Assessing the impact of COVID-19 on global fossil fuel consumption and CO₂ emissions - L. Vanessa Smith; Nori Tarui; Takashi Yamagatax (Osaka University, Institute of Social and Economic Research (ISER), 2020)
The shock to the global economy from COVID-19 is predicted to be faster and more severe than the 2008 global financial crisis and even the Great Depression. We assess its impact on global fossil fuel consumption and CO2 emissions over a two-year horizon. For this purpose we employ a global vector autoregressive (GVAR) model, which captures complex spatial-temporal interdependencies across countries due to the spread of the virus and associated international propagation of economic impact. The model makes use of a unique quarterly data set of coal, natural gas, and oil consumption, output and exchange rates, including global fossil fuel prices for 32 major CO2 emitting countries. We produce forecasts of coal, natural gas and oil consumption, conditional on GDP growth scenarios based on alternative IMF World Economic Outlook forecasts that were made before and after the outbreak. We also simulate the effect of a relative price change in fossil fuels, due to carbon pricing in all countries in the sample, on consumption and output. Our results show that fossil fuel consumption and CO2 emissions are expected to return to their pre-crisis levels, and even exceed them, within the two-year horizon despite the large reductions in the first quarter following the outbreak. Our forecasts anticipate more robust growth for emerging than for advanced economies. Recovery to the pre-crisis levels is expected even if another wave of pandemic occurs within a year. The results from our counterfactual carbon pricing scenario show that an increase in coal prices is expected to have a smaller impact on GDP than on fossil fuel consumption. Thus, the COVID-19 pandemic would not provide countries with a strong reason to delay climate change mitigation efforts.
Keywords: C33; O50; P18; Q41; Q43; Q47; 330; COVID-19; CO2 emissions; fuel consumption; Global VAR (GVAR); conditional forecasts