Uncertainty and heterogeneity in factor models forecasting

In this paper, we exploit the heterogeneity in the forecasts obtained by estimating different factor models to measure forecast uncertainty. Our approach is simple and intuitive. It consists first in selecting all the models that outperform some benchmark model, and then in constructing an empirical distribution of the forecasts produced by them. We interpret this distribution as a measure of uncertainty. We illustrate our methodology by means of a forecasting exercise using a large database of Italian data from 1982 to 2009.