Addressing COVID-19 Outliers in BVARs with Stochastic Volatility

130 Pages Posted: 31 Mar 2021

See all articles by Andrea Carriero

Andrea Carriero

Queen Mary, University of London

Todd E. Clark

Federal Reserve Bank of Cleveland

Massimiliano Giuseppe Marcellino

Bocconi University - Department of Economics; Centre for Economic Policy Research (CEPR)

Elmar Mertens

Deutsche Bundesbank

Multiple version iconThere are 2 versions of this paper

Date Written: March 1, 2021

Abstract

Incoming data in 2020 posed sizable challenges for the use of VARs in economic analysis: Enormous movements in a number of series have had strong effects on parameters and forecasts constructed with standard VAR methods. We propose the use of VAR models with time-varying volatility that include a treatment of the COVID extremes as outlier observations. Typical VARs with time-varying volatility assume changes in uncertainty to be highly persistent. Instead, we adopt an outlier-adjusted stochastic volatility (SV) model for VAR residuals that combines transitory and persistent changes in volatility. In addition, we consider the treatment of outliers as missing data. Evaluating forecast performance over the last few decades in quasi-real time, we find that the outlier-augmented SV scheme does at least as well as a conventional SV model, while both out-perform standard homoskedastic VARs. Point forecasts made in 2020 from heteroskedastic VARs are much less sensitive to outliers in the data, and the outlier-adjusted SV model generates more reasonable gauges of forecast uncertainty than a standard SV model. At least pre-COVID, a close alternative to the outlier-adjusted model is an SV model with t-distributed shocks. Treating outliers as missing data also generates better-behaved forecasts than the conventional SV model. However, since uncertainty about the incidence of outliers is ignored in that approach, it leads to strikingly tight predictive densities.

JEL Classification: C53, E17, E37, F47

Suggested Citation

Carriero, Andrea and Clark, Todd E. and Marcellino, Massimiliano and Mertens, Elmar, Addressing COVID-19 Outliers in BVARs with Stochastic Volatility (March 1, 2021). CEPR Discussion Paper No. DP15964, Available at SSRN: https://ssrn.com/abstract=3816849

Andrea Carriero (Contact Author)

Queen Mary, University of London ( email )

Mile End Road
London, London E1 4NS
United Kingdom

Todd E. Clark

Federal Reserve Bank of Cleveland ( email )

P.O. Box 6387
Cleveland, OH 44101
United States
216-579-2015 (Phone)

Massimiliano Marcellino

Bocconi University - Department of Economics ( email )

Via Gobbi 5
Milan, 20136
Italy

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

Elmar Mertens

Deutsche Bundesbank ( email )

Wilhelm-Epstein-Str. 14
Frankfurt/Main, 60431
Germany

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