Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic / Frank Schorfheide, Dongho Song.

Format:

Book

Author/Creator:

Schorfheide, Frank.

Contributor:

National Bureau of Economic Research.

Song, Dongho.

Series:

Working Paper Series (National Bureau of Economic Research) no. w29535.

NBER working paper series no. w29535

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Other Title:

Real-Time Forecasting with a

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2021.

Summary:

We resuscitated the mixed-frequency vector autoregression (MF-VAR) developed in Schorfheide and Song (2015, JBES) to generate macroeconomic forecasts for the U.S. during the COVID-19 pandemic in real time. The model combines eleven time series observed at two frequencies: quarterly and monthly. We deliberately did not modify the model specification in view of the COVID-19 outbreak, except for the exclusion of crisis observations from the estimation sample. We compare the MF-VAR forecasts to the median forecast from the Survey of Professional Forecasters (SPF). While the MF-VAR performed poorly during 2020:Q2, subsequent forecasts were at par with the SPF forecasts. We show that excluding a few months of extreme observations is a promising way of handling VAR estimation going forward, as an alternative of a sophisticated modeling of outliers.

Notes:

Print version record

December 2021.