Uma análise espacial dos empregos e das empresas no Brasil
Ano de defesa: | 2018 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Católica de Brasília
|
Programa de Pós-Graduação: |
Programa Stricto Sensu em Economia de Empresas
|
Departamento: |
Escola de Gestão e Negócios
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Resumo em Inglês: | The general objective of this study was to work in a methodology that would allow the development of two parameters to evaluate the concentration of productive sectors by regions and time periods. Specifically, it was sought: a) to verify the agglomeration of jobs and companies by regions, states and sectors in Brazil; and b) introduce two parameters that allow the evaluation of the concentration of productive sectors by region and time period. The years considered to reach the established objectives extend from 1994 to 2015. For the first objective a spatial analysis of agglomerations assisted by graphs was made. In relation to the second objective, we adopted the Locational Quotient (QL) technique, which allows us to identify the concentration of variables analyzed in this study. QL uses three indices in its definition (one to refer to the sector, another the region and the last to the time). Therefore, when fixing the index that refers to the region, the other two indexes defined a sequence of matrices, where each one was defined as Regional Matrix of Locational Quotients. Considering that each matrix has a covariance matrix, it was possible to define the parameters: first, as the norm of eigenvalues (NAV), which contains all the eigenvalues of the covariance matrix associated with it; the second in turn, Percentages Greater than one (PMU), which presents the largest percentages, tending to one, in the regional matrix. Data were obtained from the Integrated Automatic Data Recovery System (SIDRA), from the Brazilian Institute of Geography and Statistics (IBGE). The software used to manipulate the data consisted of Excel, Scilab 6.0 and Siad. Based on the results it was observed that the parameters introduced here synthesize the concentration of the sectors throughout each period for the regions. In this way, it can be concluded that the use of the parameters can be useful in the investigation of the local economic problems, indicating clues that point to the real needs of regional development. |
Link de acesso: | https://bdtd.ucb.br:8443/jspui/handle/tede/2541 |
Resumo: | The general objective of this study was to work in a methodology that would allow the development of two parameters to evaluate the concentration of productive sectors by regions and time periods. Specifically, it was sought: a) to verify the agglomeration of jobs and companies by regions, states and sectors in Brazil; and b) introduce two parameters that allow the evaluation of the concentration of productive sectors by region and time period. The years considered to reach the established objectives extend from 1994 to 2015. For the first objective a spatial analysis of agglomerations assisted by graphs was made. In relation to the second objective, we adopted the Locational Quotient (QL) technique, which allows us to identify the concentration of variables analyzed in this study. QL uses three indices in its definition (one to refer to the sector, another the region and the last to the time). Therefore, when fixing the index that refers to the region, the other two indexes defined a sequence of matrices, where each one was defined as Regional Matrix of Locational Quotients. Considering that each matrix has a covariance matrix, it was possible to define the parameters: first, as the norm of eigenvalues (NAV), which contains all the eigenvalues of the covariance matrix associated with it; the second in turn, Percentages Greater than one (PMU), which presents the largest percentages, tending to one, in the regional matrix. Data were obtained from the Integrated Automatic Data Recovery System (SIDRA), from the Brazilian Institute of Geography and Statistics (IBGE). The software used to manipulate the data consisted of Excel, Scilab 6.0 and Siad. Based on the results it was observed that the parameters introduced here synthesize the concentration of the sectors throughout each period for the regions. In this way, it can be concluded that the use of the parameters can be useful in the investigation of the local economic problems, indicating clues that point to the real needs of regional development. |
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Sandoval, Wilfredo Sosahttp://lattes.cnpq.br/6348109836924616http://lattes.cnpq.br/6601087522831430Ferreira, Rúbia Silene Alegre2019-05-17T14:26:18Z2018-12-14FERREIRA, Rúbia Silene Alegre. Uma análise espacial dos empregos e das empresas no Brasil. 2018. 54 f. Tese (Programa Stricto Sensu em Economia de Empresas) - Universidade Católica de Brasília, Brasília, 2018.https://bdtd.ucb.br:8443/jspui/handle/tede/2541The general objective of this study was to work in a methodology that would allow the development of two parameters to evaluate the concentration of productive sectors by regions and time periods. Specifically, it was sought: a) to verify the agglomeration of jobs and companies by regions, states and sectors in Brazil; and b) introduce two parameters that allow the evaluation of the concentration of productive sectors by region and time period. The years considered to reach the established objectives extend from 1994 to 2015. For the first objective a spatial analysis of agglomerations assisted by graphs was made. In relation to the second objective, we adopted the Locational Quotient (QL) technique, which allows us to identify the concentration of variables analyzed in this study. QL uses three indices in its definition (one to refer to the sector, another the region and the last to the time). Therefore, when fixing the index that refers to the region, the other two indexes defined a sequence of matrices, where each one was defined as Regional Matrix of Locational Quotients. Considering that each matrix has a covariance matrix, it was possible to define the parameters: first, as the norm of eigenvalues (NAV), which contains all the eigenvalues of the covariance matrix associated with it; the second in turn, Percentages Greater than one (PMU), which presents the largest percentages, tending to one, in the regional matrix. Data were obtained from the Integrated Automatic Data Recovery System (SIDRA), from the Brazilian Institute of Geography and Statistics (IBGE). The software used to manipulate the data consisted of Excel, Scilab 6.0 and Siad. Based on the results it was observed that the parameters introduced here synthesize the concentration of the sectors throughout each period for the regions. In this way, it can be concluded that the use of the parameters can be useful in the investigation of the local economic problems, indicating clues that point to the real needs of regional development.O objetivo geral deste estudo foi o de trabalhar em uma metodologia que possibilitasse o desenvolvimento de dois parâmetros para avaliar a concentração de setores produtivos por regiões e períodos de tempo. Especificamente, buscou-se: a) verificar a aglomeração dos empregos e das empresas por regiões, estados e setores no Brasil; e b) introduzir dois parâmetros que possibilitem a avaliação da concentração dos setores produtivos por regiões e período de tempo. Os anos considerados para alcançar os objetivos estabelecidos se estendem de 1994 a 2015. Para o primeiro objetivo fez-se uma análise espacial das aglomerações auxiliada por gráficos. Em relação ao segundo objetivo, adotou-se a técnica do Quociente Locacional (QL), que permite identificar a concentração das variáveis analisadas neste estudo. O QL utiliza três índices na sua definição (um para referenciar ao setor, outro a região e o último ao tempo). Portanto, ao se fixar o índice que faz referência à região, os outros dois índices definiram uma sequência de matrizes, onde cada uma delas foi definida como Matriz Regional de Quocientes Locacionais. Considerando-se que cada matriz tem associada uma matriz de covariância, assim foi possível se definir os parâmetros: o primeiro, como a Norma de Autovalores (NAV), que contém todos os autovalores da matriz de covariância a ela associada; o segundo por sua vez, Porcentagens Maiores que um (PMU), que apresenta as porcentagens maiores, tendendo a um, na matriz regional. Os dados foram obtidos no Sistema Integrado de Dados de Recuperação Automática (SIDRA), do Instituto Brasileiro de Geografia e Estatística (IBGE). Os softwares utilizados para a manipulação dos dados consistiram no Excel, Scilab 6.0 e Siad. Com base nos resultados observou-se que os parâmetros ora introduzidos sintetizam a concentração dos setores ao longo de cada período para as regiões. Desta forma, conclui-se que o uso dos parâmetros pode ser útil na investigação dos problemas econômicos locais, sinalizando pistas que apontem as reais necessidades de desenvolvimento regional.Submitted by Sara Ribeiro (sara.ribeiro@ucb.br) on 2019-05-17T14:25:49Z No. of bitstreams: 1 RubiaSileneAlegreFerreiraTese2018.pdf: 1583978 bytes, checksum: 538de9081ecc028c7f6c5e81ba041911 (MD5)Approved for entry into archive by Sara Ribeiro (sara.ribeiro@ucb.br) on 2019-05-17T14:26:18Z (GMT) No. of bitstreams: 1 RubiaSileneAlegreFerreiraTese2018.pdf: 1583978 bytes, checksum: 538de9081ecc028c7f6c5e81ba041911 (MD5)Made available in DSpace on 2019-05-17T14:26:18Z (GMT). No. of bitstreams: 1 RubiaSileneAlegreFerreiraTese2018.pdf: 1583978 bytes, checksum: 538de9081ecc028c7f6c5e81ba041911 (MD5) Previous issue date: 2018-12-14application/pdfhttps://bdtd.ucb.br:8443/jspui/retrieve/6282/RubiaSileneAlegreFerreiraTese2018.pdf.jpgporUniversidade Católica de BrasíliaPrograma Stricto Sensu em Economia de EmpresasUCBBrasilEscola de Gestão e NegóciosEmpresaEmpregosAglomeraçãoQuociente Locacional RegionalRegional Locational QuotientAgglomerationCompaniesJobsCNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIAUma análise espacial dos empregos e das empresas no Brasilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UCBinstname:Universidade Católica de Brasíliainstacron:UCBTHUMBNAILRubiaSileneAlegreFerreiraTese2018.pdf.jpgRubiaSileneAlegreFerreiraTese2018.pdf.jpgimage/jpeg5545https://bdtd.ucb.br:8443/jspui/bitstream/tede/2541/4/RubiaSileneAlegreFerreiraTese2018.pdf.jpgeeee036bf84c76e047ac27552a578765MD54TEXTRubiaSileneAlegreFerreiraTese2018.pdf.txtRubiaSileneAlegreFerreiraTese2018.pdf.txttext/plain120996https://bdtd.ucb.br:8443/jspui/bitstream/tede/2541/3/RubiaSileneAlegreFerreiraTese2018.pdf.txtbf4c89b0822bce8a8c444d72d267c8d0MD53ORIGINALRubiaSileneAlegreFerreiraTese2018.pdfRubiaSileneAlegreFerreiraTese2018.pdfapplication/pdf1583978https://bdtd.ucb.br:8443/jspui/bitstream/tede/2541/2/RubiaSileneAlegreFerreiraTese2018.pdf538de9081ecc028c7f6c5e81ba041911MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81905https://bdtd.ucb.br:8443/jspui/bitstream/tede/2541/1/license.txt75558dcf859532757239878b42f1c2c7MD51tede/2541oai:bdtd.ucb.br:tede/25412019-05-18 01:05:54.596Biblioteca Digital de Dissertações da Universidade Católica de Brasília - UCBsdi@ucb.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 |
dc.title.por.fl_str_mv |
Uma análise espacial dos empregos e das empresas no Brasil |
title |
Uma análise espacial dos empregos e das empresas no Brasil |
spellingShingle |
Uma análise espacial dos empregos e das empresas no Brasil Ferreira, Rúbia Silene Alegre Empresa Empregos Aglomeração Quociente Locacional Regional Regional Locational Quotient Agglomeration Companies Jobs CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA |
title_short |
Uma análise espacial dos empregos e das empresas no Brasil |
title_full |
Uma análise espacial dos empregos e das empresas no Brasil |
title_fullStr |
Uma análise espacial dos empregos e das empresas no Brasil |
title_full_unstemmed |
Uma análise espacial dos empregos e das empresas no Brasil |
title_sort |
Uma análise espacial dos empregos e das empresas no Brasil |
author |
Ferreira, Rúbia Silene Alegre |
author_facet |
Ferreira, Rúbia Silene Alegre |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Sandoval, Wilfredo Sosa |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/6348109836924616 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/6601087522831430 |
dc.contributor.author.fl_str_mv |
Ferreira, Rúbia Silene Alegre |
contributor_str_mv |
Sandoval, Wilfredo Sosa |
dc.subject.por.fl_str_mv |
Empresa Empregos Aglomeração Quociente Locacional Regional |
topic |
Empresa Empregos Aglomeração Quociente Locacional Regional Regional Locational Quotient Agglomeration Companies Jobs CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA |
dc.subject.eng.fl_str_mv |
Regional Locational Quotient Agglomeration Companies Jobs |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA |
dc.description.abstract.eng.fl_txt_mv |
The general objective of this study was to work in a methodology that would allow the development of two parameters to evaluate the concentration of productive sectors by regions and time periods. Specifically, it was sought: a) to verify the agglomeration of jobs and companies by regions, states and sectors in Brazil; and b) introduce two parameters that allow the evaluation of the concentration of productive sectors by region and time period. The years considered to reach the established objectives extend from 1994 to 2015. For the first objective a spatial analysis of agglomerations assisted by graphs was made. In relation to the second objective, we adopted the Locational Quotient (QL) technique, which allows us to identify the concentration of variables analyzed in this study. QL uses three indices in its definition (one to refer to the sector, another the region and the last to the time). Therefore, when fixing the index that refers to the region, the other two indexes defined a sequence of matrices, where each one was defined as Regional Matrix of Locational Quotients. Considering that each matrix has a covariance matrix, it was possible to define the parameters: first, as the norm of eigenvalues (NAV), which contains all the eigenvalues of the covariance matrix associated with it; the second in turn, Percentages Greater than one (PMU), which presents the largest percentages, tending to one, in the regional matrix. Data were obtained from the Integrated Automatic Data Recovery System (SIDRA), from the Brazilian Institute of Geography and Statistics (IBGE). The software used to manipulate the data consisted of Excel, Scilab 6.0 and Siad. Based on the results it was observed that the parameters introduced here synthesize the concentration of the sectors throughout each period for the regions. In this way, it can be concluded that the use of the parameters can be useful in the investigation of the local economic problems, indicating clues that point to the real needs of regional development. |
dc.description.abstract.por.fl_txt_mv |
O objetivo geral deste estudo foi o de trabalhar em uma metodologia que possibilitasse o desenvolvimento de dois parâmetros para avaliar a concentração de setores produtivos por regiões e períodos de tempo. Especificamente, buscou-se: a) verificar a aglomeração dos empregos e das empresas por regiões, estados e setores no Brasil; e b) introduzir dois parâmetros que possibilitem a avaliação da concentração dos setores produtivos por regiões e período de tempo. Os anos considerados para alcançar os objetivos estabelecidos se estendem de 1994 a 2015. Para o primeiro objetivo fez-se uma análise espacial das aglomerações auxiliada por gráficos. Em relação ao segundo objetivo, adotou-se a técnica do Quociente Locacional (QL), que permite identificar a concentração das variáveis analisadas neste estudo. O QL utiliza três índices na sua definição (um para referenciar ao setor, outro a região e o último ao tempo). Portanto, ao se fixar o índice que faz referência à região, os outros dois índices definiram uma sequência de matrizes, onde cada uma delas foi definida como Matriz Regional de Quocientes Locacionais. Considerando-se que cada matriz tem associada uma matriz de covariância, assim foi possível se definir os parâmetros: o primeiro, como a Norma de Autovalores (NAV), que contém todos os autovalores da matriz de covariância a ela associada; o segundo por sua vez, Porcentagens Maiores que um (PMU), que apresenta as porcentagens maiores, tendendo a um, na matriz regional. Os dados foram obtidos no Sistema Integrado de Dados de Recuperação Automática (SIDRA), do Instituto Brasileiro de Geografia e Estatística (IBGE). Os softwares utilizados para a manipulação dos dados consistiram no Excel, Scilab 6.0 e Siad. Com base nos resultados observou-se que os parâmetros ora introduzidos sintetizam a concentração dos setores ao longo de cada período para as regiões. Desta forma, conclui-se que o uso dos parâmetros pode ser útil na investigação dos problemas econômicos locais, sinalizando pistas que apontem as reais necessidades de desenvolvimento regional. |
description |
The general objective of this study was to work in a methodology that would allow the development of two parameters to evaluate the concentration of productive sectors by regions and time periods. Specifically, it was sought: a) to verify the agglomeration of jobs and companies by regions, states and sectors in Brazil; and b) introduce two parameters that allow the evaluation of the concentration of productive sectors by region and time period. The years considered to reach the established objectives extend from 1994 to 2015. For the first objective a spatial analysis of agglomerations assisted by graphs was made. In relation to the second objective, we adopted the Locational Quotient (QL) technique, which allows us to identify the concentration of variables analyzed in this study. QL uses three indices in its definition (one to refer to the sector, another the region and the last to the time). Therefore, when fixing the index that refers to the region, the other two indexes defined a sequence of matrices, where each one was defined as Regional Matrix of Locational Quotients. Considering that each matrix has a covariance matrix, it was possible to define the parameters: first, as the norm of eigenvalues (NAV), which contains all the eigenvalues of the covariance matrix associated with it; the second in turn, Percentages Greater than one (PMU), which presents the largest percentages, tending to one, in the regional matrix. Data were obtained from the Integrated Automatic Data Recovery System (SIDRA), from the Brazilian Institute of Geography and Statistics (IBGE). The software used to manipulate the data consisted of Excel, Scilab 6.0 and Siad. Based on the results it was observed that the parameters introduced here synthesize the concentration of the sectors throughout each period for the regions. In this way, it can be concluded that the use of the parameters can be useful in the investigation of the local economic problems, indicating clues that point to the real needs of regional development. |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018-12-14 |
dc.date.accessioned.fl_str_mv |
2019-05-17T14:26:18Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
status_str |
publishedVersion |
format |
doctoralThesis |
dc.identifier.citation.fl_str_mv |
FERREIRA, Rúbia Silene Alegre. Uma análise espacial dos empregos e das empresas no Brasil. 2018. 54 f. Tese (Programa Stricto Sensu em Economia de Empresas) - Universidade Católica de Brasília, Brasília, 2018. |
dc.identifier.uri.fl_str_mv |
https://bdtd.ucb.br:8443/jspui/handle/tede/2541 |
identifier_str_mv |
FERREIRA, Rúbia Silene Alegre. Uma análise espacial dos empregos e das empresas no Brasil. 2018. 54 f. Tese (Programa Stricto Sensu em Economia de Empresas) - Universidade Católica de Brasília, Brasília, 2018. |
url |
https://bdtd.ucb.br:8443/jspui/handle/tede/2541 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Católica de Brasília |
dc.publisher.program.fl_str_mv |
Programa Stricto Sensu em Economia de Empresas |
dc.publisher.initials.fl_str_mv |
UCB |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Escola de Gestão e Negócios |
publisher.none.fl_str_mv |
Universidade Católica de Brasília |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da UCB instname:Universidade Católica de Brasília instacron:UCB |
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Universidade Católica de Brasília |
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UCB |
bitstream.url.fl_str_mv |
https://bdtd.ucb.br:8443/jspui/bitstream/tede/2541/4/RubiaSileneAlegreFerreiraTese2018.pdf.jpg https://bdtd.ucb.br:8443/jspui/bitstream/tede/2541/3/RubiaSileneAlegreFerreiraTese2018.pdf.txt https://bdtd.ucb.br:8443/jspui/bitstream/tede/2541/2/RubiaSileneAlegreFerreiraTese2018.pdf https://bdtd.ucb.br:8443/jspui/bitstream/tede/2541/1/license.txt |
bitstream.checksum.fl_str_mv |
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bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Biblioteca Digital de Dissertações da Universidade Católica de Brasília - UCB |
repository.mail.fl_str_mv |
sdi@ucb.br |
_version_ |
1643299936710688768 |