Evaluation of the Relative Performance of RAS and Cross-Entropy Techniques for Updating Input-Output Tables of Malaysia

Abstract

The growing interest in applied general equilibrium models for policy analyses increases the demand for up-to-date input-output tables. Constructing survey-based input-output tables for a recent year is costly and time-consuming. These constraints have led to the emergence of non-survey updating techniques. In this paper, the relative performance of two prominent non-survey techniques designed to update input-output tables, the RAS and cross-entropy, is compared. Results show that the cross-entropy technique is superior to the RAS regardless of the size of matrices. For both techniques, our analyses suggest that the accuracy of estimates improves with a high level of sectoral aggregation.