  Time averaging has been the traditional approach to handle mixed sampling
frequencies. However, it ignores information possibly embedded in high
frequency. Mixed data sampling (MIDAS) regression models provide a concise way
to utilize the additional information in high-frequency variables. In this
paper, we propose a specification test to choose between time averaging and
MIDAS models, based on a Durbin-Wu-Hausman test. In particular, a set of
instrumental variables is proposed and theoretically validated when the
frequency ratio is large. As a result, our method tends to be more powerful
than existing methods, as reconfirmed through the simulations.
