In this paper, we provide a multivariate framework for temporal disaggregation of time series observed at a given frequency into higher frequency time series. The suggested method uses the seemingly unrelated time series equations model and it is estimated by the Kalman filter. The methodology is flexible enough to allow for almost any kind of temporal disaggregation problems of both raw and seasonally adjusted time series. Comparisons with other temporal disaggregation methods proposed in the literature are presented using a wide OECD data set. Copyright 2005 Royal Economic Society
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