Detalhes bibliográficos
| Ano de defesa: |
2018 |
| Autor(a) principal: |
Cunha, Danúbia Rodrigues da
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| Orientador(a): |
Monsueto, Sandro Eduardo
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| Banca de defesa: |
Monsueto, Sandro Eduardo,
Casari, Priscila,
Diaz, Mário Ernesto Piscoya |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
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| Programa de Pós-Graduação: |
Programa de Pós-graduação em Economia (FACE)
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| Departamento: |
Faculdade de Administração, Ciências Contábeis e Ciências Econômicas - FACE (RG)
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/8269
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Resumo: |
In this work, bivariate regression models based on the bivariate normal, t and Birnbaum-Saunders distributions are used to analyze labor market data. In special, the objective is to model the dependent variable of the Mincerian earnings equation separately, namely, the variable hourly earnings (which is obtained by dividing gross monthly earnings by hours worked) is modeled in two parts, earnings and hours worked. The bivariate regression models are used to model these two parts in order to try to capture the correlation between them and the different effects, that is, remuneration or premium for labor effort, and the labor supply or the time that the worker offers to the market. In order to accomplish this, data from the Brazilian National Household Sample Survey (PNAD) for the years 2013, 2014 and 2015 are used. The parameters of the models are estimated using the maximum likelihood method. The results show that the bivariate regression model based on the bivariate t distribution has the best fit for the data, and that the presence of correlation between earnings and hours worked indicates that the bivariate model is more adequate than the univariate model. |
