected as reference objects, the food safety performance of each province will have a stronger tendency to compete for the better. If regions with similar economic development levels are selected as reference objects, food safety performance will have a stronger tendency to compete for the worse. This work provides new evidence for the relationships between government intervention and food safety, and, also, proposes some insightful implications for policymakers for governing food safety.

The propagation effect of commuting to work in the spatial transmission of COVID-19.

This work is concerned with the spatiotemporal dynamics of the coronavirus disease 2019 (COVID-19) in Germany. Our goal is twofold: first, we propose a novel spatial econometric model of the epidemic spread across NUTS-3 regions to identify the role played by commuting-to-work patterns for spatial disease transmission. Second, we explore if the imposed containment (lockdown) measures during the first pandemic wave in spring 2020 have affected the strength of this transmission channel. Our results from a spatial panel error correction model indicate that, without containment measures in place, commuting-to-work patterns were the first factor to significantly determine the spatial dynamics of daily COVID-19 cases in Germany. This indicates that job commuting, particularly during the initial phase of a pandemic wave, should be regarded and accordingly monitored as a relevant spatial transmission channel of COVID-19 in a system of economically interconnected regions. Our estimation results also provide evidence for the triggering role of local hot spots in disease transmission and point to the effectiveness of containment measures in mitigating the spread of the virus across German regions through reduced job commuting and other forms of mobility. Supplementary Information: The online version contains supplementary material available at 10.1007/s10109-021-00349-3.

The spatial econometrics of the coronavirus pandemic.

In this paper we use spatial econometric specifications to model daily infection rates of COVID-19 across countries. Using recent advances in Bayesian spatial econometric techniques, we particularly focus on the time-dependent importance of alternative spatial linkage structures such as the number of flight connections, relationships in international trade, and common borders. The flexible model setup allows to study the intensity and type of spatial spillover structures over time. Our results show notable spatial spillover mechanisms in the early stages of the virus with international flight linkages as the main transmission channel. In later stages, our model shows a sharp drop in the intensity spatial spillovers due to national travel bans, indicating that travel restrictions led to a reduction of cross-country spillovers.