The impact of oil prices on CO2 emissions in China: A Wavelet coherence approach

This paper observes the possible co-movements of oil price and CO2 emissions in China by following wavelet coherence and wavelet partial coherence analyses to be able to depict short-run and long-run co-movements at both low and high frequencies. To this end, this research might provide the current literature with the output of potential short run and long run, structural, changes in CO2 emissions upon a shock (a change) in oil prices in China together with the control variables of World oil prices, fossil energy consumption, and renewables consumption, and, urban population in China. Therefore, this research aims at determining wavelet coherencies between the variables and phase differences to exhibit the leading variable in potential co-movements. By following the time domain and frequency domain analyses of this research, one may claim that the oil prices in China has considerable negative impact on CO2 emissions at high frequencies for the periods 1960-2014 and 1971-2014 in China. Besides, one may underline as well other important output of the research exploring that the urban population and CO2 emissions have positive associations, move together for the period 1960-2014 in China. Eventually, this paper might suggest that authorities follow demand side management policies considering energy demand behavior at both shorter cycles and longer cycles to diminish the CO2 emissions in China

A revisited renewable consumption-growth nexus: A continuous wavelet approach through disaggregated data

WOS: 000463342600001In this research, we aim at exploring the influence of renewables on industrial production (Ip) in the US by following continuous wavelet coherence and partial continuous wavelet coherence analyses. To this end, we observed the co-movements between, biofuels and Ip, solar and Ip, wind and Ip, geothermal and Ip, wood and Ip, and, waste and Ip in the US for the monthly period from January 1989 to November 2016. The primary motivations behind this research are twofold. Firstly, it attempts to reach the co-movements, if exists, between renewables' consumption and industrial production by following time domain and frequency domain analyses. Secondly, it aims at observing the potential co-movements between renewable energy sources (geothermal, solar, wind, biofuels, wood, and, waste) and Ip by adding some control variables (fossil fuels, total biomass etc.) into the wavelet models to understand clearly the responses of the industrial production to the impulses in renewables in both short term and long term periods. The paper hence eventually reveals significant effects of geothermal, wind, solar, biofuels, wood, and, waste on US industrial production in short term cycles and long term cycles. Thereby, following this paper's results of continuous wavelet analyses which depict the impact of renewables on US economy at 1-3-year frequency and 3-8-year frequency for the time period from January 1989 to November 2016, one might provide policy makers with relevant current and future efficient renewables' energy policy for the US and other countries which have similar structures with the US