Migrações no Brasil: uma aplicação do modelo gravitacional com dados em painel (2002-2014)

• Ano de defesa: 2017
• Autor(a) principal: Barbosa, William
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Economia; UFSM; Programa de Pós-Graduação em Economia e Desenvolvimento; Centro de Ciências Sociais e Humanas
• Palavras-chave em Português: Migração; Modelo gravitacional; Dados em painel; Migration; Gravity model; Panel data; CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/12336

This paper aims to analyze the relationship between migration flows and the variables considered as factors of pull/push, such as average income in the State of origin and destination of migration, access to water, access to electricity, distribution of income, health, violence, mean years of schooling and level of employment in the period of 2002-2014 to Federation Units (FU). To achieve this goal, it is estimated a gravity model with panel data for migration flows, including a dummy variable for States which share borders. The main results that, if on the one hand, Sao Paulo and Minas Gerais are the main destination States, on the other are the main sources of inter-State migrations in Brazil. As regards econometric results, one of the main findings is that the average income in the destination is indeed a factor that can affect the migration decision of the individual. It is also possible to observe that the coefficients associated with population variables in the source and target, as well as the distance between them, were statistically significant. Were also statistically significant parameters associated with the average yield; the concentration of income; to health; to violence; the dummy to States that share borders; the number of people with access to electricity and the average years of study. It should be noted that, in the present study, the number of people with access to piped water and the percentage of the population employed were not statistically significant.