Assessing the impact of geopolitical, economic, and institutional factors on China's environmental management in the Russian-Ukraine conflicting era.

In contemporary times, geopolitical risk, and natural resources prices are susceptible due to the Russian-Ukraine conflict. In the meantime, emerging economies are struggling to explore the factors that could reduce ecological challenges and enhance environmental management. This research aims to analyze several economic, environmental, political, and institutional variables to ascertain their influence on greenhouse gas emissions in China. Covering the latest period from 1990 to 2022, various time series tests, including normality, stationarity, and cointegration tests. The results confirm that the variables studied have a stable pattern over time and are connected in the long run. The non-normal distribution of variables leads to opt novel moment quantile regression, where the results are tested for robustness via parametric approaches. The empirical results asserted that economic growth, natural resource prices, and trade significantly enhance ecological challenges (emissions). However, globalization, geopolitical risk, and institutional quality significantly reduce such environmental challenges. The results are robust, and both unidirectional and bidirectional causal associations confirm the importance of these variables in environmental management. Based on the results, this study recommends engagement in environmentally-friendly trading, investment in clean and green energy, and strengthening institutional quality for the region's environmental recovery.

Economic and non-economic drivers of tourism: bidirectional causality of tourism and environment for South Asian economies.

This study explores the relationship between economic growth, tourism, and the environment in South Asian economies. It finds that factors such as GDP, human capital, globalization, and financial risk are interconnected and have long-term associations in these countries. The study employs various methodologies and tests to analyze the data. The author employs novel panel methodologies such as the method of moment of quantile regression analysis, slope heterogeneity, cross-section dependence test, and Westerlund cointegration. Additionally, a causality test along with the latest unit-root test is used. The results reveal important findings. As GDP expands, its impact on international tourism diminishes at higher quantiles, suggesting a decreasing effect. However, GDP still contributes positively to tourism across all quantiles. Human capital has a stronger effect on attracting tourists at lower quantiles, while globalization has varying impacts depending on the level of globalization in a country. Financial risk has a greater negative impact on tourism in larger economies compared to smaller ones. The study also examines the relationship between CO2 emissions and the variables under investigation. It finds that the effect of GDP on emissions decreases at higher quantiles, indicating a smaller contribution. Human capital has a larger effect on reducing emissions at lower quantiles, while the impact of globalization is more significant at higher quantiles. Moreover, an increase in financial risk leads to a decrease in emissions, particularly at lower quantiles. Based on these findings, the study suggests policy recommendations for South Asian economies. These include promoting sustainable tourism practices, investing in human capital development, encouraging responsible globalization, mitigating financial risks, and aligning tourism strategies with sustainable development goals.

Spatial green growth in China: exploring the positive role of investment in the treatment of industrial pollution.

The industrial sector of China is critical to the country's economic growth. On the other side, industrialisation has resulted in a high rate of emissions, pushing China to spend extensively on industrial pollution remediation. As a result, this study looks at the relationship between investment completed in the treatment of industrial pollution and economic development. Initially, the study used the global Moran's I test (Queen's contiguity matrix) to find spatial autocorrelation for the 'investment completed in the treatment of industrial pollution' factor, where the study found a positive association across Chinese provinces, and suggest the existence of spatial autocorrelation. Thereafter, a time-fixed effect spatial error model was used due to the lowest Akaike information criterion and Bayesian information criterion to analyse regional data of China from 1999 to 2018. The data reveal a positive association between investment completed in the treatment of industrial pollution and regional economic growth, both in the short and long term. Furthermore, the negative consequences of urban wages and foreign investment on investment completed in the treatment of industrial pollution are having the reverse effect on regional green development, necessitating ecologically friendly actions to mitigate the negative environmental effects of both. The results highlight the need for policymakers in other countries to review their plans for economic expansion and create environmentally friendly legislation. By implementing the Chinese green economic growth model, policymakers in industrially polluting nations can reduce industrial pollution and foster green growth in their nation.

Revisiting the nexus between fiscal decentralization and environment: evidence from fiscally decentralized economies.

Fiscal decentralization is a topic of great importance, especially in the context of environmental sustainability. Numerous research studies have been conducted on fiscal decentralization providing conflicting results, and therefore, the current study fills the gap by examining the effect of fiscal decentralization on environmental quality in the presence of environment-related technological innovation, renewable energy consumption, international trade, and economic growth taking seven fiscally decentralized advanced OECD countries as a case study. Using data from 1990 to 2018, we employed the Spatial Durbin Model (SDM) to test the spatial spillover effect of fiscal decentralization on the environment in seven fiscally decentralized countries. The primary findings show that carbon emissions are affected by the associated regions, which significantly correlates with the spatial distribution, and in the short run, fiscal decentralization increases carbon emissions. However, in the long run, fiscal decentralization decreases carbon emissions and is essential for achieving the goals of net-zero carbon emission. The results also show that the indirect effect is significantly positive in the economic-geographical weight matrix, and the spatial spillover effect of fiscal decentralization is not conducive to the environment of countries with economic exchanges. Furthermore, fiscal decentralization has a threshold effect, and the results show that when the fiscal decentralization degree is higher, it significantly reduces CO2 emissions. Any policy in these countries that target renewable energy, fiscal decentralization, and eco-innovation will significantly reduce carbon emissions.

Role of financial stability, technological innovation, and renewable energy in achieving sustainable development goals in BRICS countries.

Global warming is the buzzword these days, where researchers and policymakers are working hard to figure out its causes and how we can achieve sustainable development goals. Several research studies have been conducted to determine the key factors that influence environmental degradation. However, studies have ignored the role of financial institutions in achieving sustainable development goals. Therefore, the present study evaluates the influence of financial stability on consumption-based-carbon emission for BRICS countries in the presence of renewable energy, technological innovation, industry value-added, and international trade over the period of 1995 to 2018. This study has simulated its analyses by utilizing the spatial Durbin model through the spatial time-fixed effect technique due to the cross-border spillover effect. The results show that financial stability, technological innovation, economic growth, and imports contribute to consumption-based carbon emissions, whereas renewable energy and exports negatively influence consumption-based carbon emissions. In the case of cross-border spillover analysis, the study's findings revealed that only renewable energy has a positive spillover effect among the variables with a significant effect, whereas economic growth and bilateral export have a negative effect on consumption-based carbon emission.

Does environmental taxes achieve the carbon neutrality target of G7 economies? Evaluating the importance of environmental R&D.

The present study highlights the importance of environmental taxes and R&D in achieving the goal of carbon neutrality. Post Paris conference (COP21), countries set domestic targets to achieve zero carbon or carbon neutrality. Several studies have been conducted to explore the factors affecting environmental quality. However, the literature on the importance of environmental taxes and environmental R&D in affecting environmental quality is scant, and thus, this study investigates the impact of environmental taxes and R&D on consumption-based carbon emissions for G-7 countries over a period of 1990-2019. The cointegration test results show a stable long-run association between environmental taxes, environmental R&D, imports, exports, GDP, and consumption-based CO2 emissions. The results show that in the short- and long-run, environmental taxes, environmental R&D, and exports significantly reduce carbon emissions, whereas GDP and imports significantly enhance carbon emissions. The Dumitrescu and Hurlin Granger causality test results show that any policy that targets environmental taxes, environmental R&D, exports, imports, and GDP significantly changes CO2 emissions. This study recommends that policymakers in G-7 countries should focus on environmental R&D and taxes to achieve the goal of carbon neutrality.

China carbon neutrality target: Revisiting FDI-trade-innovation nexus with carbon emissions.

Since the Paris Agreement, countries around the globe have been striving to achieve their carbon neutrality targets. However, because China has one of the largest economies in the world, to achieve its targeted carbon neutrality, the roles of foreign direct investment (FDI), technological innovation (TI), and trade are crucial. Therefore, this study aims to introduce the level of trade, renewable energy consumption (REC), and FDI from the years 1995-2017 as new determinants in promoting a sustainable environment in China. The study employs advanced panel methods based on slope homogeneity and a cross-sectional dependence test. The results confirm a cointegration relationship for all models in this study, suggesting that gross domestic product and FDI positively affect carbon emissions. By contrast, foreign trade, REC, and TI are inversely associated with carbon emissions. Moreover, according to Chinese provincial data, the joint term for FDI with REC and TI is negatively associated with carbon emissions. The policy implications of this study suggest that to achieve sustainable FDI, TI should be encouraged to mitigate the pollution caused by FDI. There is a dire need to implement green practices and eco-friendly policies at a national scale.

Does financial stability and renewable energy promote sustainable environment in G-7 Countries? The role of income and international trade.

Financial stability is of great importance especially in the context of achieving sustainable environment. The objective of this study is to fill the research gap in this area by introducing financial stability, international trade, renewable energy, and income as novel determinants of consumption-based carbon emissions. The present study is based on G-7 economies, and the time period is from 1990 to 2018. The present study employed advanced econometric techniques that can deal with problems of slope homogeneity and cross-section dependence. The cointegration analysis results show a stable long-run association between financial stability, renewable energy, international trade, national income, and consumption-based carbon emissions with structural breaks (1994 Italy's fiscal crises, 2001 mild recession, 2008 global financial crises, and 2010 European debt crises). The results show that both in long- and short-run financial stability, exports and renewable energy significantly reduce carbon emissions. In contrast, national income and imports are found to have a significant positive effect on consumption-based carbon emissions. Policymakers in G-7 countries should focus more on financial sector stability and encourage firms to use renewable energy. Any policy that targets financial stability, exports, and renewable energy will significantly reduce carbon emissions. This study is a novel contribution to the area of consumption-based carbon emissions as it incorporates the role of financial stability for G-7 economies.

Does technological innovation limit trade-adjusted carbon emissions?

The objective of this analysis is to examine the impact of international trade and technological innovation over the 1990-2018 period on the G7 economy's consumption-based carbon emissions. The report explores international trade by separately considering imports and exports. The results indicate that the data cross-sections are dependent and that the panel has slope heterogeneity. The results of the co-integration study indicate that imports, exports of technological innovation, GDP, and demand-related carbon emissions are co-integrated with systemic splits (2001 mild recession, 2008 financial crises, and 2011 decline of stock market, and 2014 export decline). The cross sectionally augmented autoregressive distributive lag model results show that technological innovation and exports have a negative effect on the use of carbon. Meanwhile, imports and GDP are positive associated with carbon emissions based on consumption. The analysis of the robustness test also verifies these impacts. The results of this research study show that policymakers and regulators can encourage technological innovation to reduce carbon pollution and improve the sustainability of the environment.

Does air pollution upsurge in megacities after Covid-19 lockdown? A spatial approach.

The current coronavirus (COVID-19) pandemic has a high spreading and fatality rate. To control the rapid spreading of the COVID-19 virus, the government of India imposed lockdown policies, which creates a unique opportunity to analyze the impact of lockdown on air quality in the two most populous cities of India, i.e., Delhi and Mumbai. To do this, the study employed a spatial approach to examine the concentration of seven criteria pollutants, i.e., PM2.5, PM10, NH3, CO, NO2, O3, and SO2, before, during, and after a lockdown in Delhi and Mumbai. Overall, around 42%, 50%, 21%, 37%, 53%, and 41% declines in PM2.5, PM10, NH3, CO, NO2, and SO2 were observed during the lockdown period as compared to previous years. On the other hand, a 2% increase in O3 concentration was observed. However, the study analyzed the National Air Quality Index (NAQI) for Delhi and Mumbai and found that lockdown does not improve the air quality in the long term period. Our key findings provide essential information to the cities' administration to develop rules and regulations to enhance air quality.