Forecasts from dynamic factor models potentially benefit from refining the data set by eliminating uninformative series. The
paper proposes to use forecast weights as provided by the factor model itself for this purpose. Monte Carlo simulations and
an empirical application to forecasting euro area, German, and French GDP growth from unbalanced monthly data suggest that
both forecast weights and least angle regressions result in improved forecasts. Overall, forecast weights provide yet more
robust results.
Keywords:KP_Berichte_Analysen
Forschungsbereich:Makroökonomie und öffentliche Finanzen