- Rotation in the dynamic factor modeling of multivariate stationary time series.
- Volume | Issue number
- 66 | 1
- Pages (from-to)
- Document type
- Faculty of Social and Behavioural Sciences (FMG)
- Psychology Research Institute (PsyRes)
A special rotation procedure is proposed for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average. This is accomplished by minimizing a so-called state-space criterion that penalizes deviations of the rotated solution from a generalized state-space model with only instantaneous factor loadings. Alternative criteria are discussed in the closing section. The results of an empirical application are presented in some detail.
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