A MIDAS (mixed-data sampling) regression is a direct forecasting tool that can relate future low-frequency data with current and lagged high-frequency indicators and yield different forecasting models for each forecast horizon. It can flexibly deal with data sampled at different frequencies and provide a direct forecast of the low-frequency variable. It incorporates each individual high-frequency data in the regression, which solves the problems of losing potentially useful information and including mis-specification.