Automation and job loss: the Brazilian case

Detalhes bibliográficos
Autor(a) principal: Vaz, Bruno Ottoni Eloy
Data de Publicação: 2022
Outros Autores: Fernandes, Lucas Alexandre Estrela Ferreira, Oliveira, Paulo Rocha e, Santos, Ana Tereza Pires dos, Barreira, Tiago Cabral
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Nova Economia (Online)
Texto Completo: https://revistas.face.ufmg.br/index.php/novaeconomia/article/view/6367
Resumo: Abstract Technological innovations are enabling machines to further replace human labor. In this context, we estimate – based on the Frey and Osborne (2017) study, which uses data from the United States of America (USA) – how many Brazilian jobs may be eliminated in one or two decades due to currently existing technologies. We add to earlier research, that included the Brazilian case, as we consider the entire employment structure - including both formal and informal sectors - in order to estimate the proportion of jobs in the country that may be substituted by machines. Our results indicate that 58.1% of Brazilian jobs may disappear over the next 10 to 20 years due to automation. Moreover, we observe that jobs in the informal sector face higher probabilities of elimination by automation when compared to the formal sector. Keywords: Automation, Technological change, Job Loss, Occupational Selection JEL: E24, J23, J24, O33.
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spelling Automation and job loss: the Brazilian caseAutomação e perda de empregos: o caso brasileiroAbstract Technological innovations are enabling machines to further replace human labor. In this context, we estimate – based on the Frey and Osborne (2017) study, which uses data from the United States of America (USA) – how many Brazilian jobs may be eliminated in one or two decades due to currently existing technologies. We add to earlier research, that included the Brazilian case, as we consider the entire employment structure - including both formal and informal sectors - in order to estimate the proportion of jobs in the country that may be substituted by machines. Our results indicate that 58.1% of Brazilian jobs may disappear over the next 10 to 20 years due to automation. Moreover, we observe that jobs in the informal sector face higher probabilities of elimination by automation when compared to the formal sector. Keywords: Automation, Technological change, Job Loss, Occupational Selection JEL: E24, J23, J24, O33.Resumo Inovações tecnológicas estão ampliando a capacidade da máquina substituir o trabalho humano. Neste cenário, procuramos estimar – tomando como base o estudo de Frey e Osborne (2017), que utiliza dados americanos, e tem sido muito citado – quantos empregos brasileiros podem ser eliminados, em uma ou duas décadas, em virtude de tecnologias já existentes na atualidade. Ajudamos a incrementar as evidências existentes, para o caso brasileiro, dado que consideramos a estrutura do mercado de trabalho como um todo – incluindo os setores formal e informal – quando estimamos a proporção de empregos que podem ser substituídos por máquinas. Nossos resultados indicam que 58,1% dos empregos brasileiros podem desaparecer, nos próximos 10 ou 20 anos, em função da automação. Além disso, observamos que os trabalhadores ocupados no setor informal têm maior chance de ver seus empregos sendo substituídos por máquinas do que aqueles empregados no setor formal. Palavras-chave: Automação, Mudanças Tecnológicas, Perda de Emprego, Escolha Ocupacional Classificação JEL: E24, J23, J24, O33.Departamento de Ciências Econômicas da UFMG2022-05-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://revistas.face.ufmg.br/index.php/novaeconomia/article/view/6367Nova Economia; Vol. 32 No. 1 (2022): Revista Nova Economia; 157-180Nova Economia; v. 32 n. 1 (2022): Revista Nova Economia; 157-1801980-53810103-6351reponame:Nova Economia (Online)instname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGenghttps://revistas.face.ufmg.br/index.php/novaeconomia/article/view/6367/3686Copyright (c) 2022 Bruno Ottoni Eloy Vaz, Lucas Alexandre Estrela Ferreira Fernandes, Paulo Rocha e Oliveira, Ana Tereza Pires dos Santos, Tiago Cabral Barreirahttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessVaz, Bruno Ottoni EloyFernandes, Lucas Alexandre Estrela FerreiraOliveira, Paulo Rocha eSantos, Ana Tereza Pires dosBarreira, Tiago Cabral2022-06-19T15:14:56Zoai:ojs.pkp.sfu.ca:article/6367Revistahttps://revistas.face.ufmg.br/index.php/novaeconomiaPUBhttps://revistas.face.ufmg.br/index.php/novaeconomia/oai||ne@face.ufmg.br1980-53810103-6351opendoar:2022-06-19T15:14:56Nova Economia (Online) - Universidade Federal de Minas Gerais (UFMG)false
dc.title.none.fl_str_mv Automation and job loss: the Brazilian case
Automação e perda de empregos: o caso brasileiro
title Automation and job loss: the Brazilian case
spellingShingle Automation and job loss: the Brazilian case
Vaz, Bruno Ottoni Eloy
title_short Automation and job loss: the Brazilian case
title_full Automation and job loss: the Brazilian case
title_fullStr Automation and job loss: the Brazilian case
title_full_unstemmed Automation and job loss: the Brazilian case
title_sort Automation and job loss: the Brazilian case
author Vaz, Bruno Ottoni Eloy
author_facet Vaz, Bruno Ottoni Eloy
Fernandes, Lucas Alexandre Estrela Ferreira
Oliveira, Paulo Rocha e
Santos, Ana Tereza Pires dos
Barreira, Tiago Cabral
author_role author
author2 Fernandes, Lucas Alexandre Estrela Ferreira
Oliveira, Paulo Rocha e
Santos, Ana Tereza Pires dos
Barreira, Tiago Cabral
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Vaz, Bruno Ottoni Eloy
Fernandes, Lucas Alexandre Estrela Ferreira
Oliveira, Paulo Rocha e
Santos, Ana Tereza Pires dos
Barreira, Tiago Cabral
description Abstract Technological innovations are enabling machines to further replace human labor. In this context, we estimate – based on the Frey and Osborne (2017) study, which uses data from the United States of America (USA) – how many Brazilian jobs may be eliminated in one or two decades due to currently existing technologies. We add to earlier research, that included the Brazilian case, as we consider the entire employment structure - including both formal and informal sectors - in order to estimate the proportion of jobs in the country that may be substituted by machines. Our results indicate that 58.1% of Brazilian jobs may disappear over the next 10 to 20 years due to automation. Moreover, we observe that jobs in the informal sector face higher probabilities of elimination by automation when compared to the formal sector. Keywords: Automation, Technological change, Job Loss, Occupational Selection JEL: E24, J23, J24, O33.
publishDate 2022
dc.date.none.fl_str_mv 2022-05-27
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/6367
url https://revistas.face.ufmg.br/index.php/novaeconomia/article/view/6367
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistas.face.ufmg.br/index.php/novaeconomia/article/view/6367/3686
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
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. 32 No. 1 (2022): Revista Nova Economia; 157-180
Nova Economia; v. 32 n. 1 (2022): Revista Nova Economia; 157-180
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
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