On the transmission of oil supply and demand shocks to CO2 emissions in the US by considering uncertainty: A time-varying perspective

In an economic context increasingly governed by structural changes, crises, and uncertainty, our understanding of the transmission of oil price shocks to real economic activity and the resulting effects on CO2 emissions is found to evolve over time. Our understanding is also found to evolve when considering the sources of oil price fluctuations as emanating from the supply or demand side. So far, there is still few answers provided by the literature on how economic and policy uncertainty influences the response of CO2 emissions to different sources of oil price shocks. This paper tries to investigate this ‘missing link’ by estimating the time-varying transmission of oil supply and demand shocks to CO2 emissions in the US, while considering the simultaneous effect of uncertainty. Using monthly data covering a period including the Covid-19 health crisis, a two-step estimation procedure is adopted: before constructing a time-varying parameter structural vector autoregression model with stochastic volatility (TVP-SVAR-SV), a structural VAR model (SVAR) is implemented to decompose oil price shocks in four structural shocks namely: oil supply shock, aggregate demand shock, domestic demand shock and oil-specific demand shock. Estimation results and robustness tests show that the level of uncertainty shapes the transmission of oil price shocks to CO2 emissions. Oil supply and oil-specific demand shocks impact negatively CO2 emissions mostly when uncertainty is low. A high uncertainty level leads to a perverse positive impact of aggregate demand shocks on CO2 emissions. Interestingly, CO2 emissions are found to increase during low levels of uncertainty in response to domestic demand driven oil price shocks. This finding may be due to the expansive economic policies enforced to decrease uncertainty and increase consumption in reaction to domestic demand shocks. These results imply that workable solutions targeting an optimal level of CO2 emissions should not only consider different sources of oil price fluctuations but also the level of uncertainty. Discarding the level of uncertainty may lead to a sub-optimal calibration of the regulatory and fiscal measures aiming to protect the environment against different sources of oil price shocks and to adapt these measures to the time horizon of carbon emissions responses.