How to Estimate a VAR after March 2020
20 Pages Posted: 26 Aug 2020
Date Written: August, 2020
This paper illustrates how to handle a sequence of extreme observations—such as those recorded during the COVID-19 pandemic—when estimating a Vector Autoregression, which is the most popular time-series model in macroeconomics. Our results show that the ad-hoc strategy of dropping these observations may be acceptable for the purpose of parameter estimation. However, disregarding these recent data is inappropriate for forecasting the future evolution of the economy, because it vastly underestimates uncertainty.
Keywords: COVID-19, density forecasts, outliers, volatility
JEL Classification: C32, E32, E37, C11
Suggested Citation: Suggested Citation