Investigating the environmental externalities of digital financial inclusion and the COVID-19 pandemic: an environmental sustainability perspective.

Financial inclusion enhances economic growth by facilitating businesses and individuals to access financial resources. Financial inclusion also contributes to environmental sustainability; however, very few studies have explored the link between financial inclusion and the environment. Also, the impact of the COVID-19 pandemic on environmental performance remains unexplored. From this perspective, this study probes the objective of whether financial inclusion and environmental performance co-move in COVID-19 in highly polluted economies. This objective is tested with the help of 2SLS and GMM approaches. The study also gets assistance from a panel quantile regression approach for empirical tasks. The results show that financial inclusion and the COVID-19 pandemic have a negative impact on CO2 emissions. Based on these findings, the study suggests that highly polluted economies should promote financial inclusion and assimilate environmental policies with financial inclusion policies to attain environment-related goals.

Financial inclusion and low-carbon architectural design strategies: solutions for architectural climate conditions and architectural temperature on new buildings.

The objective of this research is to explore the potential of financial inclusion and low-carbon architectural design strategies as solutions to improve the thermal comfort and energy efficiency of new buildings in different architectural climate conditions. The manufacture sector, which accounts for about 40% of all yearly greenhouse gas releases, has been stimulating with trying to reduce the amount of energy it consumes and the detrimental effects it has on the climate, in accordance with the standards outlined in the 2016 Paris Agreement. In this study, panel data analysis is used to examine the connection between green property financing and carbon dioxide emissions from the building sector in one hundred and five developed and developing countries. Although this analysis finds a negative correlation among the development of environmentally friendly real estate financing and firms' worldwide carbon dioxide emissions, it finds that this correlation is most robust in developing nations. A number of these countries are experiencing an unregulated and rapid population explosion, which has boosted their demand for oil, making this discovery essential for them. The difficulty in securing green funding during this crisis is slowing and even reversing gains made in past years, making it all the more important to keep this momentum going during the COVID-19 outbreak. It's critical to keep the momentum going by doing something.

Investigating asymmetric impacts of total factor energy efficiency on carbon emissions in India.

As many complex energy relations are not linear and have diminishing returns, assuming a symmetric (linear) effect of energy efficiency (ENEF) on carbon emissions (CAE) has limited our understanding of the emission-ENEF nexus. This research, therefore, initially estimates total factor energy efficiency by applying a stochastic frontier technique using sample panels for India encompassing the period from 2000 to 2014. Further, a nonlinear panel autoregressive distributed lag modelling framework is utilised in order to investigate the asymmetric (nonlinear) long- and short-run impacts of ENEF on CAE. The findings demonstrated that ENEF has asymmetric long- and short-run impacts on CAE in India. Based on the outcomes, numerous crucial implications are discussed with a particular reference to developing economies like India.

Financial stability influence on climate risk, GHG emission, and green economic recovery of China.

This study examines the nexus between financial stability, climate risks, GHG emission mitigation, and green economic recovery of China. Financing efforts to protect against and reduce the hazards associated with climate change need to consider these risks and resources. Study used the Kalman technique of analysis for empirical inference. This research focuses on the carbon risk in China by employing a Kalman estimation approach. Although environmental mitigation was found to be important at 39%, financial strength and carbon hazards were considerable at 34%. Moreover, the report demonstrates the relationship between climatic threats and environmental drift in China, at a rate of 17%, emphasizing the need to address climate change issues. A state's fiscal health guarantees national economic security while pursuing green economic recovery initiatives. Researchers concluded that precise policy suggestions were needed to promote green economic development.

Economic development, social media awareness, and technological innovation in biogas sector under climate change in the post-COVID-19 pandemic conditions.

After COVID-19, financing for emerging nation reserves in renewable energy bases was deemed a crucial aspect of sustainable development. Investing in biogas energy plants can be highly beneficial for lowering the use of fossil fuels. Using a survey of shareholders, investors, biogas energy professionals, and active social media participants in Pakistan, this study evaluates the intentions of individual investors to invest in biogas energy plants. The primary purpose of this study is to increase investment intent for biogas energy projects following COVID-19. This study focuses on financing biogas energy plants in the post-COVID-19 era and evaluates the research's assumptions using partial least squares structural equation modeling (PLS-SEM). The study employed the technique of purposive sampling to acquire data for this investigation. The results indicate that attitudes, perceived biogas energy benefits, perceived investment attitudes, and supervisory structure evaluations inspire one's propensity to finance biogas vitality plant efforts. The study found a link between eco-friendly responsiveness, monetary benefits, and investors' actions. The aspiration of investors to mark such reserves was set up to be unpretentious by their risk aversion. Conferring to the facts, evaluating the monitoring structure is the critical factor. The previous studies on investment behavior and other forms of pro-environmental intent and action yielded contradictory results. In addition, the regulatory environment was evaluated to see how the theory of planned behavior (TPB) affects financiers' objectives to participate in biogas power plants. The consequences of the study indicate that feelings of pride and discernment of energy expansively affect people's desire to invest in biogas plants. Biogas energy efficacy has little effect on investors' decisions to invest in biogas energy plants. This study offers policymakers practical ideas on enhancing investments in biogas energy plants.

Evaluating the trilemma nexus of digital finance, renewable energy consumption, and CO2 emission: evidence from nonlinear ARDL model.

It has been established in 2030 sustainability objectives as per SDGs that highlight the critical importance of access to affordable, renewable energy, robust, long-term industrial progress, and digital financing in CO2 emission. The intent of study is to test the trilemma nexus between digital finance, renewable energy consumption, and carbon emission reduction with nonlinear ARDL tests. The study acquired the data and applied the nonlinear ARDL test, split analysis tests, and vector-error correction model (VECM) tests. The results of the study highlighted that the increase of digital finance positively enhances the renewable energy and negatively reduces the CO2 emissions which we calculate to be 11.4% of the digital finance funding on renewable energy goods. For this, a 39% increase in digital financing is noticed by the research findings during the COVID-19 crisis period. Such robust study findings present the latest insights that digital financing is an eminent and viable source of financing for the trilemma nexus with renewable energy consumption and the CO2 emissions. Following these, multiple research implications are also presented for the key stakeholders.

Environmental reverberations of geopolitical risk and economic policy uncertainty resulting from the Russia-Ukraine conflict: A wavelet based approach for sectoral CO2 emissions.

After the COVID-19 pandemic, Russia invaded Ukraine in February 2022, and a natural gas crisis between the European Union (EU) and Russia has begun. These events have negatively affected humanity and resulted in economic and environmental consequences. Against this background, this study examines the impact of geopolitical risk (GPR) and economic policy uncertainty (EPU) caused by the Russia-Ukraine conflict, on sectoral carbon dioxide (CO2) emissions. To this end, the study analyzes data from January 1997 to October 2022 by using wavelet transform coherence (WTC) and time-varying wavelet causality test (TVWCT) approaches. The WTC results show that GPR and EPU reduce CO2 emissions in the residential, commercial, industrial, and electricity sectors, while GPR increases CO2 emissions in the transportation sector during the period from January 2019 to October 2022, which includes Russia-Ukraine conflict. The WTC analysis also indicates that the reduction in CO2 emissions provided by the EPU is higher than that of the GPR for several periods. According to the TVWCT, there are causal impacts of the GPR and the EPU on sectoral CO2 emissions, but the timing of the causal impacts differs between the raw and decomposed data. The results suggest that the EPU has a larger impact on reducing sectoral CO2 emissions during the Ukraine-Russia crisis and that production disruptions due to uncertainty have the greatest impact on reducing CO2 emissions in the electric power and transportation sectors.

Economic growth, social, and welfare development during COVID-19 pandemic: do country-specific characters matter in the MENA region?

The coronavirus disease 2019 (COVID-19) pandemic has generated major shocks that have crippled the economic development of many countries and regions. The COVID-19 pandemic has hampered not only economic development but also global countries from achieving their sustainable development goals through various channels. Given their first experience, many countries have no guidelines for measuring the true impact of the pandemic on their economic and social development, either at the global, regional, or country level. Amid the current slow research development in this area, this study investigates the medium- and long-run impact of the COVID-19 pandemic on the United Nation's achievement of sustainable development goals. The sample in the study comprises the Middle East and North African countries, including Algeria, Bahrain, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Qatar, Saudi Arabia, Syria, Tunisia, United Arab Emirates, and Yemen. The social development goals are approximated by economic growth and human development index, which play as the dependent variables representing two models, respectively. From another aspect, independent variables are derived from three primary sectors: government, households, and healthcare providers. In estimating the model, the study implements the panel regression estimation method using multiple variance estimators. The study findings will help policymakers formulate deliberate policy plans to stabilize economic and social fluctuations in the region and to improve the performance of basic macroeconomic parameters.

Dynamics of renewable energy index in G20 countries: influence of green financing.

The research intends to investigate the green financing trends movement with renewable energy dependence of G-20 economies. The data envelopment analysis (DEA) technique explains research results and illustrates current topicality. The Wald econometric method is utilized for robustness analysis, and a comparative picture of public support is provided. The research demonstrated that green financing metrics are significantly affected by public support during the COVID-19 crisis. Due to the volatility of COVID-19, public assistance funding plays an uneven role in green finance. G-20 member nations financed 17% of total green financing using public funds, which contributed 4% to GDP and achieved 16% of annual energy dependence improvement due to COVID-19 and 24% additional production from renewable energy resources. The results of this research demand maximal support by using positions in the government, ministries in charge of energy efficiency, and departments for energy efficiency improvement. Several possible policy interventions are discussed in this paper that may increase renewable energy efficiency via several alternative approaches, including on-bill financing, direct efficiency grant, guaranteed energy efficiency contracts, and credit lines for energy efficiency. If recommended policies are implemented successfully, they are expected to reduce the crisis' impact and elevate funding for energy efficiency.

Potential pathways to reach energy-related CO2 emission peak in China: analysis of different scenarios.

The prevalence of global unilateralism and the shock of COVID-19 brought considerable uncertainty to China's economic development. Consequently, policy selection related to the economy, industry, and technology is expected to significantly impact China's national economic potential and carbon emission mitigation. This study used a bottom-up energy model to assess the future energy consumption and CO2 emission trend before 2035 under three scenarios: a high-investment scenario (HIS), a medium-growth scenario (MGS), and an innovation-driven scenario (IDS). These were also used to predict the energy consumption and CO2 emission trend for the final sectors and calculate each sector's mitigation contribution. The main findings were as follows. Firstly, under HIS, China would achieve its carbon peak in 2030, with 12.0 Gt CO2. Moderately lowering the economic growth rate to support the low-carbon transition of the economy by boosting the development of the low-carbon industry and speeding up the employment of key low-carbon technologies to improve energy efficiency and optimize energy structure in the final sectors, the MGS and the IDS would achieve carbon peak approximately in 2025, with a peak of 10.7 Gt CO2 for the MGS and 10.0 Gt CO2 for the IDS. Several policy recommendations were proposed to meet China's nationally determined contribution targets: instigating more active development goals for each sector to implement the "1+N" policy system, taking measures to accelerate the R&D, boosting the innovation and application of key low-carbon technologies, strengthening economic incentives, forming an endogenous driving force for market-oriented emission reduction, and assessing the climate impacts of new infrastructure projects.

Local Fiscal Pressure and Public Health: Evidence from China.

Under the dual challenges of global downward economic pressure and the COVID-19 pandemic, studying the impact of local government fiscal pressure on public health is a meaningful endeavor. First, this paper analyzes the impact of local government fiscal pressure on public health and clarifies its impact mechanisms. Second, by utilizing panel data of 31 Chinese provinces from 2000 to 2020, two-way fixed-effects and mediating-effects models are developed to identify the effects and impact mechanisms of local government fiscal pressure on public health. The results show that local government fiscal pressure can be detrimental to public health through three main mechanisms: reducing public health fiscal expenditures, hindering industrial structure upgrading, and exacerbating environmental pollution. Heterogeneity analysis finds that the negative effects of local government fiscal pressure on public health mainly exist in Central and Western China. Accordingly, three policy implications are proposed: optimizing the fiscal system, accelerating industrial upgrading, and improving the appraisal system of local officers.

Uncertainty quantification of CO2 emissions from China's civil aviation industry to 2050.

To mitigate aviation's carbon emissions of the aviation industry, the following steps are vital: accurately quantifying the carbon emission path by considering uncertainty factors, including transportation demand in the post-COVID-19 pandemic period; identifying gaps between this path and emission reduction targets; and providing mitigation measures. Some mitigation measures that can be employed by China's civil aviation industry include the gradual realization of large-scale production of sustainable aviation fuels and transition to 100% sustainable and low-carbon sources of energy. This study identified the key driving factors of carbon emissions by using the Delphi Method and set scenarios that consider uncertainty, such as aviation development and emission reduction policies. A backpropagation neural network and Monte Carlo simulation were used to quantify the carbon emission path. The study results show that China's civil aviation industry can effectively help the country achieve its carbon peak and carbon neutrality goals. However, to achieve the net-zero carbon emissions goal of global aviation, China needs to reduce its emissions by approximately 82%-91% based on the optimal emission scenario. Thus, under the international net-zero target, China's civil aviation industry will face significant pressure to reduce its emissions. The use of sustainable aviation fuels is the best way to reduce aviation emissions by 2050. Moreover, in addition to the application of sustainable aviation fuel, it will be necessary to develop a new generation of aircraft introducing new materials and upgrading technology, implement additional carbon absorption measures, and make use of carbon trading markets to facilitate China's civil aviation industry's contribution to reduce climate change.

Do Environmental Regulations Facilitate a Low-Carbon Transformation in China's Resource-Based Cities?

Resource-based cities (RBCs) are not only important for ensuring national resource and energy security, but they also face serious ecological and environmental problems. To achieve China's carbon peaking and neutrality goals in the coming years, RBCs' achievement of a low-carbon transformation has become increasingly significant. The core of this study is an investigation as to whether governance, including environmental regulations, can facilitate the low-carbon transformation of RBCs. Based on RBC data from 2003 to 2019, we establish a dynamic panel model to research the influence and mechanism of environmental regulations on low-carbon transformation. We found that China's environmental regulations facilitate a low-carbon transformation in RBCs. Mechanism analysis identified that the environmental regulations facilitate the low-carbon transformation in RBCs by strengthening foreign direct investment, enhancing green technology innovation and promoting industrial structure upgrading. Heterogeneity analysis found that the environmental regulations play a greater role in facilitating the low-carbon transformation of RBCs in regions with more developed economies and less dependence on resources. Our research provides theoretical and policy implications for environmental regulations for the low-carbon transformation of RBCs in China, applicable to other resource-based areas.

FDI and Wellbeing: A Key Node Analysis for Psychological Health in Response to COVID-19 Using Artificial Intelligence.

Developing countries are primary destinations for FDI from emerging economies following the World Investment Report 2022, including destinations in OECD countries. Based on three theoretical lenses and case analyses, we argue that Chinese outward FDI has impacts on wellbeing in destination countries, and that this is an important issue for psychological health in response to COVID-19. Based on the super-efficiency DEA approach, our study investigated the impact of Chinese outward FDI on wellbeing in OECD countries. We also applied a Tabu search to identify country groups based on the relationship between Chinese outward FDI and wellbeing and we developed a key node analysis of the country groups using an immune algorithm. This research has implications for public administrators in global governance and could help shape FDI policies to improve psychological health of the destination countries in response to COVID-19.

Impact of COVID-19 on the national development of countries: Implications for the public health.

The article focuses on measuring the fluctuations in countries' development as a result of the COVID-19 pandemic. The obtained measures make it possible to predict the extent of the impact of risks to public health on the economy, financial-budgetary, political-institutional development of states in the future, as well as the social determinants of public health. This assessment represents a new paradigm that makes it possible to effectively evaluate the manifestations of the consequences of COVID-19 and to identify the relevant determinants of the lack of resilience of the medical and social security systems to the coronavirus pandemic around the world. We picked the determinant of national development indicators of the 59 countries in order to measure the fluctuations in their economic development. In addition, we applied the binary response model for identifying the economic, financial-budgetary, and political-institutional development change with the happiness index of the countries being the dependent variable. The analysis of our empirical model made it possible for us to conclude that economic and financial-budgetary components have significantly increased the influence on well-being during the COVID-19 pandemic. In contrast, we observed the decrease in the impact of political and institutional indicators during the same period.

Spatial Concentration of Health Industry under COVID-19.

The COVID-19 pandemic has impacted the industry immensely and, in some cases, irreversibly. This research pioneers in studying how the pandemic have influenced the survival and spatial distribution of the health-related manufacturing industry (HRMI) in Taiwan. Eight categories of HRMI are examined, with their change in survival performances and spatial concentration between 2018 and 2020. Average Nearest Neighbour and Local Indicators of Spatial Association are conducted, to visualise the distribution of industrial clusters. We found the pandemic did not shock the HRMI in Taiwan, but actually induced its growth and spatial concentration to a certain extent. Additionally, due to it being a knowledge-intensive industry, the HRMI mainly concentrate in metropolitan areas with which universities and science parks may have largely supported. However, the spatial concentration and cluster scope growth do not necessarily accompany the improvement of spatial survival, which may be resulted from the different life cycle stages an industry category is in. This research fills in the gap of medical studies with literatures and data from the field of spatial studies. It provides interdisciplinary insights under the condition of pandemic.

Impact of COVID-19 on China's business and economic conditions: the importance of quantile asymmetries.

China has remained a growth engine for the global economy for the last several years. In this study, we assess the impact of COVID-19 on China's business and economic conditions; employing the quantile-on-quantile (QQ) regression and the quantile causality approaches. These econometrics batteries suit our research postulation, as they are capable to delineate underlying asymmetries across the whole distribution, based on which we can infer whether the response of China's business and economic conditions towards COVID-19 is heterogenous or homogenous. Utilizing the novel business and economic conditions measures, we observed that COVID-19 had initially disrupted both business and economic conditions in China. However, they showcased recovery over time. Our in-depth analysis allowed us to infer that the effect of COVID-19 on China's business and economic conditions is heterogeneous across different quantiles, and there is reliable evidence of asymmetry. The outcomes of quantile causality in mean and variance corroborate our primary estimations. These findings educate policymakers, companies, and other stakeholders to understand the nuances of China's business and economic conditions vis-a-vis COVID-19 in the short-run and as time elapsed.

Can Stringent Government Initiatives Lead to Global Economic Recovery Rapidly during the COVID-19 Epidemic?

This paper investigates the effectiveness of government measures implemented against COVID-19 and the factors influencing a country's economic growth from a global perspective. With the help of the data of the Government Response Stringency Index (GRSI), Google mobility, and confirmed COVID-19 daily cases, we conducted a panel model for 105 countries and regions from 11 March 2020 to 31 June 2021 to explore the effects of response policies in different countries against the pandemic. First, the results showed that staying in residential places had the strongest correlation with confirmed cases. Second, in countries with higher government stringency, stay-at-home policies carried out in the early spread of the pandemic had the most effective the impact. In addition, the results have also been strictly robustly analyzed by applying the propensity score matching (PSM) method. Third, after reconstructing a panel data of 47 OECD countries, we further concluded that governments should take stricter restrictive measures in response to COVID-19. Even though it may also cause a shock to the market in the short term, this may not be sustainable. As long as the policy response is justified, it will moderate the negative effect on the economy over time, and finally have a positive effect.

Borderland Economic Resilience under COVID-19: Evidence from China-Russia Border Regions.

The COVID-19 pandemic has had a great impact on the global economy and trade, and border regions have been hit severely because of their high dependency on foreign trade. To understand better the economic impact of COVID-19 on border regions, we developed a COVID-19 economic resilience analytical framework and empirically examined 10 Chinese-Russian border cities in Northeast China. We quantitatively analyzed five dimensions of economic resilience, distinguished four types of shock, and examined the determinants of economic resilience. The results show that: (1) the COVID-19 pandemic has wide-ranging impacts in the border areas, with import-export trade and retail sales of consumer goods being the most vulnerable and sensitive to the shock. The whole economy of the border areas is in the downward stage of the resistance period; (2) from a multi-dimensional perspective, foreign trade and consumption are the most vulnerable components of the borderland economic system, while industrial resilience and income resilience have improved against the trend, showing that they have good crisis resistance; (3) borderland economic resilience is a spatially heterogeneous phenomenon, with each border city showing different characteristics; (4) economic openness, fiscal expenditure, and asset investment are the key drivers of economic resilience, and the interaction between the influencing factors presents a nonlinear and bi-factor enhancement of them. The findings shed light on how border economies can respond to COVID-19, and how they are useful in formulating policies to respond to the crisis.