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This study aims to investigate the relationship between trade openness and the use of renewable energy sources and South Asia's economic growth and environmental quality. Since renewable energy offers a more sustainable and environmentally friendly option than fossil fuels, it becomes essential to attaining sustainable development. Using renewable energy has grown in popularity as a global solution to the urgent problems of energy security, climate change, and environmental sustainability. Renewable energy must be used by South Asian nations in order to reduce greenhouse gas emissions, maintain long-term energy security, and promote economic resilience. Incorporating renewable energy could enhance the country's energy situation, lessen dependency on imported fossil fuels, and open up new business prospects. Data on the use of renewable energy is gathered for the variable of renewable energy use. Data regarding GDP is gathered for the gross domestic product variable using current US dollars. The Energy Information Administration is the source of the data regarding the use of renewable energy (EIA). Additionally, the World Development Indicators database (WDI) is where the GDP and trade openness data are gathered. The following nations are represented in the data, which was gathered between 2001 and 2020: Bangladesh, India, Nepal, Sri Lanka, and Pakistan. We investigated the long-term relationship between energy consumption, economic growth, and environmental quality in this analysis using the Panel ARDL approach. The dependent variables in the equation above are the environmental quality and economic growth of the Asian developing nations that were chosen for analysis. According to the study's conclusion, TO, GDP, and RNW have long-term negative effects on the environment since they raise CO2. Conversely, RNW reduces CO2, however the effect is negligible compared to other relevant variables. While the results of the CD test show the presence of CSD, the Pedroni Panel Cointegration Test reveals long-run cointegration of a series. The correlation matrix displays the relationship between the variables. The result showed how strongly, negatively, or positively the factors linked with one another. Additionally, there is a substantial positive correlation between GDP and carbon dioxide, its dependent variable. Additionally, RNW are found to be directly related to one another. Both the TO and GDP have a strong and direct correlation, and there is a positive and significant relationship between GDP and RNW. The other cross-sections are connected to this one. They are interdependent and have an impact on one another. Using South Asia as a focus, this study looks at how trade openness and the use of renewable energy affect environmental quality and economic growth in nations including Bangladesh, India, Nepal, Bhutan, and the Maldives.
This study aims to investigate the relationship between trade openness and the use of renewable energy sources and South Asia's economic growth and environmental quality. Since renewable energy offers a more sustainable and environmentally friendly option than fossil fuels, it becomes essential to attaining sustainable development. Using renewable energy has grown in popularity as a global solution to the urgent problems of energy security, climate change, and environmental sustainability. Renewable energy must be used by South Asian nations in order to reduce greenhouse gas emissions, maintain long-term energy security, and promote economic resilience. Incorporating renewable energy could enhance the country's energy situation, lessen dependency on imported fossil fuels, and open up new business prospects. Data on the use of renewable energy is gathered for the variable of renewable energy use. Data regarding GDP is gathered for the gross domestic product variable using current US dollars. The Energy Information Administration is the source of the data regarding the use of renewable energy (EIA). Additionally, the World Development Indicators database (WDI) is where the GDP and trade openness data are gathered. The following nations are represented in the data, which was gathered between 2001 and 2020: Bangladesh, India, Nepal, Sri Lanka, and Pakistan. We investigated the long-term relationship between energy consumption, economic growth, and environmental quality in this analysis using the Panel ARDL approach. The dependent variables in the equation above are the environmental quality and economic growth of the Asian developing nations that were chosen for analysis. According to the study's conclusion, TO, GDP, and RNW have long-term negative effects on the environment since they raise CO2. Conversely, RNW reduces CO2, however the effect is negligible compared to other relevant variables. While the results of the CD test show the presence of CSD, the Pedroni Panel Cointegration Test reveals long-run cointegration of a series. The correlation matrix displays the relationship between the variables. The result showed how strongly, negatively, or positively the factors linked with one another. Additionally, there is a substantial positive correlation between GDP and carbon dioxide, its dependent variable. Additionally, RNW are found to be directly related to one another. Both the TO and GDP have a strong and direct correlation, and there is a positive and significant relationship between GDP and RNW. The other cross-sections are connected to this one. They are interdependent and have an impact on one another. Using South Asia as a focus, this study looks at how trade openness and the use of renewable energy affect environmental quality and economic growth in nations including Bangladesh, India, Nepal, Bhutan, and the Maldives.
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