How to Estimate a VAR after March 2020

Giorgio Primiceri and Michele Lenza

No 15245, CEPR Discussion Papers from C.E.P.R. Discussion Papers

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; Volatility; Outliers; Density forecasts (search for similar items in EconPapers)
JEL-codes: C11 C32 E32 E37 (search for similar items in EconPapers)
Date: 2020-09
New Economics Papers: this item is included in nep-mac
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Citations: View citations in EconPapers (157)

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Related works:
Working Paper: How to estimate a VAR after March 2020 (2020)
Working Paper: How to Estimate a VAR after March 2020 (2020)
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