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The RAS method is an iterative procedure that bi-proportionally scales aninput-output table to be consistent with given row and column sums. It can beused to disaggregate an annual national table to more detailed tables, such asregional, quarterly, and domestic/imported tables. However, the regulartwo-dimensional RAS method does not ensure the consistency of the disaggregatedtables with the original table. For this problem, we use the multidimensionalRAS method, which besides input and output totals, also ensures regional,quarterly, and domestic/imported totals. Our analysis of Czech industries showsthat the multidimensional RAS method increases the accuracy of table estimationas 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 itsrelation to the cross-entropy model.

Disaggregating Input--Output Tables by the Multidimensional RAS Method: A Case Study of the Czech Republic