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Determinants of trade openness are available in the literature; however, no substantial evidence available for the nexus between environmental quality, institutional quality, and trade openness with the presence of FDI as a mediating factor. With this study, we tried to figure out the answer to the question, i.e., whether the relationship between EQ, IQ, and TO is symmetric or asymmetric, provided that FDI is a mediating factor by performing ARDL, CS-ARDL, and nonlinear ARDL for 1982–2019. Furthermore, directional causality also evaluates by following the non-Granger causality test with symmetry and asymmetry of EQ, IQ, and FDI in respective equations. Study findings with ARDL and CS-ARDL document that positive outcomes are running from EQ, IQ, and FDI to trade openness, especially in the long run. Furthermore, asymmetric estimation establishes asymmetry shocks in EQ, IQ, and FDI which are positively linked with trade openness, especially in the long run. Moreover, the Wald test results ascertain the presence of asymmetry both in the long run and short run. The directional casualty with symmetry effects of EQ, IQ, and FDI disclosure feedback hypothesis explains trade openness’s causal effects. Besides, causality test with asymmetry divulges feedback hypothesis available between EQ and trade openness, i.e., [ EQ −  TO: EQ +  TO] and IQ and trade openness [ IQ −  TO: IQ +  TO], on the other hand, unidirectional casualty running from positive shocks in foreign direct investment to trade openness [ FDI +  TO].

The present paper aims to study the impacts of financial innovation on financial inclusion for selected 22 Arab countries from 2004 to 2020. It considers financial inclusion as a dependent variable. It describes ATMs and the number of commercial banks' depositors as proxy variables. In contrast, financial inclusion is considered an independent variable. We used the ratio between broad and narrow money to describe it. We employ several statistical tests such as lm, Pesaran, and shin W-stat, a- tests for cross-section dependence, and unit root and panel granger causality with NARDL and system GMM approaches. The empirical results reveal the significant nexus between these two variables. The outcomes suggest that adaptation and diffusion of financial innovation play catalyst roles in bringing unbanked people into the financial network. In comparison, the inflows of FDI establish mixed positive and negative effects, which vary with model estimation following different econometrical tools. It is also revealed that FDI inflow can augment the financial inclusion process, and trade openness can play a directive role and enhance the financial inclusion process. These findings suggest that financial innovation, trade openness, and institutional quality should continue in the selected countries to enhance financial inclusion and promote capital formation in the selected countries.

This study investigates the interplay between income from natural resources, education, access to financial services, and technological advancements in achieving Sustainable Development Goals (SDGs) 7 and 13 in eight resource-rich countries. Motivated by the global urgency for sustainable practices, this research employs a robust analytical framework to explore short- and long-term interactions among these variables, including panel data analysis, cointegration tests, and asymmetry coefficient estimation. Key findings reveal that income from natural resources is directly linked to increased CO2 emissions, emphasizing the environmental costs of resource exploitation. Conversely, higher education levels are associated with reduced CO2 emissions and ecological footprints, highlighting education’s vital role in environmental sustainability. At the same time, financial inclusion fosters economic growth and contributes to environmental degradation, necessitating regulatory measures. Technological innovation, particularly green technology, is crucial for mitigating environmental impacts. This study uniquely combines these factors to provide empirical evidence of their collective influence on sustainability, filling a gap in existing research. The results suggest that effective governance, environmental education, alignment of financial practices with sustainability goals, and support for green innovation are essential for harmonizing economic development with environmental conservation. Graphical Abstract

: As the world becomes increasingly aware of the need to shift towards sustainable energy sources, China and the United States are two global superpowers leading this transition. With growing populations and increasing demand for energy, these countries have recognized the importance of renewable energy in meeting their needs while reducing carbon emissions. The motivation of the study is to evaluate the impact of trade policy uncertainty on renewal energy demean in the USA and China for the period 2000-2021 by employing linear and nonlinear assessment. The test statistics derived through the cointegration test by following Bayer-Hancked and Makki's cointegration established a long-run tie in the empirical equation. Moreover, the long-run linkage was revealed with symmetry and asymmetry investigation. Referring to the coefficients of linear assessment, the study established that uncertainties have a detrimental role in clean energy demand in the long- and short-run assessment. The asymmetric association between uncertainties and REC has been documented through the execution of a standard weld test with the null of symmetry. The directional causality test established a unidirectional linkage between trade policy uncertainty and REC [TPU<- ->REC], and a bidirectional linkage between economic policy uncertainty and REC [EPU<- ->REC].

The motivation of the study is to gauge the role of economic policy uncertainty (EPU), environmental degradation (ED), and financial inclusion (FI) on remittances in India and China for the period 2003Q1-2022Q1. The study performed several econometrical tools such as both conventional and structural break unit root tests, long-run cointegration between variables investigative by performing the novel combined cointegration test, augmented autoregressive distributed lagged (AARDL) implemented for exploring long-run cointegration and explanatory variables magnfititutes on remittances both in the long-run and short-run and directional causality performed with Fourier TY causality test. Combined cointegration and the AARDL test ascertained the long-run association in the empirical equation. Refers to long-run coefficients of EPU, ED, and FI, it revealed a positive and statistically significant linkage with remittance inflows in the economy. In addition, the causality test reveals directional effects available between FDI, GLO, and remittances, but the direction differs from among economics. Furthermore, the study performed a robustness test by implementing dynamic OLS, fully modified OLS and CC regression and supported the earlier model established relationship, especially in the long-run the coefficients of  EPU, ED, and FI.

China’s fast industrialization and urbanization have led to impressive economic growth and caused severe environmental degradation, resulting in increased CO2 emissions. These emissions have increased by leaps and bounds with China’s rapid industrialization and urbanization. The case for sustainable development is compelling and has unleashed a search for green investments and technological innovations to meet the challenge. This study is motivated by the significant need to understand the effects of green finance, technological innovations, and environmental taxes on China’s economic growth and environmental sustainability. Furthermore, it tries to investigate how these elements may help make the model more sustainable and not endanger the developmental achievements of the country. For this purpose, we employed a comprehensive econometric approach through longitudinal data, and different models included Two-step GMM, Two-step system-GMM, and CS-ARDL. These methodologies portray various ways green investments, green technological innovation, tax, urbanization, inflows of FDI, and industrial structure intersect to influence environmental and economic outcomes in China. The results reflect a strong negative correlation with green investments made with CO2 emissions, proving that high investments in green technologies and practices effectively reduce carbon outputs. The study also underlined regional disparities and technological innovations in green. The study, therefore, recommends more efforts by Chinese policymakers on green finance and investment, standardization, and the rise in environmental standards across the country; enhanced efforts in further bringing down CO2 emissions through ecological taxes and incentives; and collective efforts with strong governmental support for research and development in low-carbon technologies that can help place China on a sustainable economic path.

The rapid technological and economic growth in CIVETS countries poses challenges to environmental sustainability. This study explores the intricate relationships between Information and Communication Technology (ICT), natural resource usage, and green innovation in these economies. Employing advanced statistical models uncovers long-term and short-term patterns, providing valuable insights for policymakers, stakeholders, and scholars. Key findings reveal that ICT diffusion can potentially reduce carbon emissions, while natural resource rent is linked to increased ecological footprints. Conversely, green technological innovation is promising in alleviating environmental degradation. The study underscores the importance of comprehensive policies integrating ICT diffusion, sustainable resource management, and green innovation. To achieve environmental sustainability, the study recommends responsible natural resource extraction, fiscal incentives for green innovation, digital tools for environmental monitoring, and international collaboration. Public awareness and sustainable urbanization practices guided by ICT are also crucial. These insights help policymakers balance economic development with ecological preservation in the CIVETS nations.

This study aims to explore the effects of renewable energy consumption, trade openness, and foreign direct investment on environmental sustainability in Bangladesh, assessed through innovative indicators of load capacity factor and inverted load capacity factor. The research utilizes Fourier ARDL, Fourier NARDL, Bayer-Hanck cointegration, and Fourier Toda-Yamamoto causality methods, employing annual data from 1990 to 2022 to examine both symmetric and asymmetric relationships. These advanced econometric techniques consider structural breaks, long-term dependencies, and nonlinear interactions between variables. The main findings indicate that renewable energy consumption positively influences the load capacity factor, enhancing energy efficiency and grid stability while reducing the inverted load capacity factor, which signifies environmental inefficiency. Foreign direct investment shows a dual effect: it boosts the load capacity factor when aligned with sustainable practices but leads to environmental degradation if unregulated. Trade openness fosters economic growth but has mixed effects on environmental sustainability and asymmetric impacts on the load capacity factor. The Fourier Toda-Yamamoto causality test confirms unidirectional causality from renewable energy consumption to the load capacity factor and bidirectional causality between foreign direct investment and trade openness with the load capacity factor. These findings support the Environmental Kuznets Curve hypothesis, which states that economic growth initially harms environmental quality but eventually promotes sustainability as green policies are implemented. The novelty of this research lies in the use of the load capacity factor and inverted load capacity factor as new sustainability indicators, moving away from traditional carbon emission-based metrics. Fourier-based econometric models enhance the robustness of the study by capturing cyclical variations and nonlinear interactions, thereby providing a more precise analysis of environmental sustainability dynamics. These findings contribute to redefining sustainability assessment frameworks in emerging economies. The policy recommendations include expanding renewable energy infrastructure through incentives, implementing green investment regulations for foreign investors, and adopting environmentally conscious trade policies. These measures will enable Bangladesh to balance economic growth and environmental sustainability and align its energy strategies with the Sustainable Development Goals.

This study examines the impact of remittances and financial inclusion on alleviating energy poverty in sub-Saharan Africa. Utilizing a Fourier-augmented machine learning framework from 2003 to 2023, the methodology integrates Fourier Toda–Yamamoto causality tests, panel cointegration, and CS-ARDL models across 36 countries. The results confirm that remittances significantly reduce energy poverty by enabling household investments in clean energy, especially where financial inclusion is strong. Financial services, such as credit and savings, are critical mediators for optimizing remittance utilization for sustainable energy infrastructure. The novelty of this study lies in the application of Fourier functions to detect nonlinear patterns and structural breaks, offering a robust estimation approach that overcomes the limitations of conventional econometric models. This pioneering combination of Fourier methods and machine learning enhances causal inferences in dynamic socioeconomic contexts. Policy recommendations include promoting financial inclusion through tailored banking services, incentivizing off-grid renewables, and fostering partnerships between banks and energy providers to align financial tools with the goals of energy development. Graphical Abstract

This study explores the role of foreign direct investment (FDI), financial development (FD), and globalization (GLO) in environmental degradation (ED) through the channel of energy consumption (EC) for the selected panel of belt and road initiative (BRI) countries for 1990–2017. The study applies appropriate panel unit root tests, the Westerlund cointegration test, the dynamic seemingly unrelated regression (DSUR) long-run panel estimation approach, and the Dumitrescu–Hurlin panel causality test. Results of panel unit root test ascertain variables are interred either at a level or after first difference and long-run association documents by implementing conventional and error correction. Study findings with DSUR, in the long run, reveal that energy consumption and economic growth expose positive statistically significant association with environmental degradation, implying intensity in energy consumption and aggregate output level shall augment the present state of environmental degradation. While negative statistically significant effects reveal running from FDI, financial development, and globalization to environmental degradation, implying that energy efficiency technology, the scope of green financing through financial development, and cross country effects help the economy reduce environmental consequences with lesser carbon emission. Results of directional causality unveiled feedback hypothesis available in explaining the causality between environmental degradation and energy consumption [ED←➔EC] and FDI and environmental degradation [FDI←➔ED], moreover, unidirectional effects running from financial development, globalization, and economic growth to environmental degradation, i.e., [FD➔ED; GLO➔ED; Y➔ED]. The finding reveals the need to formulate energy policies that promote belt and road (BR) country energy efficiency.