Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior - Moreno, Mateus Hurbano Bomfim (2021)
With educational training as one of the main attributes of the human capital requirements, this dissertation uses the microdata from the 2017-2018 Family Budget Survey to analyze the determinants of investment in education for Brazilian families with students and non-students, who can attend basic education or higher education. Specifically, we sought to identify: the determinants of investments in education, taking into account the individual and family socioeconomic characteristics, as well as regional differences; the influence of these variables in the decision of investing and the volume to be invested in education; and the relevance of the child's condition concerning the family and the formal education, as well as the influence of variables of interaction between family characteristics and family income. Two databases were used, differentiated by levels of education, in which the sample was restricted to children who were identified as either student or ex-student: i) of the basic education (aged up to 21 years) and ii) higher education (between 17 and 30 years old). Heckman's two-stage model was used as the method, for which, in the first stage, the probit binary choice model was estimated observing the decision of families to incur educational expenses or not. At this stage, the main results were that the variables with the greatest influence on the families' decision to invest in education corresponded to the continuous variables (positive effect) of the proportion of children and adolescents in the family and one proxy for family income; as well as to the dummy variables that identify a frequency in the public school system and non-frequency in educational institutions (negative effect). The second stage concerns the estimation of a multiple linear regression equation on the volume of monthly family expenses per capita for the education of children. In this case, the main determinants were again the variables highlighted in the previous step, in addition to those that identify the child's condition and regional differences (positive effects). Also, in the multiple linear regression model, the vector of interactions between variables of family and monetary characteristics was incorporated. Present only in the basic education dataset, the variable “interaction between the female single-parent family arrangement and the family income” had shown, that in families headed by single mothers, the influence of family income on the volume of education expenses for children is greater. The interaction between the color of the head of the family and the family income suggested that, in families headed by white people, the impact of family income on education spending is greater. Finally, it is suggested to have public policies to promote equity and quality of education, which should account for: extracurricular activities; basic income; the differences between rural and urban households; regional differences between and inside mesoregions, especially about the northern region; and racial and sex inequalities existent in the labor market.