Development of a methodology for calibrating inoperability input-output models

Project Code

NP 2013-04


De La Salle University






PHP 244,000.00

Names of Grantees

Raymund Tan, PhD

Executive Summary

The technical coefficient matrices in input-output (IO) models are empirical, and therefore inherently historical in nature. Numerous methods have been proposed to update these matrices to enable IO models to be more accurate for forecasting applications. This project proposed a fuzzy linear programming approach to updating the technical coefficients of IO tables, focusing specifically on Philippine data. This method determined the updated set of coefficients by finding the smallest deviation from the previous set of technical coefficients necessary to satisfy updated final demand and total output data. Triangular fuzzy numbers were assumed to define the allowable bounds for updating the coefficients, and maximum-minimum aggregation was used to identify the optimal set of updated technical coefficients.