How to Estimate a VAR after March 2020

20 Pages Posted: 26 Aug 2020

See all articles by Michele Lenza

Michele Lenza

European Central Bank (ECB)

Giorgio E. Primiceri

affiliation not provided to SSRN

Multiple version iconThere are 3 versions of this paper

Date Written: August, 2020

Abstract

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

Lenza, Michele and Primiceri, Giorgio E., How to Estimate a VAR after March 2020 (August, 2020). ECB Working Paper No. 20202461, Available at SSRN: https://ssrn.com/abstract=3681328

Michele Lenza (Contact Author)

European Central Bank (ECB) ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany

Giorgio E. Primiceri

affiliation not provided to SSRN

No Address Available

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