Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic

New Paper by Frank Schorfheide & Dongho Song

“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.”

Read more here.

Posted by at 6:54 PM

Labels: Forecasting Forum


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