A note about globalization and development in Ecuador

Considering the contemporary, rapidly evolving society, renewable energy emerges as a key element in advancing both environmental resilience and energy independence. The current study aims to undertake a comparative analysis of the renewable energy adoption between the Old Member States (OMSs) and New Member States (NMSs) of the European Union (EU). This study focuses on regional heterogeneity as well as the role of economic, social, and environmental determinants in shaping effective energy transition policies. This study uses advanced long-term panel estimates such as Dynamic Ordinary Least Squares (DOLS), Fully Modified Least Squares (FMOLS) and Canonical Cointegration Regression (CCR) on a dataset covering the 2010–2023 period. Moreover, this study utilizes quantile regression methods such as Quantile Regression (QREG) and Method of Moments Quantile Regression (MMQR). Finally, this study employs the Dumitrescu–Hurlin test to assess panel causality. The empirical findings reveal notable discrepancies between the two samples when it comes to fossil fuel reliance, income inequality, financial and economic development, the existing level of greenhouse gas emissions, and green finances influencing renewable energy adoption. In the OMS region, a 1% increase in GHG and income inequality reduces the adoption of renewable energy by 0.80–1.14% and 0.61–0.67%, respectively, while a 1% increase in GDP increases the adoption of renewable energy by 0.72–0.92%. In the NMS region, GHG inhibits renewable energy transition by 0.27–0.30%, while fossil fuel energy share, income inequality, green finance, GDP and financial development do not have a significant effect. These results highlight economic development as the key to renewable energy transition in OMSs, while in NMSs, GHG and financial development are key levers. This research seeks to support the developing and restructuring of the existing green framework to enhance its overall effectiveness.

This study is to examine the relationship between information and communication technology (ICT) and financial development in the Turkish economy during the period of 1986–2018. By empirical literature, economic growth, technological innovation, and financial globalization are added to the financial development model as explanatory variables. The autoregressive distributed lag (ARDL) model and Hatemi-J cointegration test with two structural breaks are applied to examine the presence of cointegration between the variables. Dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR) estimation techniques are applied for long-term estimates. The vector error correction model (VECM) Granger causality approach is used for causality analysis. Our empirical results show that under the structural break, ICT, economic growth, technological innovation, and financial globalization are cointegrated with financial development. In the presence of a structural break, ICT and technological innovation negatively affect financial development, while economic growth and financial globalization have a positive impact on financial development. The causality analysis determines that there is a one-way causality relationship running from ICT and economic growth to financial development. In addition, technological innovation and financial globalization lead to long-term financial development. Empirical findings have important policy recommendations for financial development in the Turkish economy.

Addressing global environmental concerns requires the widespread adoption of renewable energy sources. More research is needed to examine the relationships between renewable energy (RE) and globalization, economic growth, and environmental quality in Indonesia. Therefore, we examined how renewable energy usage in Indonesia has changed due to the dynamic effects of globalization, financial development, and environmental quality. Time-series data were analyzed using an autoregressive distributed lag (ARDL) model to test for cointegration and long-run/short-run dynamics between 1990 and 2020. In addition to ARDL bounds testing, we used the Johansen and Engle-Granger cointegration methods for confirmation. Globalization, financial progress, human capital, greenhouse gas emissions, and economic expansion have favorable long- and short-term effects on renewable energy sources. Globalization has enabled Indonesia to expand trade, FDI, and financial investment. It has also increased energy-efficient technology use due to environmental policies. The computed results are robust enough to substitute estimators, such as dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). We recommend the implementation of policies that support financial and environmental development by utilizing renewable resources and increasing investments in renewable energy ventures.

This study is an attempt to explain the nexus between health expenditures, GDP, human development index (HDI), CO2 emissions (COEM), renewable energy (RENE), financial development (FD) and electricity consumption (EC) using data from 2000Q1 to 2014Q4 for Brazil, India, China and South Africa. The study applies CIPS and CADF to determine the integration order. The tests confirmed the unique order of integration. The study further uses the Westerlund panel cointegration, which suggests the existence of a long-run relationship. Moreover, the panels dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) are applied to ascertain the long-run elasticity. The health expenditure and electricity consumption affect the COEM positively. Moreover, HDI and RE affect COEM negatively. The study further confirms the existence of an N-shaped EKC in the long run. The pairwise Dumitrescu and Hurlin, Econ Model 29:1450-1460, (2012) test is used to uncover the direction of the association between the variables. The findings obtained from DH confirm a bidirectional causality between HDI and FD. Likewise, another bidirectional causal relationship has also been found between FD and EC. The findings of our study advocate policies in the direction of HDI and health expenditure by adopting RENE. This study highlights the importance of RENE, which can facilitate a reduction in carbon emissions and decreasing health expenditures. Moreover, the financial sector needs to be improved to create entrepreneurship opportunities for the public in improving the HDI in ensuring sustainable development.

• Improving environmental quality through reducing emissions is the central pillar of climate change mitigation and achieving sustainable development goals. • The empirical findings reveal that economic growth, energy use, urbanization, and reduced agricultural productivity increase CO 2 emissions in Bangladesh. • Several unit root tests (ADF, DF-GLS, and P-P), cointegration test (ARDL bounds test, Johansen cointegration test, and Engle-Granger cointegration test), and cointegration models (DOLS, FMOLS, CCR) have been utilized to confirm the accuracy of the results. • The findings of the study offer policymakers more detailed and helpful information for establishing successful policies in the areas of low-carbon economies, renewable energy, sustainable urban development, and climate-smart agriculture that would reduce emissions in Bangladesh. Greenhouse gases (GHGs) emissions, notably carbon dioxide (CO 2 ) emissions are causing global climate change, which poses enormous hazards to human life, the environment, development, and sustainability. Bangladesh is predominantly an agricultural country experiencing continuous economic growth and rapid urbanization which is causing higher energy consumption and CO 2 emissions. The present study empirically explores the nexus between economic growth, energy use, urbanization, agricultural productivity, and CO 2 emissions in Bangladesh. Time series data from 1972 to 2018 were utilized by employing the Dynamic Ordinary Least Squares (DOLS) approach. The Autoregressive Distributed Lag (ARDL) bounds test revealed evidence of cointegration among the variables in the long run which has been verified by the Johansen cointegration test and Engle-Granger cointegration test. The empirical findings reveal that economic growth, energy use, urbanization, and reduced agricultural productivity increase CO 2 emissions in Bangladesh. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). In addition, the pairwise Granger causality test is utilized to capture the causal linkage between the variables. This study adds to the current body of knowledge by shining light on the factors that contribute to environmental degradation in Bangladesh. This article put forward policy recommendations aimed at sustainable development by establishing strong regulatory policy instruments to reduce environmental degradation.

This paper investigates the oil resource abundance and environmental quality nexus in Algeria, with emphasis on the role of oil export receipts and domestic oil consumption, and whether financial development is a policy option for reducing carbon dioxide (CO2) emissions in the economy. Using time series data from 1971 to 2016, the Bayer–Hanck test for cointegration confirms the presence of a long‐run equilibrium relationship among the variables. Further analyses based on the auto‐regressive distributed lag (ARDL) model, fully modified least square (FMOLS), dynamic ordinary least square (DOLS), canonical cointegration regression (CCR) and Granger causality based on the vector error correction model (VECM) confirm the oil resource abundance curse in Algeria via the impact of domestic oil consumption on environmental quality. The estimates also show that financial development reduces CO2 emissions and has both short‐run and long‐run causal impact on economic growth. Thus, deepening financial sector development can be instrumental for achieving a low‐carbon and sustainable economy in Algeria.

Uruguay has set a target of becoming carbon neutral by the year 2030, and this study looks into the role that economic progress, renewable energy utilization, technological innovations, and forest extent could play in reaching the goal. The Dynamic Ordinary Least Squares (DOLS) technique was applied to examine time series data from 1990 to 2021. According to the outcomes of the DOLS estimation, a one-percentage-point boost in economic growth is associated with a 1.16% increase in CO2 emissions. However, increasing the use of renewable energy by 1% is related to a reduction in CO2 emissions of 0.73 percent over the long run, as indicated by the coefficient of renewable energy being negative and statistically significant. The calculated long-run coefficient of technological innovations is negative and statistically significant, suggesting that a 1% increase in technological innovation causes a 0.11% cut in CO2 emissions. The long-run coefficient of forest area is notably negative and significant, which means that expanding forest area by 1% lessens CO2 emissions by 0.56%. The empirical results show that as Uruguay's economy grows, so do its CO2 emissions, but the country may get closer to its goal of carbon neutrality through the growing use of renewable energy, technological innovation, and sustainable forest management. The robustness of the outcomes was verified by utilizing the fully modified least squares (FMOLS) and canonical cointegrating regression (CCR) techniques. In order for Uruguay to reach its goal of carbon neutrality by 2030, this article offers policy ideas centered on a low-carbon economy, promoting renewable energy utilization, financing of technological innovations, and sustainable forest management.Graphical

The ASEAN countries have increasingly become a new economic force in the global economy. Economic growth and development have significantly improved living standards. However, environmental degradation in the region has been significantly deteriorating. This study examines the long-term effects of renewable energy consumption, urbanization and financial development on environmental degradation in ASEAN countries from 1995 to 2020. Various econometric techniques are used, including the fully modified OLS, dynamic OLS, canonical cointegration regression and Ganger’s causality relationship. The empirical results indicate that increased renewable energy consumption and extended urbanization reduce environmental degradation. However, economic growth and financial development lead to increased environmental degradation. Granger’s causality relationship analysis confirms a bidirectional linkage between renewable energy consumption and urbanization, urbanization and financial development, and urbanization and environmental degradation. Financial development and urbanization also have a bidirectional causality relationship with economic growth. Finally, the results confirm a unilateral causality relationship between environmental degradation financial development and urbanization. The governments of the ASEAN countries will need to consider the significant roles of renewable energy usage and urbanization in their policies in achieving sustainable economic growth and development and improving environmental quality.

Global climate change caused by greenhouse gasses (GHGs), particularly carbon dioxide (CO2) emissions, poses incomparable threats to the environment, development, and sustainability. This research investigates the potential of economic growth, renewable energy use, and forested area toward achieving environmental sustainability in Malaysia by reducing CO2 emissions. Time series data from 1990 to 2019 were utilized by applying the Dynamic Ordinary Least Squares (DOLS) method. The empirical findings show that the coefficient of economic growth is positive and significant, indicating a 1% increase in economic growth is related to a 0.78% rise in CO2 emissions. In addition, the coefficient of renewable energy use is negative but not significant, suggesting that increasing renewable energy use by 1% is associated with CO2 emissions reduction by 0.10%. Finally, the coefficient of forested area is negative and significant, implying that increasing forested area by 1% is linked with a 3.86% reduction in CO2 emissions. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and canonical cointegrating regression (CCR). In addition, the pairwise Granger causality test was utilized to capture the causal relationship between the variables. The empirical outcomes reveal that economic growth deteriorates the environmental quality in Malaysia while enhanced renewable energy use and forested area can reduce Malaysia's carbon emissions. This study put forward policy recommendations for a low-carbon economy, promoting renewable energy, and sustainable forest management which could help to achieve environmental sustainability through emission reduction in Malaysia.

The nexus between economic growth, renewable energy use, agricultural land expansion, and carbon emissions: New insights from Peru

Global climate change caused by Greenhouse gases (GHGs), particularly carbon dioxide (CO2) emissions, poses incomparable threats to the environment, development, and sustainability. This research investigates the potential of economic growth, renewable energy use, and technological innovation to achieve environmental sustainability by reducing CO2 emissions in Bangladesh. Time series data from 1980 to 2019 were utilized by applying the autoregressive distributed lag (ARDL) bounds testing approach followed by the Dynamic Ordinary Least Squares (DOLS) method. The DOLS estimate findings show that the long-run coefficient of economic growth is positive and significant with CO2 emissions, indicating a 1% increase in economic growth is related to a 1.3% rise in CO2 emissions. Furthermore, the coefficient of renewable energy use is negative and significant, which indicates that increasing renewable energy use by 1% is associated with CO2 emissions reduction by 0.15% in the long run. In addition, the estimated long-run coefficient of technological innovation is negative but not significant, implying that a 1% increase in technological innovation results in a 0.07% reduction in CO2 emissions. The empirical findings reveal that economic growth increases CO2 emissions in Bangladesh while increased renewable energy use and technological innovation help to achieve environmental sustainability by reducing CO2 emissions. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and canonical cointegrating regression (CCR). In addition, the pairwise Granger causality test is utilized to capture the causal linkage between the variables. This article provides policy recommendations aimed at a low-carbon economy, promoting renewable energy use, and financing technological advancement, to achieve emission reduction and environmental sustainability in Bangladesh.

This study investigates the impact of globalisation, renewable energy consumption, and economic growth on CO2 emissions in 26 European Union (EU) countries, in the period 1990–2020. Second-generation panel unit root tests are applied, the Westerlund cointegration test is used, and a panel of fully modified least squares (FMOLS) and dynamic ordinary least squares (DOLS) techniques are employed to estimate the long-term relationship between variables. The causality relationship among the considered variables is identified using the heterogeneous Dumitrescu–Hurlin causality test. It was found that globalisation and renewable energy consumption contributed to the carbon emissions’ mitigation, while economic growth induced their increase. The results are robust when control variables (i.e., financial development, foreign direct investment, and urbanisation) are added to the model. Foreign direct investment and urbanisation are contributors to carbon emissions’ increase, whereas financial development induces their decrease. The effect of the considered variables on carbon emissions is differentiated by economic development and level of institutional quality. Unidirectional causality relationships were identified from globalisation to carbon emissions and from carbon emissions to foreign direct investment and bidirectional relationships were found between economic growth, renewable energy consumption, financial development, and carbon emissions. The policy implications of the results are also discussed.

We examine the case of Tunisia to empirically assess the impact of financial development, renewable energies, tourism, capital formation, and industrialization on environmental protection from 1988 to 2021. Given the heterogeneity between countries in terms of environmental conditions, energy consumption and production, and infrastructure, the results may be distinct from the previous studies. Using the Autoregressive Distributed Lag (ARDL) model, the findings show that tourism and industrialization increase carbon emissions, whereas financial development, renewable energy, and capital formation lower them. One percent increase in renewable energy helps reduce carbon dioxide emissions by 0.80% in the long run and 0.57% in the short run. The rate of adjustment towards equilibrium was 0.48%. Other methods, including Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR), confirm the accuracy of our results. These findings provide policymakers in Tunisia and other countries with similar contexts with a solid basis for designing programs to improve environmental protection.

This study explores the interplay among economic growth, financial globalization, urbanization, fossil fuel consumption, and renewable energy usage and their combined impact on the load capacity factor in Mexico. This research employs the load capacity factor as a unique measure of ecological health, facilitating a comprehensive ecosystem assessment by sequentially evaluating biocapacity and ecological effects. Using time series data spanning from 1971 to 2018, this study employs the Autoregressive Distributed Lag (ARDL) method to analyze both long-term and short-term dynamics and cointegration. The findings reveal that economic growth, fossil fuel usage, and urbanization reduce Mexico’s load capacity factor, thereby diminishing environmental quality. In contrast, the adoption of renewable energy sources and the influence of financial globalization exhibit positive effects on the load capacity factor over the long and short term. These outcomes remain consistent even when compared with alternative estimation techniques, including dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). As a priority, Mexican policymakers should accelerate the transition to renewable energy sources, encourage sustainable urban development, and foster a more ecologically conscious economic agenda. Furthermore, promoting greener technologies can enhance the load capacity and mitigate environmental degradation. Ultimately, Mexico can establish an environment conducive to expanding sustainable investments by encouraging cross-border investments, enabling global trade in financial services, and cultivating greater integration of capital and financial markets.

Global climate change, exacerbated by greenhouse gas (GHG) emissions, notably carbon dioxide (CO2) emissions, provides huge risks to the environment, development, and sustainability. This study empirically investigated the dynamic impacts of economic growth, fossil fuel energy use, renewable energy use, and agricultural productivity on CO2 emissions in Nepal. Time series data from 1990 to 2019 were utilized by applying the autoregressive distributed lag (ARDL) bounds testing approach followed by the Dynamic Ordinary Least Squares (DOLS) method. The ARDL bounds test revealed evidence of cointegration among the variables. The DOLS findings revealed that an increase in economic growth and fossil fuel energy use by 1% for each variable would increase CO2 emissions by 0.61% and 0.67%, respectively. Conversely, a 1% increase in renewable energy use and agricultural productivity may lead to CO2 emissions reduction by 3.65% and 0.41% in the long run. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and canonical cointegrating regression (CCR). In addition, the pairwise Granger causality test was utilized to capture the causal linkage between the variables. This article put forward policy recommendations aimed at sustainable development by establishing strong regulatory policy instruments to reduce environmental degradation.