SAM Updating Using Multiobjective Optimization Techniques

In this work we present an adjustment/updating procedure of Social Accounting Matrices (SAM) using multiobjective optimization techniques. The usual setting concentrates the adjustment effort in either the column or row coefficients of the SAM. The normal tendency consists in using the column coefficients because they better reflect the technical coefficients embedded in the SAM. Using the benchmark SAM as the basis, and incorporating the new information available we pose a double-objective optimization problem and apply the method of compromise programming that allow us to work together with column and row coefficients. We present samples of the adjustment procedure where we show and compare the Pareto optimal solutions obtained together with other solutions obtained with different adjustment criteria. We compare the results obtained with the ones obtained with other approaches like RAS and the minimum sum of cross entropy together with other methods proposed by the authors. This comparison allows us to evaluate the differences existing between these different methods and the pure vertical or horizontal adjustment criteria. We believe that the adjustment/updating criteria used does not need to be the same along the different parts of the SAM. We may want to update the input-output matrix included in the SAM concentrating in the vertical/column/technical coefficients. But there may be other parts of the SAM where we think that the use of row coefficients, or together both row and column coefficients, is more appropriate. The method we propose can be also applied to situations where the adjustment criteria is not the same for different parts of the SAM.