چكيده به لاتين
An enormous population of Iranian youth is drafted for compulsory military service every year. This population is predominantly aged between 18-20 and is highly educated. Indeed, such a population of the labor force as conscripts has a very high opportunity cost for the economy. However, for some reasons, there is not much research to provide us a quantitative assessment of this cost. This study aims to provide a model using Operation Research method, and more precisely Dual Matrices in Linear Programming to give us a quantitative concept of the opportunity cost of the draftee human resource for the I.R. Iran. The data of the study is based on 2015 statistics. The statistical population of the study is 400,000 conscripts. The focus of this study is to extract the model by classification of academic degrees and subdivisions of the industry sorted in ISIC. Using the few statistics of 2015, the model is solved. According to the research findings, the opportunity cost of the conscription manpower is 46.70 percent of the Value Added of the industry that year. This is equal to the economic cost our country incurs by using this population as military service duty men, or in other words, it is the amount of the opportunities lost. The sensitivity analysis method was used to test the model behavior with economic logic. The research scenarios in this section include the effect of increasing the rate of return on education per year in the country, the effect of increasing per capita productivity in industry, the effect of increasing the wage floor, and the effect of the entry of women into public service on the opportunity cost of the economy. According to the results of the scenarios, it seems that the strongest factor in determining the present opportunity cost situation in the Iranian economy is the population. Labor productivity, wages, and education levels are the next contributing factors to the opportunity cost of the population. Also, an estimation of the opportunity cost of the draftee population for 2018 was obtained through a scenario. In the end, policy requirements and recommendations were discussed.
