A MIDAS regression involves a dependent variable observed at a low frequency and independent variables observed at a higher frequency. This paper relates a true high frequency data generating process, where also the dependent variable is observed (hypothetically) at the high frequency, with a MIDAS regression. It is shown that a correctly specified MIDAS regression usually includes lagged dependent variables, a substantial number of explanatory variables (observable at the low frequency) and a moving average term. Next, the parameters of the explanatory variables unlikely obey certain convenient patterns, and hence imposing such restrictions in practice is not recommended.

Additional Metadata
Keywords high frequency, low frequency, MIDAS regression
JEL Time-Series Models; Dynamic Quantile Regressions (jel C32)
Persistent URL hdl.handle.net/1765/93331
Series Econometric Institute Research Papers
Franses, Ph.H.B.F. (2016). Yet another look at MIDAS regression (No. EI2016-32). Econometric Institute Research Papers. Retrieved from http://hdl.handle.net/1765/93331