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Renewable energy attracts attentions by removing the harmful effects of fossil fuels and protecting the environment. The focus of this study is to investigate GDP per capita, carbon dioxide emissions per capita, technological innovation and trade as the determinants of renewable energy production for the selected Latin American countries during the 1991–2014 period. Technological innovation factor is rarely investigated as one of the determinants of renewable energy. The country group includes Argentina, Brazil, Mexico, Colombia, Chile and Guatemala. Empirical results are obtained by applying panel estimation methods. Cointegration relationship among the analyzed variables is confirmed by Pedroni and Westerlund panel cointegration tests. According to the empirical analysis, GDP per capita, technological innovation and trade have positive and statistically significant impact on renewable energy production per capita. On the other hand, it is found that carbon dioxide emissions and renewable energy production are negatively associated. In addition, the elasticity estimates with respect to technological innovation and trade are found as close to each other. The policy implications of the empirical findings are argued as well. [Display omitted] • The drivers of renewable energy generation are analyzed by panel data techniques. • A 1% rise in output is found to increase renewable energy production by 0.26%. • The effects of technological innovation and trade are estimated as very close. • The elasticity estimate with respect to CO2 emission is found as −0.196. [ABSTRACT FROM AUTHOR]

This study investigates the short-term and long-term impacts of economic growth, trade openness and technological progress on renewable energy use in Organization for Economic Co-operation and Development (OECD) countries. Based on a panel data set of 25 OECD countries for 43 years, we used the autoregressive distributed lag (ARDL) approach and the related intermediate estimators, including pooled mean group (PMG), mean group (MG) and dynamic fixed effect (DFE) to achieve the objective. The estimated ARDL model has also been checked for robustness using the two substitute single equation estimators, these being the dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS). Empirical results reveal that economic growth, trade openness and technological progress significantly influence renewable energy use over the long-term in OECD countries. While the long-term nature of dynamics of the variables is found to be similar across 25 OECD countries, their short-term dynamics are found to be mixed in nature. This is attributed to varying levels of trade openness and technological progress in OECD countries. Since this is a pioneer study that investigates the issue, the findings are completely new and they make a significant contribution to renewable energy literature as well as relevant policy development. • Economic growth, trade openness and technological growth drive renewable energy use. • Long-term dynamics of the variables are found homogenous across the OECD countries. • Short-term dynamics vary as to variation in technological growth and trade openness. • An understanding of variable dynamics is vital for increasing renewable energy use. [ABSTRACT FROM AUTHOR]