How to Estimate a VAR after March 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.
We thank Domenico Giannone for numerous conversations on the topic, and Todd Clark for comments. The views expressed in this paper are those of the authors and do not necessarily represent those of the European Central Bank or the Eurosystem. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Giorgio E. Primiceri
Non-teaching compensated activities, 2017-2020:
American Economic Journal: Macroeconomics, co-editor,
Federal Reserve Bank of Chicago, consultant
European Central Bank, consultant.