This paper uses the wavelet technique to investigate the impact of energy consumption (renewable and non-renewable), and economic growth on carbon dioxide (CO2) emission in the United States. Monthly data from the year of 1981 (January) to 2018 (December) are used for this investigation. The techniques adopted on the data includes wavelet covariance, wavelet correlation, continuous wavelet power spectrum and wavelet coherence spectrum. The results indicate that (i) non-renewable energy consumption has a positive influence on CO2 emissions in the short, medium and long run; (ii) renewable energy consumption has a positive impact on CO2 emissions over some periods in the short run; (iii) economic growth has a positive influence on CO2 in the medium and long run. Based on these findings, some policy recommendations are summarized in our paper, and all these findings can provide some implications for other similar countries, e.g., China.

CICTP