Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior

Detalhes bibliográficos
Autor(a) principal: Moreno, Mateus Hurbano Bomfim
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
Texto Completo: http://tede.unioeste.br/handle/tede/5626
Resumo: 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.
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spelling Pontili, Rosangela Mariahttp://lattes.cnpq.br/2484451282332686Gabriel, Flávio Braga de Almeidahttp://lattes.cnpq.br/9084287979694927Ferro, Andrea Rodrigueshttp://lattes.cnpq.br/3432809140419477Pontili, Rosangela Mariahttp://lattes.cnpq.br/2484451282332686http://lattes.cnpq.br/4657048589906610Moreno, Mateus Hurbano Bomfim2021-11-04T18:01:49Z2021-02-22MORENO, Mateus Hurbano Bomfim. Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior. 2021. 125 f. Dissertação (Mestrado em Economia) - Universidade Estadual do Oeste do Paraná, Toledo, 2021.http://tede.unioeste.br/handle/tede/5626With 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.Tendo a formação educacional como um dos principais atributos do capital humano dos indivíduos, esta dissertação utiliza os microdados da Pesquisa de Orçamentos Familiares de 2017-2018 para analisar os determinantes do investimento em educação para famílias brasileiras que tinham filhos estudantes e não estudantes, mas aptos a cursar a educação básica ou o ensino superior. Especificamente, buscou-se identificar: os determinantes dos investimentos em capital humano levando-se em conta as características socioeconômicas individuais e familiares, assim como, as diferenças regionais; a influência dessas variáveis tanto na decisão pelo investimento, quanto na decisão do volume a ser investido em capital humano; e a relevância da condição do filho com relação à família e com relação à educação formal, bem como a influência de variáveis de interação entre características familiares e a renda familiar. Utilizou-se dois bancos de dados, diferenciando-os entre níveis de ensino, nos quais restringiu-se a amostra aos filhos que foram identificados como alunos ou ex-alunos: i) da educação básica (com idade até 21 anos) e ii) do ensino superior (com idade entre 17 e 30 anos). Utilizou-se como método o modelo de duas etapas de Heckman, para o qual, na primeira etapa estimou-se o modelo de escolha binária probit observando a decisão das famílias de incorrer em gastos educacionais, ou não. Nesta etapa os principais resultados encontrados para os dois bancos de dados foram que as variáveis com maior influência sobre a decisão das famílias pelo investimento em educação corresponderam às variáveis contínuas (efeito positivo) de proporção de crianças e adolescentes na família e a proxy da renda familiar; bem como, às variáveis dummies que identificam a frequência na rede pública de ensino e a não frequência em instituições de ensino (efeito negativo). A segunda etapa diz respeito a estimativa de uma equação de regressão linear múltipla para o volume de despesas familiares mensais per capita com a educação dos filhos. Neste caso, os principais determinantes foram novamente as variáveis destacadas na etapa anterior, além daquelas que identificam a condição do filho e de diferenças regionais (efeitos positivos). Ainda, no modelo de regressão linear múltipla incorporou-se o vetor de interações entre variáveis de características familiares e monetárias. Presente apenas no banco da educação básica, a variável “interação entre o arranjo familiar monoparental feminino e a renda familiar” demonstrou que em famílias chefiadas por mães solo, a influência da renda familiar no volume de despesas com educação dos filhos é maior. A interação entre a cor do chefe da família e a renda familiar sugeriu que, em famílias chefiadas por pessoas brancas, o impacto da renda familiar sobre os gastos com educação é maior. Por fim, sugere-se que haja políticas públicas que promovam a equidade e qualidade da educação, levando-se em consideração: atividades extracurriculares; a Renda Básica; as diferenças de situação domiciliar entre áreas rurais e urbanas; diferenças regionais, especialmente com relação à região norte; e desigualdades raciais e de sexo presentes no mercado de trabalho.Submitted by Marilene Donadel (marilene.donadel@unioeste.br) on 2021-11-04T18:01:49Z No. of bitstreams: 1 Mateus_Moreno_2021.pdf: 1629821 bytes, checksum: 2c198e4292afc583cee6d31837159db8 (MD5)Made available in DSpace on 2021-11-04T18:01:49Z (GMT). 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dc.title.por.fl_str_mv Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior
dc.title.alternative.eng.fl_str_mv Determinants of human capital investment: estimates for families with children students and non-students of basic education and higher education
title Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior
spellingShingle 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
Despesa familiar com educação
Modelo de duas etapas de Heckman
Pesquisa de orçamentos familiares
Human capital
Heckman's two-step model
Household expenditure on education
CIENCIAS SOCIAIS APLICADAS::ECONOMIA
title_short Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior
title_full Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior
title_fullStr Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior
title_full_unstemmed Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior
title_sort Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior
author Moreno, Mateus Hurbano Bomfim
author_facet Moreno, Mateus Hurbano Bomfim
author_role author
dc.contributor.advisor1.fl_str_mv Pontili, Rosangela Maria
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/2484451282332686
dc.contributor.referee1.fl_str_mv Gabriel, Flávio Braga de Almeida
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/9084287979694927
dc.contributor.referee2.fl_str_mv Ferro, Andrea Rodrigues
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/3432809140419477
dc.contributor.referee3.fl_str_mv Pontili, Rosangela Maria
dc.contributor.referee3Lattes.fl_str_mv http://lattes.cnpq.br/2484451282332686
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/4657048589906610
dc.contributor.author.fl_str_mv Moreno, Mateus Hurbano Bomfim
contributor_str_mv Pontili, Rosangela Maria
Gabriel, Flávio Braga de Almeida
Ferro, Andrea Rodrigues
Pontili, Rosangela Maria
dc.subject.por.fl_str_mv Despesa familiar com educação
Modelo de duas etapas de Heckman
Pesquisa de orçamentos familiares
topic Despesa familiar com educação
Modelo de duas etapas de Heckman
Pesquisa de orçamentos familiares
Human capital
Heckman's two-step model
Household expenditure on education
CIENCIAS SOCIAIS APLICADAS::ECONOMIA
dc.subject.eng.fl_str_mv Human capital
Heckman's two-step model
Household expenditure on education
dc.subject.cnpq.fl_str_mv CIENCIAS SOCIAIS APLICADAS::ECONOMIA
description 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.
publishDate 2021
dc.date.accessioned.fl_str_mv 2021-11-04T18:01:49Z
dc.date.issued.fl_str_mv 2021-02-22
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dc.identifier.citation.fl_str_mv MORENO, Mateus Hurbano Bomfim. Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior. 2021. 125 f. Dissertação (Mestrado em Economia) - Universidade Estadual do Oeste do Paraná, Toledo, 2021.
dc.identifier.uri.fl_str_mv http://tede.unioeste.br/handle/tede/5626
identifier_str_mv MORENO, Mateus Hurbano Bomfim. Determinantes do investimento em capital humano: estimativas para famílias com filhos estudantes e não estudantes da educação básica e no ensino superior. 2021. 125 f. Dissertação (Mestrado em Economia) - Universidade Estadual do Oeste do Paraná, Toledo, 2021.
url http://tede.unioeste.br/handle/tede/5626
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language por
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Toledo
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