Working Paper: CEPR ID: DP15965
Authors: Massimiliano Marcellino; Andrea Carriero; Todd Clark; Elmar Mertens
Abstract: 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 fromthe 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).
Keywords: Bayesian VARs; Stochastic Volatility; Pandemics
JEL Codes: E32; E44; C11; C55
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| COVID-19 outbreak (H12) | macroeconomic uncertainty (D89) |
| COVID-19 outbreak (H12) | financial uncertainty (G33) |
| macroeconomic uncertainty (D89) | downturn in economic conditions (F44) |
| financial uncertainty (G33) | downturn in financial conditions (E44) |
| COVID-19 (I15) | downturn in economic conditions (F44) |
| COVID-19 (I15) | downturn in financial conditions (E44) |