This paper analyzes the causal relationship between renewable energy consumption, oil prices, and economic activity in the United States from July 1989 to July 2016, considering all quantiles of the distribution. Although the concept of Granger-causality is defined for the conditional distribution, the majority of papers have tested Granger-causality using conditional mean regression models in which the causal relations are linear. We apply a Granger-causality in quantiles analysis that evaluates causal relations in each quantile of the distribution. Under this approach, we can discriminate between causality affecting the median and the tails of the conditional distribution. We find evidence of bi-directional causality between changes in renewable energy consumption and economic growth at the lowest tail of the distribution; besides, changes in renewable energy consumption lead economic growth at the highest tail of the distribution. Our results also support unidirectional causality from fluctuations in oil prices to economic growth at the extreme quantiles of the distribution. Finally, we find evidence of lower-tail dependence from changes in oil prices to changes in renewable energy consumption. Our findings call for government policies aimed at developing renewable energy markets, to increase energy efficiency in the U.S. (C) 2018 Elsevier B.V. All rights reserved.