In this paper we propose a new extension of Di-Fonzo (1990)’s methodology for multivariate temporal disaggregation. We assume that the errors of the high-frequency series follow a VAR(1) model instead of a white noise process. Additionally, an extensive review of different univariate and multivariate disaggregation methods is presented. Finally, we carry out a multivariate application to obtain Colombia’s monthly national accounts from quarterly data. The results obtained using the proposed methodology are similar to those with Di-Fonzo’s method. However, our resulting series are less volatile.