Comprehending the determinants of renewable energy (RE) deployment has preoccupied the energy literature as well as policymakers internationally due to countries' overall shift away from fossil fuels in the energy mix. As stated in the literature, empirical studies that analyze the determinants of RE deployment use a number of different indicators for RE. The effect of an ambiguous choice of the proxy might produce various outcomes and thus create inconsistencies in the policy recommendations. This study aims at filling this gap in the literature comparing and contrasting not only the use of RE indicators but also, for robustness purposes, using indicators at aggregate and per capita forms for a global sample, developed countries, and developing countries. For the empirical purpose, this study employs two econometric techniques: the pooled ordinary least squares with robust SEs and the augmented mean group estimator, which account for cross-sectional dependence in the dataset. The results show that a 1% increase in gross domestic product (GDP) or GDP per capita leads to an increase in RE between 0.05% and 1.01% and a 1% increase in energy price causes an increase in RE between 0.07% and 0.99% with respect to various proxies, implying that the magnitudes of impacts of income and oil price are quite smaller when RE is proxied with RE consumption than when it is proxied with RE production. In addition, their impacts dramatically change across the choice between the share of RE and the levels of RE. More interestingly, not only the size of the effect of carbon emissions but also its direction changes across indicators. Overall, the choice of RE indicator is of great importance in putting forward reliable and consistent policy suggestions.