The determinants of male retirement in urban Brazil
Autor(a) principal: | |
---|---|
Data de Publicação: | 2009 |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Nova Economia (Online) |
Texto Completo: | https://revistas.face.ufmg.br/index.php/novaeconomia/article/view/479 |
Resumo: | I use matched and unmatched PME data to study the determinants of male’s retirement over the past two decades. The PME is a very rich source of data, although not very used. The matched data consists of a series of short panel data constructed by matching individual records across adjacent years of the PME. Some patterns I find are not surprising. For example, probability of being retired increases monotonically with age, and the strong dependence of labor transition on otherindividual characteristics such as education. Some other patterns are more interesting and surprising. The labor force participation rates of older workers in the main metropolitanareas are lower than what is observed in the rest of the country. The main explanation is that workers in the main metropolitan areas had earlier enrollment into the system andthey also have better access to early retirement benefits. I also observed an inverse U-shaped relation between education andretirement. Less and more educated workers have similar retirement patterns during the period studied. Last, I find that more educated workers, and those in the formal sector, have higher retirement probabilities than less educated and those in the informal labor market. |
id |
UFMG-4_59f3120da552ef1b93aebbc4220b5dda |
---|---|
oai_identifier_str |
oai:ojs.pkp.sfu.ca:article/479 |
network_acronym_str |
UFMG-4 |
network_name_str |
Nova Economia (Online) |
repository_id_str |
|
spelling |
The determinants of male retirement in urban BrazilThe determinants of male retirement in urban Brazilretirementlabor forceaposentadoriaparticipação noI use matched and unmatched PME data to study the determinants of male’s retirement over the past two decades. The PME is a very rich source of data, although not very used. The matched data consists of a series of short panel data constructed by matching individual records across adjacent years of the PME. Some patterns I find are not surprising. For example, probability of being retired increases monotonically with age, and the strong dependence of labor transition on otherindividual characteristics such as education. Some other patterns are more interesting and surprising. The labor force participation rates of older workers in the main metropolitanareas are lower than what is observed in the rest of the country. The main explanation is that workers in the main metropolitan areas had earlier enrollment into the system andthey also have better access to early retirement benefits. I also observed an inverse U-shaped relation between education andretirement. Less and more educated workers have similar retirement patterns during the period studied. Last, I find that more educated workers, and those in the formal sector, have higher retirement probabilities than less educated and those in the informal labor market.Eu uso dados longitudinais e de período da Pesquisa Mensal de Emprego (PME) para investigar os determinantes da aposentadoria masculina nas duas últimas décadas. A PME é uma fonte de dados muito rica, porém pouco utilizada. Os dados longitudinais foram construídos pareando informações individuais de anos adjacentes da PME.Eu encontrei alguns padrões de aposentadoria pouco surpreendentes. Por exemplo, a probabilidade de a pessoa ser aposentada aumenta com a idade e háuma grande dependência da transição dos indivíduos para a aposentadoria em características pessoais como a educação. Por outro lado, alguns padrões de aposentadoria são interessantes e surpreendentes. A taxa de participação dos trabalhadores idosos nas áreas metropolitanas é mais baixa do que o observado nas demais regiões do país. A principal explicação é que esses trabalhadores contribuem para o sistema previdenciário há mais tempo e tem fácil acesso aos benefícios por tempo de serviço. Eu também observo uma relação de U invertido entre educação e probabilidade de aposentadoria. Os trabalhadores com mais e menos anos de educação formal têm padrões bastante similares de aposentadoria. Por último, eu mostro que os trabalhadores mais educados e aqueles no setor formal têm maior probabilidade de aposentadoria do que os trabalhadores do setor informal e com menos anos de estudo.Departamento de Ciências Econômicas da UFMG2009-06-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.face.ufmg.br/index.php/novaeconomia/article/view/479Nova Economia; Vol. 17 No. 1 (2007)Nova Economia; v. 17 n. 1 (2007)1980-53810103-6351reponame:Nova Economia (Online)instname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGporhttps://revistas.face.ufmg.br/index.php/novaeconomia/article/view/479/475Queiroz, Bernardo Lanzainfo:eu-repo/semantics/openAccess2020-08-11T04:27:45Zoai:ojs.pkp.sfu.ca:article/479Revistahttps://revistas.face.ufmg.br/index.php/novaeconomiaPUBhttps://revistas.face.ufmg.br/index.php/novaeconomia/oai||ne@face.ufmg.br1980-53810103-6351opendoar:2020-08-11T04:27:45Nova Economia (Online) - Universidade Federal de Minas Gerais (UFMG)false |
dc.title.none.fl_str_mv |
The determinants of male retirement in urban Brazil The determinants of male retirement in urban Brazil |
title |
The determinants of male retirement in urban Brazil |
spellingShingle |
The determinants of male retirement in urban Brazil Queiroz, Bernardo Lanza retirement labor force aposentadoria participação no |
title_short |
The determinants of male retirement in urban Brazil |
title_full |
The determinants of male retirement in urban Brazil |
title_fullStr |
The determinants of male retirement in urban Brazil |
title_full_unstemmed |
The determinants of male retirement in urban Brazil |
title_sort |
The determinants of male retirement in urban Brazil |
author |
Queiroz, Bernardo Lanza |
author_facet |
Queiroz, Bernardo Lanza |
author_role |
author |
dc.contributor.author.fl_str_mv |
Queiroz, Bernardo Lanza |
dc.subject.por.fl_str_mv |
retirement labor force aposentadoria participação no |
topic |
retirement labor force aposentadoria participação no |
description |
I use matched and unmatched PME data to study the determinants of male’s retirement over the past two decades. The PME is a very rich source of data, although not very used. The matched data consists of a series of short panel data constructed by matching individual records across adjacent years of the PME. Some patterns I find are not surprising. For example, probability of being retired increases monotonically with age, and the strong dependence of labor transition on otherindividual characteristics such as education. Some other patterns are more interesting and surprising. The labor force participation rates of older workers in the main metropolitanareas are lower than what is observed in the rest of the country. The main explanation is that workers in the main metropolitan areas had earlier enrollment into the system andthey also have better access to early retirement benefits. I also observed an inverse U-shaped relation between education andretirement. Less and more educated workers have similar retirement patterns during the period studied. Last, I find that more educated workers, and those in the formal sector, have higher retirement probabilities than less educated and those in the informal labor market. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009-06-05 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.face.ufmg.br/index.php/novaeconomia/article/view/479 |
url |
https://revistas.face.ufmg.br/index.php/novaeconomia/article/view/479 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://revistas.face.ufmg.br/index.php/novaeconomia/article/view/479/475 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Departamento de Ciências Econômicas da UFMG |
publisher.none.fl_str_mv |
Departamento de Ciências Econômicas da UFMG |
dc.source.none.fl_str_mv |
Nova Economia; Vol. 17 No. 1 (2007) Nova Economia; v. 17 n. 1 (2007) 1980-5381 0103-6351 reponame:Nova Economia (Online) instname:Universidade Federal de Minas Gerais (UFMG) instacron:UFMG |
instname_str |
Universidade Federal de Minas Gerais (UFMG) |
instacron_str |
UFMG |
institution |
UFMG |
reponame_str |
Nova Economia (Online) |
collection |
Nova Economia (Online) |
repository.name.fl_str_mv |
Nova Economia (Online) - Universidade Federal de Minas Gerais (UFMG) |
repository.mail.fl_str_mv |
||ne@face.ufmg.br |
_version_ |
1799711057370939392 |