Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach

Integrating climate resilience with sports, exercise, and public health expenditures on sustainable environment: Evidence from coastal regions of China

The adoption of environmentally-friendly habits has become more crucial in the present period as a means to mitigate the rate of environmental degradation and its detrimental consequences. The augmentation of sports, exercise and physical activities has been associated with favourable health outcomes, in addition to the ability to mitigate carbon emissions resulting from vehicular transportation. Consequently, the objective of this study is to examine the influence of sports, exercise, and physical activities, along with public health expenditure, on the environmental performance of China's coastal regions throughout the period spanning from 2010 to 2019. The proposed study employs the Feasible Generalized Least Squares (F.G.L.S) and the Generalized Method of Moments (G.M.M) methodologies. Results show that participation in sports and other forms of physical activity significantly improves environmental performance in China's coastal areas. Likewise, a robust negative correlation exists between air pollution and healthcare expenses, hence favouring enhanced environmental outcomes. Nevertheless, it is important to acknowledge that economic expansion has a direct correlation with increased emissions, hence harming environmental performance. There exists compelling evidence indicating a significant impact on environmental quality resulting from the combined influence of heightened health expenditures and increased engagement in sports. This is demonstrated by the presence of an interaction term between health expenses and sports activities. The findings of this study suggest that there is a requirement to re-evaluate healthcare spending initiatives and sporting activities in order to effectively pursue carbon neutrality goals and improve environmental sustainability.

Neutralizing the surging emissions amidst natural resource dependence, eco-innovation, and green energy in G7 countries: Insights for global environmental sustainability

The unrelenting surge in global warming in the current era suggests the inevitable need for governments across the globe to embark on policy measures that will help flatten the curve of the surging emissions. Consequently, the concept of carbon neutrality has become a vital policy approach for countries to achieve sustainable development. The present study extends the debates on carbon neutrality by examining the extent to which prominent factors such as natural resource dependence, eco-innovation, and green energy (biofuel and renewable energy) facilitate or hinder strides toward achieving carbon neutral environment in G7 economies. The study considers the additional roles of carbon tax, environmental policy stringency, and financial development in longitudinal data ranging from 1997 to 2019. The verification of the stated hypotheses hinges on a battery of estimators comprising cross-sectional ARDL, common correlated effects mean group, augmented mean group, and panel quantile regression. The empirical findings show that green energy, carbon tax, and environmental policy support the drive towards carbon neutrality by reducing the stock of CO2 emissions. On the other hand, natural resource dependence and financial development hinder the carbon neutrality agenda by escalating the surge in CO2 emissions. Robustness analyses are conducted from the angle of an additional outcome variable and estimation technique of which the results corroborate the empirical regularity of the main findings. Policy implications are derived from the empirical findings.

Asymmetric effects of fine particulate matter and stringency policy on COVID-19 intensity

This study aims to examine the influence of environmental performance (PM2.5) on COVID-19 intensity . For this purpose, we employ the newly introduced Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag model. Results indicate the asymmetric linkages between PM2.5 and COVID-19 intensity, as the positive shock in PM2.5 raises the COVID-19 intensity by 21%, whereas the negative shock in PM2.5 decreases COVID-19 intensity by 12% in long-run. On the contrary, the positive shock in stringency measures decreases COVID-19 intensity by 42.8%, while the negative shock in stringency policy increases COVID-19 intensity by 66.7%. These findings imply that higher pollution increases the COVID-19 severity while higher stringency measures slow down people's movement and reduce COVID-19 intensity. However, a sudden negative shock in lockdown increases people's interaction, leading to a higher spread of the virus. These results suggest that governments should adopt stringent action plans to contain the transmissibility of COVID-19.

How economic policy uncertainty and geopolitical risk affect environmental pollution: does renewable energy consumption matter?

Climate change traps heat, affecting various species in previously dry areas. Climate change brought on by emissions of greenhouse gases exacerbates problems such as severe storms, earthquakes, epidemics, and food distribution. The group of developed and developing countries, the world's biggest carbon emitters and most significant economies, is expertly planning to lessen its environmental challenges and contribute to achieving Sustainable Development Goals 7 and 13 set by the United Nations. This study uses the novel econometric methodologies of the dynamic ordinary least square (DOLS) estimator, the augmented mean group (AMG) estimator, and the fully modified ordinary least square (FMOLS) estimate to examine the influence of economic policy uncertainty, renewable energy consumption, geopolitical risk, non-renewable energy consumption, and economic growth on ecological footprint from 2000 to 2021. The results reveal that the variables are co-integrated; REC reduces carbon emissions, EPU, geopolitical risk, and economic growth contribute to increasing carbon emissions, while urbanization improves carbon emission. Finally, the results suggest that the developed and developing economies can progress toward SDGs 7 and 13 by using renewable energy, lowering the geopolitical risk, effectively handling policy uncertainty, and reducing urbanization.

Exploring the nonlinear relationship among financial development, human capital and CO2 emissions: a comparative study of South and East Asian emerging economies

Despite worldwide commitments to reduce fossil fuel consumption in favour of alternative energies, several countries still rely on carbon-intensive sources to meet their energy demands. The previous studies show inconsistent results on the association between financial development and CO2 emissions. As a result, the impact of financial development, human capital, economic growth and energy efficiency on CO2 emission is evaluated here. Empirical research on a panel of 13 South and East Asian (SEA) nations between 1995 and 2021 using the CS-ARDL. Estimates from the empirical analysis considering energy efficiency, human capital, economic growth and overall energy use yield different findings. Financial development has a negative effect on CO2 emission, while economic growth positively impacts CO2 emission. The data also show that improving human capital and energy efficiency has a positive, though statistically insignificant, impact on CO2 emission. According to the causes and effects analysis, CO2 emission will be influenced by policies that aim to improve financial development, human capital, and energy efficiency, but not vice versa. Policy considerations that can be implemented in light of these findings and sustainable development goals can be accomplished by promoting financial resources and human capital.

Multivariate time series short term forecasting using cumulative data of coronavirus

Coronavirus emerged as a highly contagious, pathogenic virus that severely affects the respiratory system of humans. The epidemic-related data is collected regularly, which machine learning algorithms can employ to comprehend and estimate valuable information. The analysis of the gathered data through time series approaches may assist in developing more accurate forecasting models and strategies to combat the disease. This paper focuses on short-term forecasting of cumulative reported incidences and mortality. Forecasting is conducted utilizing state-of-the-art mathematical and deep learning models for multivariate time series forecasting, including extended susceptible-exposed-infected-recovered (SEIR), long-short-term memory (LSTM), and vector autoregression (VAR). The SEIR model has been extended by integrating additional information such as hospitalization, mortality, vaccination, and quarantine incidences. Extensive experiments have been conducted to compare deep learning and mathematical models that enable us to estimate fatalities and incidences more precisely based on mortality in the eight most affected nations during the time of this research. The metrics like mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) are employed to gauge the model's effectiveness. The deep learning model LSTM outperformed all others in terms of forecasting accuracy. Additionally, the study explores the impact of vaccination on reported epidemics and deaths worldwide. Furthermore, the detrimental effects of ambient temperature and relative humidity on pathogenic virus dissemination have been analyzed.

Improved LSTM-based deep learning model for COVID-19 prediction using optimized approach

Individuals in any country are badly impacted both economically and physically whenever an epidemic of infectious illnesses breaks out. A novel coronavirus strain was responsible for the outbreak of the coronavirus sickness in 2019. Corona Virus Disease 2019 (COVID-19) is the name that the World Health Organization (WHO) officially gave to the pneumonia that was caused by the novel coronavirus on February 11, 2020. The use of models that are informed by machine learning is currently a major focus of study in the field of improved forecasting. By displaying annual trends, forecasting models can be of use in performing impact assessments of potential outcomes. In this paper, proposed forecast models consisting of time series models such as long short-term memory (LSTM), bidirectional long short-term memory (Bi-LSTM), generalized regression unit (GRU), and dense-LSTM have been evaluated for time series prediction of confirmed cases, deaths, and recoveries in 12 major countries that have been affected by COVID-19. Tensorflow1.0 was used for programming. Indices known as mean absolute error (MAE), root means square error (RMSE), Median Absolute Error (MEDAE) and r2 score are utilized in the process of evaluating the performance of models. We presented various ways to time-series forecasting by making use of LSTM models (LSTM, BiLSTM), and we compared these proposed methods to other machine learning models to evaluate the performance of the models. Our study suggests that LSTM based models are among the most advanced models to forecast time series data.

Role of climate fund raising under fiscal balance on climate change mitigation: an analysis from Pareto optimality

Since there is little progress being made in multinational climate discussions, climate finance is at a crossroads as lenders must come up with new plans for the "Future of Environment Funds." The mission of effectively and efficiently distributing money to support the shift to low-carbon, climate-resilient economies has been given to climate finance organizations. Due to its purpose to contribute to a paradigm shift, the Green Climate Fund (GCF) is anticipated to help the most vulnerable populations adapt to and mitigate climate change. This research alters the premise of the Baumol and Oates public externality model to make it more appropriate for global climate governance analysis. This research then deduces the special pricing conditions to persuade the market to comply with Pareto optimality criteria by contrasting the Pareto optimality model of global climate governance and the market equilibrium model. The rules and potential approaches that must be followed for raising capital and allocating GCFs are then determined by taking into account global Pareto optimality and fiscal balance. The study finds that when each country assumes that the GCF aims to achieve Pareto optimality in climate governance globally and its own fiscal balance, the equilibrium results of the international climate game will not achieve both the financial balance of the GCF and global Pareto optimality simultaneously. The GCF may successfully finance non-bankable components of bigger "almost bankable projects," according to our empirical analysis of the GCF portfolio structure and strategy in this research. This lends credence to an alternative interpretation of the GCF.

Re-visiting the resource curse hypothesis in the MINT economies

Natural resources are extremely important to the economy, particularly in emerging nations such as the MINT (Mexico, Indonesia, Nigeria, and Turkey) nations. To improve their economic performance, such nations put a priority on maximizing the use of natural resources. These natural materials are the basis on which all living creatures rely, and they are the primary motivation behind contemporary production. Therefore, the current research utilizes a dataset spanning the period from 1970 to 2019 to assess the effect of natural resource on economic growth for the MINT nations. The present study uses a unique quantile-on-quantile regression (QQR) approach to assess this interrelationship. Furthermore, we apply the novel quantile causality suggested by Troster (2018), which identifies causality across quantiles. The findings from the QQR reveal that in the majority of the quantiles, the effect of natural resources on economic expansion is positive in Nigeria and Mexico, while it is negative in Indonesia and Turkey. In addition, a feedback causality is found between economic growth and natural resources for Mexico, Indonesia, and Nigeria. Based on the results, it is paramount for policymakers to develop policies or frameworks that promote cleaner energy sources and more effective use of natural resources, which can aid the country's economic growth.

Identifying the pathways through digital transformation to achieve supply chain resilience: an fsQCA approach

The manufacturing industry has placed a greater emphasis on digital transformation, especially under the impact of COVID-19. However, the influence mechanism between digital transformation and supply chain resilience is still a topic of discussion. Resource orchestration theory indicates that a firm not only need to emphasize the investment of resources but also pays attention to the allocation of resources. Therefore, based on the resource orchestration theory, this study divides the digital transformation into digital transformation breadth and digital transformation depth and combines R&D spending (R&D intensity and R&D employee) and contingency factors (firm size) to construct a theoretical path of "digital transformation-supply chain resilience." This research uses fuzzy sets qualitative comparative analysis to explore how to configure the digital transformation to achieve high supply chain resilience based on data from 193 listed manufacturing firms. Using the fsQCA software, it was discovered that there were no necessary conditions for achieving high supply chain resilience; sufficient condition analysis revealed that there are six paths to achieving high supply chain resilience, four of which can be summarized as digital transformation driven and the other two as R&D spending driven. These several approaches highlight the complicated causal relationship between digital transformation and supply chain resilience, as well as give theoretical and practical recommendations for firms looking to implement digital strategies and enhance their supply chains.

Firm characteristics, governance mechanisms, and ESG disclosure: how caring about sustainable concerns?

Environmental, social, and governance (ESG) pillars help determine the business organizations' sustainable business practices. Considering the same, this research examines the association between firm characteristics, governance mechanisms, and ESG for a sample of 564 firms from fifteen developed economies. For empirical analysis, ordinary least square, fixed effect, and random effect estimations techniques were applied using annual data from 2010 to 2019. The overall findings reveal that the governance structure of firms (board size, board independence, and cross-listing) play a significant role in ESG disclosure. Moreover, low corruption perception reflects higher ESG disclosure among the targeted firms. Additionally, firm characteristics; such as liquidity position shows a better reporting of ESG during the study period. When accounting for the ESG disclosure individually, the findings confirm the productive role of board size, current ratio, and low corruption towards environmental exposure. Lastly, the results demonstrate that board size and ESG disclosure promote better financial performance. These results offer valuable policy recommendations.

Association Between Weather Parameters and SARS-CoV-2 Confirmed Cases in Two South African Cities

Several approaches have been used in the race against time to mitigate the spread and impact of COVID-19. In this study, we investigated the role of temperature, relative humidity, and particulate matter in the spread of COVID-19 cases within two densely populated cities of South Africa-Pretoria and Cape Town. The role of different levels of COVID-19 restrictions in the air pollution levels, obtained from the Purple Air Network, of the two cities were also considered. Our results suggest that 26.73% and 43.66% reduction in PM2.5 levels were observed in Cape Town and Pretoria respectively for no lockdown (Level 0) to the strictest lockdown level (Level 5). Furthermore, our results showed a significant relationship between particulate matter and COVID-19 in the two cities. Particulate matter was found to be a good predictor, based on the significance of causality test, of COVID-19 cases in Pretoria with a lag of 7 days and more. This suggests that the effect of particulate matter on the number of cases can be felt after 7 days and beyond in Pretoria.

Sustainable impact of COVID-19 on education projects: aspects of naturalism

History records show that pandemics and threats have always given new directions to the thinking, working, and learning styles. This article attempts to thoroughly document the positive core of coronavirus 2019 (COVID-19) and its impact on global social psychology, ecological stability, and development. Structural equation modeling (SEM) is used to test the hypotheses and comprehend the objectives of the study. The findings of the study reveals that the path coefficients for the variables health consciousness, naturalism, financial impact and self-development, sustainability, compassion, gregariousness, sympathy, and cooperation demonstrate that the factors have a positive and significant effect on COVID-19 prevention. Moreover, the content analysis was conducted on recently published reports, blog content, newspapers, and social media. The pieces of evidence from history have been cited to justify the perspective. Furthermore, to appraise the opinions of professionals of different walks of life, an online survey was conducted, and results were discussed with expert medical professionals. Outcomes establish that the pandemics give birth to creativity, instigate innovations, prompt inventions, establish human ties, and foster altruistic elements of compassion and emotionalism.

Modeling the impact of the COVID‐19 outbreak on environment, health sector and energy market

The global outbreak of COVID‐19 disease had a significant impact on the entire globe. Such a notable public health event can be seen as a “black swan” that brings unpredictable and unusual forces into the economic context and that it could typically lead to a chain of adverse reactions and market disruptions. Hence, the purpose of this study is to examine how COVID‐19 affects the environment, health, and the oil and energy markets. To achieve this objective, we used daily data for several measures that refer to the environment, health, and oil and energy, for the first wave of the COVID‐19 pandemic (December 31, 2019–May 22, 2020). The variable integration mix led to the approach of the ARDL model, and the Granger causality test was also employed. These empirical techniques allowed us to examine the cointegration between variables and causal relationships. The econometric results of the ARDL models exhibited that the global new cases and new deaths of COVID‐19 have short and long‐term effects on the environment, the health sector, the oil, and energy measures. However, no significant causal connection was found between the pandemic and the environment, the health sector, or the oil and energy industry, according to the Granger causality test. The uniqueness of current approach consists in the investigation of pandemic impact on the health, environment, oil, and energy sector by applying the ARDL model that permits the analysis of cointegration both in the long run and in the short term. This study provides important insights for investors and policy makers.

Modeling oil price uncertainty effects on economic growth in Mexico: a sector-level analysis

This paper analyzes the impact of international oil price uncertainty on the different economic sectors (primary, secondary, and tertiary) in Mexico in the period 1993:1-2020:4 through a bivariate structural vector autoregressive (VAR) model with a generalized autoregressive conditional heteroskedasticity (GARCH) in mean to capture the impact of oil volatility on economic growth at the sectoral level of economic activity. The results show that the uncertainty of the international price of oil has a differentiated effect on the different sectors of economic activity in Mexico since it does not influence the primary sector; it negatively impacts the secondary sector, and there is mixed evidence in the tertiary sector. Additionally, evidence is provided that both positive and negative shocks to the international oil price have asymmetric effects at the sectoral level in Mexico. The results highlight the need to implement public policies, at the country level, that help mitigate the effect of uncertainty in the oil market and promote economic stability at the sector level.

Assessing the nexus between fiscal policy, COVID-19, and economic growth

The COVID-19 issue deteriorated South Africa's already dire economic situation, exacerbated by years of considerable debt increase. The COVID-19 pandemic has disrupted trade to such an extent that some enterprises are barely working at a quarter of their potential. Furthermore, economic agents delay economic decisions while waiting to see how the crisis develops. According to some economists, increased government expenditure will raise GDP enough to keep the country's debt-to-GDP ratio steady and restore fiscal sustainability. We use a panel data model to estimate a fiscal reaction function, which we then apply to historical data to assess the government's prior efforts to maintain or restore budgetary sustainability. We calculate the impact fiscal balance, government expenditure, interest rate, and revenue changes that the government will have to make to restore the country's fiscal stability due to the financial impact of the COVID-19 issue.The findings show that fiscal balance and tax revinue have a significant impact on the economics growth, while government expenditure and corruption reduce the growth of the country.

Determining the COVID-19 effects on spillover between oil market and stock exchange: a global perspective analysis

This paper investigates volatility spillovers between the global crude oil market and the stock markets of the global oil stock markets (Russian, Canada, China, Kuwait, and the USA) pre and after the COVID-19 pandemic. We use wavelet Granger causality methods to study the volatility spillovers between global oil stock markets, mainly from January 1, 2019, to March 31, 2021. Our Results (1) shows that WTI and Brent oil prices had a negative mean return before COVID-19 but a positive mean return during the pandemic spread. Other Results (2) find the positive, significantly lowest, and highest frequency during the COVID-19 outbreak for all selected countries. The results also show that the link between oil WTI & Brent prices and stock markets return in the lowest (33-66 days) and highest frequency range (4-16) before the Covid-19 epidemic, especially in the first quarter of 2020. Before the COVID-19 period, the Russian oil stock market is seriously prejudiced with oil prices on a modest scale, but not after the pandemic's start. This study also perceives direction opposite between the COVID-19 period. The Canadian and United States America oil and stock markets influence the lowest scale in the previous COVID-19 sample for the U.S. market. Moreover, this paper exposed that oil marketing highest oil futures in their portfolios than stock shares for all times. We found that oil price shocks had a more significant impact on the stock markets of the United States and Canada than on the stock markets of other countries.

Macroeconomic lockdown effects of COVID-19 on small business in China: empirical insights from SEM technique

The coronavirus (COVID-19) outbreak in the China has exposed small- and medium-sized enterprises (SMEs) to a variety of challenges, some of which are potentially life-threatening to their sustainability. Therefore, this study aims to investigate the macroeconomic lockdown effects of COVID-19 on small business in China. A survey questionnaire with 313 participants was used to collect the data. In this study, the SEM technique was used to analyse model. The data have been gathered for the study from the managers and employees of Chinese SMEs. The findings of the study show that COVID-19 has a significant negative impact on financial performance, operational performance, profitability, access to finance, and customer satisfaction. According to the study's findings, external support aids have a greater impact on SMEs' ability to survive and thrive through innovation than on their actual performance. The findings of this study have a number of important practical consequences for small- and medium-sized business owners, governments, and policymakers.

Does health expenditure matter for life expectancy in Mediterranean countries?

This research assesses the effect of health expenditure and sanitation on life expectancy in Mediterranean countries. We also consider other drivers of life expectancy, such as CO₂ emissions and economic growth. The study covers the period 2000-2018, and the recently developed method of moments quantile regression (MMQR) approach was utilised to assess these interconnections. This method is immune to outliers and creates an asymmetric interrelationship between variables. The outcomes from the MMQR unveiled that economic growth, health expenditure, and sanitation enhanced life expectancy in all quantiles (0.1-0.90). Furthermore, in all quantiles (0.1-0.90), the effect of CO₂ emissions on life expectancy was negative. Moreover, as a robustness check, the FMOLS, DOLS, and FE-OLS long-run estimators were applied, and the outcomes validated the MMQR outcomes. Based on the results generated, policymakers in these nations should implement effective environmental and public health measures that will pay off in the long run through improved health as a result of lower emissions of CO₂, as well as increased economic expansion and productivity.

Quantile relationship between globalization, financial development, economic growth, and carbon emissions: evidence from Vietnam

Environmental quality and economic activity have a strong relationship. Carbon emissions remain one of the world's most dangerous environmental issues. Both international and local governments are developing initiatives to address this problem. Capitalizing on the limitations of the existing literature, this article investigates the dynamic nexus of financial development, economic growth, and globalization on carbon dioxide emissions in Vietnam for 1990-2020 using the quantile-on-quantile regression. The findings unveil a positive feedback link between globalization and carbon dioxide emissions at the middle and high quantiles. In addition, there is a negative nexus between financial development and carbon emissions at most quantiles, while CO₂ emissions and economic growth have a positive association at all quantiles. More importantly, our empirical results also provide the bidirectional causality between financial development, economic growth, globalization, and carbon dioxide emissions in Vietnam at different quantile levels. The consistency of the outcomes uncovers that the findings are trustworthy and appropriate for guiding policy to reduce CO₂ emissions in Vietnam. Therefore, they can help policymakers understand how financial development and globalization can achieve sustainable economic growth and tackle environmental issues in this country.

Does green finance mitigate the effects of climate variability: role of renewable energy investment and infrastructure

Few researches have inspected the task of green finance in reducing CO2 emissions, while earlier studies have inspected the influence of economic development on carbon emissions. A green finance development index is built using four indicators to fill in this knowledge gap: green credit, green insurance, green securities, and green investing. Using data spanning the years 2005-2019, a panel quantile regression is applied to investigate the links between green finance, renewable energy, and CO2 emissions. Increases in renewable energy use and advances in the green finance development index have contributed to a reduction in CO2 emissions from BRICS countries. CO2 emissions on the other hand slowed the growth of renewable energy use, slowed the flow of investment to green projects, and ultimately hampered the development of green finance. There was also a clear policy-driven influence on renewable energy spending in the countries of the BRICS region. Green finance policies, on the other hand, have consistently failed to have a long-term impact. Therefore, rising the consumption of renewable energy and creating a carbon trading market are all part of this study's recommendations for green finance policy improvement.

Does Green Financing Develop a Cleaner Environment for Environmental Sustainability: Empirical Insights From Association of Southeast Asian Nations Economies

One of the most frequently used terms in climate change discussions is environmental sustainability. With economic growth and foreign direct investment as moderator factors, this study investigates the influence of green finance and financial development on environmental sustainability and growth in ASEAN economies from 2012 to 2019. ADF and Phillip-Peron (PP) unit root tests, fully modified least square (FMOLS), were employed for long-run empirical estimates. A substantial body of evidence supports the study’s findings using VECM technology. Green financing was negatively associated with CO2 emissions. However, environmental sustainability in ASEAN is favorably associated with green financing. It is also worth noting that green financing promotes environmental sustainability at the expenditure of economic growth. Financial development, foreign direct investment, R&D investment, and green technology foster economic expansion at the price of environmental sustainability. There are still many fences to green finance that need to be addressed, including pricing CO2 emissions and reforming inefficient nonrenewable fossil fuel subsidies. Local governments play a vital role in eliminating these barriers and addressing disincentives. It is recommended that policymakers push the financial sector to adopt a green finance strategy to further the goals of long-term sustainable development. Industry must integrate multiple objectives, such as inclusive growth and environmental protection and productivity, through an even broader range of legislative frameworks ideal for decoupling growth from social and ecological unsustainability, at the heart of the green manufacturing process.

The asymmetric nexus between air pollution and COVID-19: Evidence from a non-linear panel autoregressive distributed lag model

The emergence of a new coronavirus (COVID-19) has become a major global concern that has damaged human health and disturbing environmental quality. Some researchers have identified a positive relationship between air pollution (fine particulate matter PM2.5) and COVID-19. Nonetheless, no inclusive investigation has comprehensively examined this relationship for a tropical climate such as India. This study aims to address this knowledge gap by investigating the nexus between air pollution and COVID-19 in the ten most affected Indian states using daily observations from 9th March to September 20, 2020. The study has used the newly developed Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag (NPARDL) model for asymmetric analysis. Empirical results illustrate an asymmetric relationship between PM2.5 and COVID-19 cases. More precisely, a 1% change in the positive shocks of PM2.5 increases the COVID-19 cases by 0.439%. Besides, the estimates of individual states expose the heterogeneous effects of PM2.5 on COVID-19. The asymmetric causality test of Hatemi-J's (2011) also suggests that the positive shocks on PM2.5 Granger-cause positive shocks on COVID19 cases. Research findings indicate that air pollution is the root cause of this outbreak; thus, the government should recognize this channel and implement robust policy guidelines to control the spread of environmental pollution.

Modeling COVID-19 Impact on Consumption and Mobility in Europe: A Legacy Toward Sustainable Business Performance

This article has explored the impact of coronavirus disease 2019 (COVID-19)-induced decline in consumer durables and mobility on nitrogen dioxide (NO2) emission in Europe by providing empirical and graphical justifications based on consumer price index (CPI) and gross domestic product (GDP) deflator indexes. The empirical estimations show that carbon dioxide (CO2) and NOx emission along with other greenhouse gases drastically decreased in the wake of COVID-19-induced lockdowns and decrease in the demand of consumer goods in Europe. This means that COVID-19 improved environment in the European region. However, high cost (e.g., unemployment, loss of life, and social segregation) makes COVID-19 an unstable solution to environmental woes where positive impact of COVID-19 on environment achieved in short run cannot be guaranteed in the long run. Besides environment, COVID-19 drastically curtailed economic activities and exposed them to the risk of economic crisis particularly in case of Europe.

Improving Public Health and Governance in COVID-19 Response: A Strategic Public Procurement Perspective

Good governance is the basis of dealing with major emergencies and protecting public health. It has become a major issue of the central government to construct a scientific procurement and supply system of emergency supplies. This article constructs the analytical framework of strategic procurement and expounds the realization mechanism of strategic procurement under an emergency situation to reflect China's procurement practice in COVID-19 response and improve public health and governance. Using case study, semi-structured interviews, and the Nvivo text analysis, this study found that emphasizing the strategic function of securing the public health,the top status of MSG, cross-sector procurement team, strong procurement and supply integration, comprehensive and in-depth procurement synergy mechanism are the successful experiences of China's emergency procurement. However, due to the temporary nature of the emergency procurement mechanism, strategic procurement planning, procurement management specialization, and procurement supply integration still need to be improved. The findings of this study further suggest that to improve public health and governance, it is pivotal to reconstruct the government procurement law to make it compatible with the emergency procurement and transform the government procurement system into a strategic procurement in a consistent and coherent way.

How Do Green Finance and Energy Efficiency Mitigate Carbon Emissions Without Reducing Economic Growth in G7 Countries?

Climate change is one of the most serious threats facing the world today. Environmental pollution and depletion of natural resources have been highlighted by the United Nations Sustainable Development Goals (SDGs), paving the way for modern concepts such as sustainable growth to be introduced. Therefore, this research explores the relationship between green finance, energy efficiency, and CO2 emissions in the G7 countries. The study uses panel data model technique to examine the dependence structure of green finance, energy efficiency, and CO2 emissions. Moreover, we use DEA to construct an energy efficiency index of G7 countries. A specific interval exists between the values of the energy efficiency indexes. Japan, the United Kingdom, and the United States were named the most energy-efficient countries in the world, based on results obtained for five consecutive years in this category. However, according to the comparative rankings, France and Italy are the most successful of all the G7 members, followed by the United Kingdom and Germany. Our overall findings of the econometric model confirm the negative impact of green finance and energy efficiency on CO2 emissions; however, this relationship varies across the different quantiles of the two variables. The findings in the study confirm that green finance is the best financial strategy for reducing CO2 emissions.

The role of innovation investment and institutional quality on green total factor productivity: evidence from 46 countries along the "Belt and Road"

Based on the panel data of 46 countries in "Belt and Road" (B&R) from 2004 to 2016, this paper studies the impact of innovation investment and institutional quality on green total factor productivity (GTFP). Firstly, the ICRG database, World Bank WDI database, Traditional Foundation database, and Wind database are matched to obtain the balanced panel data of 46 countries along the B&R from 2004 to 2016. Secondly, the Malmquist-Luenberger index, which can be included in the unexpected output, is used to calculate the GTFP of countries along B&R. Thirdly, the evaluation system of national institutional quality of B&R is constructed from three dimensions (political institutional quality, economic institutional quality, and legal institutional quality), and the overall system quality of different countries is measured by entropy method. Finally, an empirical study is made on the relationship among innovation investment, institutional quality, and green total factor productivity. The results show that innovation investment has significantly promoted the GTFP of the B&R countries. It is worth noting that there is a non-linear relationship between innovation investment and GTFP in the B&R countries. With the improvement of overall system quality, political system quality, economic system quality, and legal system quality, the promotion effect of innovation investment on GTFP is further enhanced. In addition, the heterogeneity regression results show that the impact of innovation investment on GTFP is significantly heterogeneous in different regions of the B&R countries. Specifically, innovation investment has the greatest impact on GTFP in South Asia, followed by East Asia and Pacific, Europe and Central Asia, Middle East, and North Africa.

Interventions for the Current COVID-19 Pandemic: Frontline Workers' Intention to Use Personal Protective Equipment

BACKGROUND

Frontline workers (FLWs) are at a higher risk of COVID-19 infection during care interactions than the general population. Personal protective equipment (PPE) is regarded as an effective intervention for limiting the transmission of airborne viruses. However, research examining FLWs' intention to use PPE is limited.

OBJECTIVES

This study addresses this research gap and also contributes by expanding the conceptual mechanism of planned behavior theory by incorporating three novel dimensions (perceived benefits of PPE, risk perceptions of the epidemic, and unavailability of PPE) in order to gain a better understanding of the factors that influence FLWs' intentions to use PPE.

METHOD

Analysis is based on a sample of 763 FLWs in Pakistan using a questionnaire survey, and the structural equation modeling approach is employed to evaluate the suppositions.

RESULTS

Study results indicate that attitude, perceived benefits of PPE, and risk perceptions of the epidemic have positive influence on FLWs' intention to use PPE. In comparison, the unavailability of PPE and the cost of PPE have opposite effects. Meanwhile, environmental concern has a neutral effect.

CONCLUSIONS

The study results specify the importance of publicizing COVID-19's lethal impacts on the environment and society, ensuring cheap PPE, and simultaneously enhancing workplace safety standards.