Mixed data sampling

From Wikipedia, the free encyclopedia

Mixed data sampling (MIDAS) is an econometric regression or filtering method developed by Ghysels et al. A simple regression example has the regressor appearing at a higher frequency than the regressand:

y_{t}=\beta_{0}+\beta_{1}B(L^{1/m};\theta)x_{t}^{(m)}+\epsilon_{t}^{(m)},\,

where y is the regressand, x is the regressor, m denotes the frequency - for instance if y is yearly x_{t}^{(4)} is quarterly - ε is the disturbance and B(L1 / m;θ) is a lag distribution, for instance the Beta function or the Almon lag.

[edit] External links

This Econometrics-related article is a stub. You can help Wikipedia by expanding it.