Mixed Data Sampling (MIDAS) regression is an estimation technique which allows for data sampled at different frequencies to be used in the same regression.

More specifically, the MIDAS methodology (Ghysels, Santa-Clara, and Valkanov, (2002) and Gyhsels, Santa-Clara, and Valkanaov (2006), and Andreou, Ghysels, and Kourtellos (2010)) addresses the situation where the dependent variable in the regression is sampled at a lower frequency than one or more of the regressors. The goal of the MIDAS approach is to incorporate the information in the higher frequency data into the lower frequency regression in a parsimonious, yet flexible fashion.

The following discussion describes EViews’ easy-to-use tools for single equation MIDAS regression estimation. We begin by offering background on the approach. Next, we describe how to estimate a MIDAS regression in EViews. We conclude with examples.