DP15965 Measuring Uncertainty and Its Effects in the COVID-19 Era
|Author(s):||Andrea Carriero, Todd Clark, Massimiliano Marcellino, Elmar Mertens|
|Publication Date:||March 2021|
|Keyword(s):||Bayesian VARs, Pandemics, stochastic volatility|
|JEL(s):||C11, C55, E32, E44|
|Programme Areas:||Monetary Economics and Fluctuations|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=15965|
We measure the effects of the COVID-19 outbreak on uncertainty, and we assess the consequences of the uncertainty for key economic variables. We use a large, heteroskedastic vector autoregression (VAR) in which the error volatilities share two common factors, interpreted as macro and financial uncertainty. Macro and financial uncertainty are allowed to contemporaneously affect the macroeconomy and financial conditions, with changes in the common component of the volatilities providing contemporaneous identifying information on uncertainty. We also consider an extended version of the model that accommodates outliers in volatility, to reduce the influence of extreme observations from the COVID period. Our estimates yield very large increases in macroeconomic and financial uncertainty since the onset of the COVID-19 period. These increases have contributed to the downturn in economic and financial conditions, but the contributions of uncertainty are small compared to the overall movements in many macroeconomic and financial indicators. That implies that the downturn is driven more by other dimensions of the COVID crisis than shocks to aggregate uncertainty (as measured by our method).