A country's financing system is essential in addressing sustainable development requirements. National sources and international financial flows contribute to economic growth and environmental quality in many ways, and their impact can be critical. This paper applied panel data analysis using a comparative approach of Pooled Mean Group Auto Regressive Distribute Lags (PMG-ARDL) and Cross Sectionally ARDL (CS-ARDL) to estimate the effects of FDI, renewable energy, and remittance on environmental quality in the top remittance-receiving countries, during 2000-2021. The study emphasized the positive relationship between FDI and carbon emissions. Moreover, renewable energy and remittances revealed an inverted U-shaped relationship with carbon emissions. In the case of developing countries from the panel, remittance improves environmental quality after reaching the threshold. Moreover, for some of the developing countries included in the panel, we found that they do not achieve the desired carbon mitigation effect in their early stages of renewable energy implementation. However, renewable energy becomes a key factor for tackling environmental pollution after a certain threshold. The mixed results determined diverse policy recommendations for various stakeholders.
This study aims to investigate the relationship between renewable energy and ecological footprint during the period of 1994-2018 from selected developing countries in Europe (Czechia, Croatia, Poland, Romania, Romania, and Turkey). In this context, the ecological footprint (EF), which has recently been the most widely used environmental indicator in the literature and is known as the most comprehensive because it includes many environmental factors, has been determined as the dependent variable. As independent variables, renewable energy consumption (REC), energy-related tax revenue (ETR), and energy productivity (EP) are included in the model. GDP and development of environment-related technologies (DET), which affect the ecological footprint in the model, are determined as control variables. As a result of the panel data analysis, according to the Durbin-Hausman cointegration test result, a long-term relationship between the variables was determined. According to the CCE estimator analysis, it can be said that there is a positive relationship between ETR and GDP variables and EF. For the AMG estimator analysis, it can be said that there is a positive relationship between GDP and EP variables and EF. Finally, according to the results of the Konya Causality test, a unidirectional causality relationship is detected from environmental technologies to the ecological footprint in Turkey, and a unidirectional causality relationship from the ecological footprint to GDP in Czechia, Romania, and Turkey. Furthermore, no causality relationship is detected between other variables. Based on the results, several policy implications are suggested.