DP15114 Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis
We consider simple methods to improve the growth nowcasts and forecasts obtained
by mixed frequency MIDAS and UMIDAS models with a variety of indicators during the
Covid-19 crisis and recovery period, such as combining forecasts across various specifications
for the same model and/or across different models, extending the model specification
by adding MA terms, enhancing the estimation method by taking a similarity approach,
and adjusting the forecasts to put them back on track by a specific form of intercept correction.
Among all these methods, adjusting the original nowcasts and forecasts by an amount
similar to the nowcast and forecast errors made during the financial crisis and following
recovery seems to produce the best results for the US, notwithstanding the different source
and characteristics of the financial crisis. In particular, the adjusted growth nowcasts for
2020Q1 get closer to the actual value, and the adjusted forecasts based on alternative indicators
become much more similar, all unfortunately indicating a much slower recovery than
without adjustment and very persistent negative effects on trend growth. Similar findings
emerge also for the other G7 countries.