Regression modelMixed-frequency

Unrestricted MIDAS Regression

U-MIDAS (Unrestricted MIDAS) is a regression framework designed to handle mixed-frequency data—when explanatory variables arrive at different sampling frequencies (e.g., monthly GDP mixed with daily stock returns). Introduced by Ghysels and colleagues (2007), it eliminates the restrictive lag-structure polynomial constraints of the original MIDAS approach, allowing fuller use of high-frequency information. This flexibility makes it ideal for nowcasting and real-time economic forecasting.

Apply with EconMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Foroni, C., Ghysels, E., & Marcellino, M. (2015). Mixed-frequency vector autoregressive models. International Journal of Forecasting, 31(4), 1051-1070. DOI: 10.1016/j.ijforecast.2014.08.009
  2. Ghysels, E., Santa-Clara, P., & Valkanov, R. (2007). There is a risk-return trade-off after all. Journal of Financial Economics, 76(3), 674-704. DOI: 10.1016/j.jfineco.2004.06.003

Related methods

Referenced by

ScholarGateU-MIDAS (Unrestricted MIDAS Regression). Retrieved 2026-06-04 from https://scholargate.app/en/econometrics/u-midas