  The RAS method is an iterative procedure that bi-proportionally scales an
input-output table to be consistent with given row and column sums. It can be
used to disaggregate an annual national table to more detailed tables, such as
regional, quarterly, and domestic/imported tables. However, the regular
two-dimensional RAS method does not ensure the consistency of the disaggregated
tables with the original table. For this problem, we use the multidimensional
RAS method, which besides input and output totals, also ensures regional,
quarterly, and domestic/imported totals. Our analysis of Czech industries shows
that the multidimensional RAS method increases the accuracy of table estimation
as well as the accuracy of the Leontief inverse, the quarterly value added, and
(to some degree) the regional Isard's model. We also rigorously demonstrate its
relation to the cross-entropy model.
