The present study examines the asymmetrical effect of temperature on COVID-19 (Coronavirus Disease) from 22 January 2020 to 31 March 2020 in the 10 most affected provinces in China. This study used ...the Sim & Zhou' quantile-on-quantile (QQ) approach to analyze how the temperature quantities affect the different quantiles of COVID-19. Daily COVID-19 and, temperature data collected from the official websites of the Chinese National Health Commission and Weather Underground Company (WUC) respectively. Empirical results have shown that the relationship between temperature and COVID-19 is mostly positive for Hubei, Hunan, and Anhui, while mostly negative for Zhejiang and Shandong provinces. The remaining five provinces Guangdong, Henan, Jiangxi, Jiangsu, and Heilongjiang are showing the mixed trends. These differences among the provinces can be explained by the differences in the number of COVID-19 cases, temperature, and the province's overall hospital facilitations. The study concludes that maintaining a safe and comfortable atmosphere for patients while COVID-19 is being treated may be rational.
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•Ø This paper examines the interlinkages between temperature and COVID-19 in the top ten coronavirus affected Chinese provinces.•Ø QQ approach of Sim and Zhou is applied to explore some nuanced features of temperature and COVID-19 nexus.•We find mostly positive relationship for Hubei, Hunan and Anhui between temperature and COVID-19.•Zhejiang and Shandong provinces are showing mostly negative impacts between temperature and COVID-19.
In the wake of recent pandemic of COVID-19, we explore its unprecedented impact on the cryptocurrencies' market. Specifically, we check how the changing intensity of the COVID-19 represented by the ...daily addition in new infections worldwide affects the daily returns of the top 10 cryptocurrencies according to the market capitalization. The results from Quantile-on-Quantile Regression (QQR) approach reveal that the changing intensity levels of the COVID-19 affect the Bearish and the Bullish market scenarios of cryptocurrencies differently (asymmetric impact). Additionally, there are differences between these currencies in their responses to the changing levels of this pandemic's intensity. Most of the currencies absorbed the small shocks of COVID-19 by registering positive gains but failed to resist against the huge changes except Bitcoin, ADA, CRO, and up to some extent Ethereum. Our results reveal new and asymmetric dynamics of this emerging asset class against an extremely stressful and unpredictable event (COVID-19). Moreover, these results are robust to the use of alternative proxy (COVID-19 deaths) for pandemic intensity. Our findings help to improve investors and policymakers' understanding of the cryptocurrencies' market dynamics, especially in the times of extremely stressful and unseen events.
•We study the impact of COVID-19 outbreak on the top 10 cryptocurrencies' returns.•The QQR approach reveals an asymmetric impact of pandemic intensity on othe Bearish and Bullish scenarios in cryptocurrencies.•Majority of the cryptocurrencies performed better against small shocks of COVID-19.•Bitcoin, ADA, CRO and Ethereum performed better against the negative effects of the highest intensity of COVID-19.•Our results are robust to the use of alternative proxy for the pandemic.
In the real world, economic covariates follow asymmetric and time-varying patterns. Therefore, it is imperative to integrate these effects while estimating environmental and economic relationships. ...Although prevailing literature reveals various emissions-deriving and eliminating factors, however, there is a dearth of empirical evidence that estimates the asymmetric and time-varying effect of globalization, natural resources, and financial development from a multidimensional perspective in China. In doing so, we employ the nonlinear autoregressive distributed lag (NARDL) and cross-wavelet modeling framework to explore the long- and short-run nonlinear and time-variant association between globalization, natural resources, financial development, and carbon emissions from 1980 to 2017. The NARDL method has the benefit of discriminating the long-term and short-term asymmetric carbon emission responses due to a positive and negative shock in our primary variables of interest. Mainly, the findings of NARDL estimations confirm that positive shocks in globalization and financial developments have a significant positive impact on carbon emissions, whereas negative shock in natural resources has a significant positive impact on carbon emissions. Similarly, the outcomes of continuous wavelet transformation and wavelet transformation coherence confirm the causal linkages between covariates; however, this effect varies across different time and frequency domains. These results imply that environmental researchers should consider asymmetric transmission channels and time–frequency associations among variables to devise long-term sustainable policies.
The worldwide outbreak of COVID-19 disease has caused immense damage to our health and economic and social life. This research article helps to determine the impact of climate on the lethality of ...this disease. Air quality index and average humidity are selected from the family of climate variables, to determine its impact on the daily new cases of COVID-19-related deaths in Wuhan, China. We have used wavelet analysis (wavelet transform coherence (WTC), partial (PWC), and multiple wavelet coherence (MWC), due to its advantages over traditional time series methods, to study the co-movement nexus between our selected data series. Findings suggest a notable coherence between air quality index, humidity, and mortality in Wuhan during a recent outbreak. Humidity is negatively related to the COVID-19-related deaths, and bad air quality leads to an increase in this mortality. These findings are important for policymakers to save precious human lives by better understanding the interaction of the environment with the COVID-19 disease.
On one side, the rapid progress in financial development boosts economic growth. On the other hand, it forces both the developed and emerging countries to play the role of good governance that help ...save the environment. The current study aims to identify the role of national governance in the relationship between financial inclusion and ecological footprints. To attain the study’s objective, we use a novel method of moments quantile regression (MMQR) on a panel data set of 65 countries from 2004 to 2017. The empirical outcomes reveal that financial inclusion has a significant positive and heterogeneous impact on ecological footprints. This effect varies across quantiles, and when moving from lower to upper quantiles, the impact of financial inclusion on environment escalates. National governance plays an important role to moderate the relationship between financial inclusion and ecological footprint negatively. Moreover, GDP and REC display a significant positive and negative influence on ecological footprints, respectively. We obtain similar and robust findings from the alternative panel estimation techniques, including FMOLS, FEOLS, and DOLS. The policy implications from this research can be considered to achieve sustainable and eco-friendly environmental goals.
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Espousing the theoretical framework of singling theory and social exchange theory, the current study examines the less explored topic of paternalistic leadership. This study contributed by ...scrutinizing the relationship between paternalistic leadership, personality characteristics, alienation, and organizational climate through the mediating role of cohesiveness. A convenience sampling technique was applied for this study. Data was collected through an adopted questionnaire from 723 respondents. A variance-based structural equation modeling (PLS-SEM) was used for testing the proposed structural model. Results revealed that paternalistic leadership and personality characteristics significantly and positively impact alienation and organizational climate. Furthermore, cohesiveness mediates the relationship between personality characteristics, paternalistic leadership, alienation, and organizational climate. Based on research findings, essential theoretical and managerial aspects with major policy-making implications are discussed in the study.
The rapid urbanization growth has not only improved the living standards of people but also raised concerns for environmental sustainability over the globe. In this regard, the issue of excessive ...urban concentration or over-agglomeration in metropolitan areas is nowadays the prime concern for urban planning and building energy-efficient and eco-friendly infrastructures. In response to rising interest in the dynamic linkage between urban concentration and environment, the current research empirically examines the crucial nexus between urban agglomerations and environmental degradation in top ten urban agglomerated countries in the world from 1960Q1 to 2014Q4. The current research is the pioneer empirical work in the area of urbanization by applying recently developed and innovative methods of quantile-on-quantile (QQ) approach and quantile Granger causality in relatively less explored area of urban agglomeration at the cross-country level. Our mainstream findings indicate that urban agglomeration has a strong positive effect on CO
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emissions in most of our sample countries, and this effect is more pronounced in higher quantiles of respective variables. These results imply that excessive levels of urban concentration in big cities cause environmental degradation, which could be attributed to extreme population density, overcrowding, traffic congestion and extensive demand for energy consumption. However, some countries such as Israel, Paraguay and Columbia exhibit overall declining and negative trends about the relationship between urban agglomerations and CO
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emissions. Moreover, quantile Granger causality results confirm the previous findings of QQ regression and verify the existence of bidirectional causal nexus between urban agglomerations and CO
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emissions in the majority of the lower, middle and upper quantiles in our selected top ten countries except for Kuwait. However, the unidirectional causal relationship also exists for several countries for extreme lower, middle and extremely higher quantiles. Our findings extend the previous work on agglomeration-environment nexus by determining the asymmetric magnitude of linkage between these two variables demanding cautious and individual-focused policies for urban planning and environmental sustainability.
Sustainable development and reducing environmental pressure are major issues that concern developed as well as developing countries. Although researchers widely use carbon dioxide emissions and ...ecological footprint within the scope of environmental degradation, a more comprehensive ecological indicator is needed to assess environmental sustainability. In this context, the load capacity factor enables a comprehensive environmental sustainability assessment through the simultaneous analysis of biocapacity and ecological footprint. However, there are few studies analyzing the determinants of load capacity factor and this study aims to fill this gap for Indonesia. Using the recently developed Fourier quantile causality test, this study investigates the impact of income, export diversification, non-renewable and renewable energy consumption on the load capacity factor for Indonesia during 1965Q1–2014Q4. The results show unidirectional causality from non-renewable energy consumption to the load capacity factor at all quantiles, while income, export diversification, and renewable energy are the causes of environmental quality at middle and higher quantiles (within 0.5, 0.7, and 0.9). Most importantly, renewable energy and export diversification increase the load capacity factor and thus support environmental quality. In contrast, an increase in income and consumption of non-renewable energy reduces the load capacity factor. These results highlight the importance of renewable energy and export diversification for the sustainable development of Indonesia.
The Internet of things (IoT) has emerged as a topic of intense interest among the research and industrial community as it has had a revolutionary impact on human life. The rapid growth of IoT ...technology has revolutionized human life by inaugurating the concept of smart devices, smart healthcare, smart industry, smart city, smart grid, among others. IoT devices' security has become a serious concern nowadays, especially for the healthcare domain, where recent attacks exposed damaging IoT security vulnerabilities. Traditional network security solutions are well established. However, due to the resource constraint property of IoT devices and the distinct behavior of IoT protocols, the existing security mechanisms cannot be deployed directly for securing the IoT devices and network from the cyber-attacks. To enhance the level of security for IoT, researchers need IoT-specific tools, methods, and datasets. To address the mentioned problem, we provide a framework for developing IoT context-aware security solutions to detect malicious traffic in IoT use cases. The proposed framework consists of a newly created, open-source IoT data generator tool named IoT-Flock. The IoT-Flock tool allows researchers to develop an IoT use-case comprised of both normal and malicious IoT devices and generate traffic. Additionally, the proposed framework provides an open-source utility for converting the captured traffic generated by IoT-Flock into an IoT dataset. Using the proposed framework in this research, we first generated an IoT healthcare dataset which comprises both normal and IoT attack traffic. Afterwards, we applied different machine learning techniques to the generated dataset to detect the cyber-attacks and protect the healthcare system from cyber-attacks. The proposed framework will help in developing the context-aware IoT security solutions, especially for a sensitive use case like IoT healthcare environment.
Face masks are considered an effective intervention in controlling the spread of airborne viruses, as evidenced by the 2009's H1N1 swine flu and 2003's severe acute respiratory syndrome (SARS) ...outbreaks. However, research aiming to examine public willingness to wear (WTW) face masks in Pakistan are scarce. The current research aims to overcome this research void and contributes by expanding the theoretical mechanism of theory of planned behavior (TPB) to include three novel dimensions (risk perceptions of the pandemic, perceived benefits of face masks, and unavailability of face masks) to comprehensively analyze the factors that motivate people to, or inhibit people from, wearing face masks. The study is based on an inclusive questionnaire survey of a sample of 738 respondents in the provincial capitals of Pakistan, namely, Lahore, Peshawar, Karachi, Gilgit, and Quetta. Structural equation modeling (SEM) is used to analyze the proposed hypotheses. The results show that attitude, social norms, risk perceptions of the pandemic, and perceived benefits of face masks are the major influencing factors that positively affect public WTW face masks, whereas the cost of face masks and unavailability of face masks tend to have opposite effects. The results emphasize the need to enhance risk perceptions by publicizing the deadly effects of COVID-19 on the environment and society, ensure the availability of face masks at an affordable price, and make integrated and coherent efforts to highlight the benefits that face masks offer.