Measuring carbon emission sensitivity to economic shocks: a panel structural vector autoregression 1870-2016.

The study of the link between production, measured in gross domestic product and CO2 emissions, is a topic under intense research. Carbon emissions are moving together with economic shocks (high synchronicity), particularly at troughs and peaks of a business cycle. This research investigates the influence of economic shocks to carbon emissions. Previous studies do not provide a direct empirical evidence on the impact of economic shocks to carbon emissions that are available. We employ structural vector autoregression to explore the impact of economic shocks on carbon emissions in 20 advanced economies from 1870 to 2016. Our empirical results prove a strong, statistically significant connection between emissions and output with a coefficient of elasticity > 1. We identify a strong empirical link using panel structural vector autoregression between carbon emissions and real GDP growth per capita. Up to 40% of the fluctuations in CO2 emissions is explained by combined economic factors (output, population, oil prices, stock exchange). The findings further indicate that carbon emission is determined by energy policy (energy intensity, carbon intensity, relative costs of renewable energy). Our findings contribute to energy policy management, energy, and business cycle research to inspire novel research on energy cycles.