Effects of globalization, foreign direct investment and economic growth on renewable electricity consumption

Economic globalization-energy diversification nexus and implications for environmental management in China

Every nation on earth has the responsibility to implement effective environmental management measures for sustainable environmental quality. In doing so, this study scrutinizes the relationship between economic globalisation and energy diversification in the Chinese economy from 1995 to 2022 for designing and implanting policies for environmental management. It uses industrialization, foreign direct investment, foreign remittances, and information & communication technology as supplementary factors into augmented energy diversification demand function. This empirical analysis shows cointegration between the variables, with economic globalisation positively impacting energy diversification. Factors such as foreign direct investment, foreign remittances, and information & communication technology contribute to energy diversity. However, industrialization has an adverse relationship with energy diversification. The relationship forms an inverted-U shaped between economic globalization and energy diversification. Our causality analysis indicates that economic globalization positively causes energy diversification. This study also reveals a reciprocal and beneficial cause-and-effect association between foreign direct investment and energy diversification. Lastly, foreign remittances and information & communication technologies positively cause energy diversification.

Exploring the impact of climate technology, financial inclusion and renewable energy on ecological footprint: Evidence from top polluted economies

Most South Asian countries' economies have grown dramatically during the past few decades. However, in light of their environmental sustainability goals, the quality of such growth performances by South Asian nations is called into doubt by the concurrent degradation in environmental quality. Consequently, reducing the environmental challenges these nations encounter is prioritized on the agendas of the relevant authorities. This study aimed to analyze the effect of the top 11 most polluted countries' levels of financial inclusion, technological innovation, consumption of renewable energy, and adoption of climate technology on environmental deterioration from 2000 to 2022. Therefore, this research aims to use cutting-edge panel data econometric techniques to investigate the factors contributing to high carbon footprints in the world's most polluted nations. The results support an inverted U-shaped relationship between economic growth and carbon footprints, crediting the environmental Kuznets curve concept. In addition, it has been shown that TECH, REC, and CT can reduce carbon footprints in both the short and long term, while GDP and financial inclusion only affect carbon footprints in the long term. The results further endorsed the pollution haven hypothesis by showing that GDP positively affects carbon footprint. As a result, leading polluting economies need to strengthen their financial sectors, create green technology, migrate to renewable energy, and limit financial inclusion to improve environmental quality.

Assessing the impact of international trade on ecological footprint in Belt and Road Initiative countries

The Belt and Road Initiative (BRI) is one such comprehensive plan that aims to boost economic growth and connectivity across Africa, Asia, and Europe. While the effort may be good for boosting exports and foreign direct investment (FDI), some are worried about the toll it may take on the environment. Therefore, we aim to examine the effect of international trade and FDI on the ecological footprint in BRI countries, considering the mediating role of the environmental performance index. The CCEMG estimator was used to examine the impacts of imports, exports, FDI, population growth, urbanization, and the Environmental Performance Index (EPI) on the global ecological footprint. Our findings show that export has a positive relationship with ecological footprint. Similarly, imports and FDI revealed a positive association with the ecological footprint. Finally, environmental performance revealed a negative association with ecological footprint in BRI countries. Our findings support the pollution haven theory by demonstrating the critical importance of environmental regulations in enticing responsible investors. By using the ecological footprint as an all-encompassing measure of environmental effect, this study sheds light on the need to incorporate sustainability within the goals of the BRI. This research emphasizes the importance of adopting well-informed methods to promote sustainable development and mitigate the BRI's adverse environmental impacts.

Modeling hydro, nuclear, and renewable electricity generation in India: An atom search optimization-based EEMD-DBSCAN framework and explainable AI

Background and objective

Tracking clean electricity generation in developing economies is highly challenging owing to the influence of turbulent external factors. Clean electricity is a significant enabler of striving toward environmental sustainability. In this research, we aim to model hydro, nuclear, and renewable electricity generation in India through applied predictive modeling. We also strive to uncover the influence of the critical determinants responsible for clean electricity growth.

Methodology

We propose a granular predictive framework comprising ensemble empirical mode decomposition, clustering applications in spatial data based on density, including noise, and atom search optimization-based novel optimization methodology to predict absolute figures of clean energy generation. The framework uses a series of socio-economic factors reflecting household demand and industrial growth in India as explanatory variables.

Results

The rigorous scrutiny of the predictive framework specifies hydro electricity generation is relatively more predictable during the time horizon influenced by the COVID-19 pandemic. The deployment of dedicated explainable artificial intelligence (AI) tools suggests an increased adoption of clean electricity in selected industrial sectors in India, which broadly governs the evolutionary pattern.

Conclusion

The underlying research is the first of its kind to fathom the daily temporal dynamics of clean electricity generation in the Indian context. Consideration of three distinct clean electricity sources during highly volatile time regimes underscores the contribution of the work. The predictive framework survives a stringent performance check, which justifies the robustness of the same. Demand in different industrial sectors in India profoundly influences the growth toward clean electricity.

Does globalization matter in the relationship between renewable energy consumption and economic growth, evidence from Asian emerging economies

The study aims to investigate the impact of social, economic and political globalization on the renewable energy-economic growth nexus in a panel of six Asian emerging economies over the period 1975-2020. The results of the CS-ARDL approach show that renewable energy consumption contributes significantly to long run economic growth. Economic and political globalization firmly hold back economic growth, while social globalization directly promotes economic growth. The nonlinear effects of political, social, and economic globalization on economic growth clearly demonstrate the validity of the inverted U-shaped relationship between political globalization, economic globalization, and economic growth, and the U-shaped relationship between social globalization and economic growth. The study also found that economic, social and political globalization moderated the impact of renewable energy on boosting economic growth. Based on the renewable energy consumption model, it is revealed that economic growth significantly promotes long run renewable energy consumption. Economic, social, and political globalization have significantly boosted long run renewable energy consumption. However, the nonlinear effect model reflects a U-shaped relationship between globalization indicators and renewable energy consumption. The interaction of political, economic, and social globalization with economic growth has also witnessed an increase in renewable energy consumption, which supports the scale effect hypothesis. The causality test concludes that there is a two-way causal relationship between renewable energy consumption and economic growth, thus supporting the feedback hypothesis. The policy implications for Asian emerging economies are discussed based on the empirical analysis of this study.

How natural resources depletion, technological innovation, and globalization impact the environmental degradation in East and South Asian regions

Rapid economic expansion has caused resource depletion, globalization issues, and environmental deterioration. Globalization has highlighted East and South Asian mineral richness. This article investigates the effects of technological innovation (TI), natural resources, globalization, and renewable energy consumption (REC) on environmental deterioration in the East and South Asian region from 1990 to 2021. The cross-sectional autoregressive distributed lag (CS-ARDL) estimator is used to estimate short- and long-run slope parameters and dependencies across countries. The results demonstrate that many natural resources significantly enhance environmental degradation, while globalization, TI, and REC reduce emission levels in East and South Asian economies and that economic growth significantly degrades ecological quality. This research suggests that governments in the East and South Asian region develop suitable policies that promote the efficient use of natural resources via technological advancements. Furthermore, future policies regarding energy consumption, globalization, and economic development should be aligned with the aims of sustainable environmental development.

Do economic freedom, innovation, and technology enhance Chinese FDI? A cross-country panel data analysis

This study evaluates the determinants of Economic freedom, innovation and technology concerning Chinese foreign direct investment. The aim of the study is to explore, that how these determinants influence Outward Foreign Direct Investment (OFDI) from China toward different regional economies. The study will enrich the existing literature by providing useful policies to the concerned economies to influence more Chinese FDI to host economies. The panel data set includes 27 (African, European, and Asian) Countries data over the period of 2003 to 2018. Moreover, the study employed panel data analysis and the result reveals that property rights, patents residents (pantentAR), Research & Development (R&D), Inflation, official exchange rate (OER), and Tax Burden (TaxB) have a strong positive and significant impact on Chinese OFDI in the selected sample countries, While Government Expenditures (GovE) has positive, but insignificant impact on Chinese OFDI. On the other hand, Chinese OFDI is negatively and statistically significant association with Business Freedom (BusF). This study will put forth considerable policies to the concerned to induce further inflows of Chinese FDI into the host countries. The policymakers should build policies that provide a comfortable environment for business activities and mostly focus on value-added production i.e., expenditures on R&D to enhance high-technology exports because they efficiently attract FDI into host countries. Another key factor is Tax Burden (TaxB), which significantly influences Chinese FDI along with other factors.