Gender and the Factors Affecting Child Labor in Iran: an Application of IV-TOBIT Model

Abstract

In this paper we first intend to examine the probability of falling into the realm of child labor by using conditional probability theorem. Furthermore, we will compare the extent of each factor's effect on boys and girls using a TOBIT regression model. Finally we will analyze aspects of Iran's labor market to assess the future ahead of the children who work at present. As the results will show, the probability of not attending school conditional on being male is 0.081, whereas the same probability conditional on being female is 0.12. More probability scores are estimated in the paper. Moreover, the results from the TOBIT regression shows that in general boys are more affected than the girls by the same factors. Also, based on the macro statistics published by Iran's Statistical Center, the graduation of numerous people from graduate schools combined with the low and slow rate of economic growth makes it quite difficult to find a decent work in the country. As a result, the skilled labor force will be content with accepting low wage jobs which are more suitable for the unskilled workers. Therefore, those who left school earlier in their lives will face several problems in the future.