This technical report aims to present a generalised framework for assessing the predictive
content of ONS real time indicators in both dimensions: (i) individual predictors (i.e.
variable-by-variable), and (ii) using machine learning techniques to build variable selection
models. The evaluation is done on a nowcasting basis (h = 0). Simple correlation and
predictive power scores are included as well as best subset selection, penalised
regressions, random forests and principal components.
