Estimation of Technological Coefficients Of Input-Output Table by Using the Group Decision Making Models (In Line With the Analytic Hierarchy)

Decision makers and persons, in charge of ascertaining economic activities of each sector, who hold top position for marking for policies need to employ fully effective methods in order to make decision about priority cases of different sectors in comparison with each other as well as being able to allocate resources in a more proper way. These effective methods should be, processed and analyzed without taking too long or incurring high costs. The input-output model in economics is one of the tools being employed for economic planning and analysis of inter – industries relations . This model is prepared and updated with prevailing methods, such as RAS and its adjusted version. One has to dedicate long time work (months) and allocate high costs (billion of Rials), as well as a need for availability of precise data and statistic of the existing conditions (activities) at the State’s different economic sectors. It should be noted that this process usually is employed in less developed countries like Iran, within long intervals. This article intends to estimate technological coefficients of the input-output table in Iran for the first time by improvising a new method with the help of an improved analytic hierarchy process and group decision making (GDM). This particular method may well show itself to be quite effective when no clear cut statistic data of the activities of the State’s economy are available, also when we are facing time limit, resources inadequacy stringency while it is simultaneously felt that we must make use of technological coefficients in planning. Ten, estimated technological coefficients for the particular period has been worked out by employing RAS customary method, compared with estimated coefficients suggested by this piece of research work (As a modern model and incurring high time and costs of the prevailing methods) through making use of non-parametric statistical tests. The comparison has proved that the obtained results clearly shoe no meaningful difference between these two compared coefficients. Thus, the obtained results are very promising and it is hoped that they may come handy whenever the relevant experts have in mind to use an effective method.