Aplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017

Detalhes bibliográficos
Autor(a) principal: Souza, Fábio Roberto de
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações do UFSM
Texto Completo: http://repositorio.ufsm.br/handle/1/27859
Resumo: Directed to the application of the Kaldor-Verdoorn "Law", to Brazilian agriculture for the year 2017, due to the active role that the agricultural sector has in the economic and social spheres of Brazil, the present study aimed to investigate the relationship between productivity of labor and the production of the national agricultural sector, aiming to analyze the performance of labor productivity in crops located in Brazilian geographic micro-regions in the year 2017, examining the structure of spatial clusters to know the sources of growth in agriculture. For this, two methodologies were used to investigate the relationship of Kaldor's second "Law", the first being the exploratory analysis of spatial data (AEDE) and the second a simple regression with the models of spatial dependence: SAR, SEM and SAC. The results originated by the exploratory analysis of spatial data (AEDE), found that both for the univariate and for the bivariate case, referring to the Kaldor-Verdoorn relationship, the highest concentrations of spatial clusters were located in the microregions that obtained high and low indexes of agricultural production and productivity. However, specifically, for the bivariate case, that is, Kaldor's “Law” relation, there was also a high concentration of spatial clusters of the Low-High type. As for the spatial independence models applied in the Kaldor-Verdoorn relationship, after performing and interpreting all the tests, the one that proved to be the most suitable for the inferences of the present study was the SAC spatial autoregressive error model. The results evidenced by this spatial model showed that for the five hundred and fifty-four geographic micro-regions, the relationship of Kaldor's second "Law", between the people occupied, or employed, in agriculture and the value of Brazilian agricultural production, presented elasticity superior to 0.65%, thus, indicating a high degree of influence of the second variable on the first.
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spelling 2023-02-22T20:02:06Z2023-02-22T20:02:06Z2022-09-30http://repositorio.ufsm.br/handle/1/27859Directed to the application of the Kaldor-Verdoorn "Law", to Brazilian agriculture for the year 2017, due to the active role that the agricultural sector has in the economic and social spheres of Brazil, the present study aimed to investigate the relationship between productivity of labor and the production of the national agricultural sector, aiming to analyze the performance of labor productivity in crops located in Brazilian geographic micro-regions in the year 2017, examining the structure of spatial clusters to know the sources of growth in agriculture. For this, two methodologies were used to investigate the relationship of Kaldor's second "Law", the first being the exploratory analysis of spatial data (AEDE) and the second a simple regression with the models of spatial dependence: SAR, SEM and SAC. The results originated by the exploratory analysis of spatial data (AEDE), found that both for the univariate and for the bivariate case, referring to the Kaldor-Verdoorn relationship, the highest concentrations of spatial clusters were located in the microregions that obtained high and low indexes of agricultural production and productivity. However, specifically, for the bivariate case, that is, Kaldor's “Law” relation, there was also a high concentration of spatial clusters of the Low-High type. As for the spatial independence models applied in the Kaldor-Verdoorn relationship, after performing and interpreting all the tests, the one that proved to be the most suitable for the inferences of the present study was the SAC spatial autoregressive error model. The results evidenced by this spatial model showed that for the five hundred and fifty-four geographic micro-regions, the relationship of Kaldor's second "Law", between the people occupied, or employed, in agriculture and the value of Brazilian agricultural production, presented elasticity superior to 0.65%, thus, indicating a high degree of influence of the second variable on the first.Direcionado a aplicação da “Lei” de Kaldor-Verdoorn, à agricultura brasileira para o ano de 2017, devido ao papel ativo que o setor agrícola tem nas esferas econômicas e sociais do Brasil, o presente estudo teve como propósito investigar a relação entre a produtividade do trabalho e a produção do setor agrícola nacional, objetivando analisar o desempenho da produtividade do trabalho nas lavouras localizadas nas microrregiões geográficas brasileiras no ano de 2017, examinando a estrutura de clusters espaciais para conhecer as fontes de crescimento na agrícola. Para isso, foi utilizado duas metodologias para investigação da relação da segunda “Lei” de Kaldor, sendo a primeira a análise exploratória de dados espaciais (AEDE) e a segunda uma regressão simples com os modelos de dependência espacial: SAR, SEM e SAC. Os resultados originados pela análise exploratória de dados espaciais (AEDE), constataram que tanto para o caso univariado quanto para o bivariado, referente a relação de Kaldor-Verdoorn, as maiores concentrações de clusters espaciais se localizaram nas microrregiões que obtiveram Altos e Baixos índices de produção e produtividade agrícola. No entanto, especificamente, para o caso bivariado, ou seja, da relação da “Lei” de Kaldor, também, houve grande concentração de clusters espaciais do tipo Baixo-Alto. Quanto aos modelos de independência espacial aplicados na relação de Kaldor-Verdoorn, após a realização e interpretação de todos os testes, o que se mostrou mais adequado para as inferências do presente estudo foi o modelo de erro autorregressivo espacial SAC. Os resultados evidenciados por esse modelo espacial demostraram que para as quinhentas e cinquenta e quatro microrregiões geográficas, a relação da segunda “Lei” de Kaldor, entre o pessoal ocupado, ou empregado, na agricultura e o valor da produção agrícola brasileira apresentou elasticidade superior a 0,65%, assim, apontado alto grau de influência da segunda variável sobre a primeira.porUniversidade Federal de Santa MariaCentro de Ciências Sociais e HumanasPrograma de Pós-Graduação em Economia e DesenvolvimentoUFSMBrasilEconomiaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAgricultura“Lei” de Kaldor-VerdoornModelos espaciaisAgricultureKaldor-Verdoorn “Law”Spatial modelsCNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIAAplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017The “Law” of Kaldor-Verdoorn as a possible instrument for analysis of brazilian agricultureinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisCoronel, Daniel Arrudahttp://lattes.cnpq.br/9265604274170933Freitas, Clailton Ataídes deMassuquetti, AngélicaBender Filho, Reisolihttp://lattes.cnpq.br/1676737747170911Souza, Fábio Roberto de600300000000600600600600600600c5f7e145-5c80-4b8f-b8ac-11b990235657b3aaedf1-5adf-4b37-a819-198b92ef85251d4b06da-3cbd-440f-b15f-975a89a5b0ce1057bcef-20cc-4372-b44f-cf02e5c67837e990c5b5-255c-4895-85c5-766af8863bafreponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDIS_PPGED_2022_SOUZA_FÁBIO.pdfDIS_PPGED_2022_SOUZA_FÁBIO.pdfDissertação de mestradoapplication/pdf2592819http://repositorio.ufsm.br/bitstream/1/27859/1/DIS_PPGED_2022_SOUZA_F%c3%81BIO.pdfea6026cd5c175ea5b73905ee49f8b472MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.por.fl_str_mv Aplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017
dc.title.alternative.eng.fl_str_mv The “Law” of Kaldor-Verdoorn as a possible instrument for analysis of brazilian agriculture
title Aplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017
spellingShingle Aplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017
Souza, Fábio Roberto de
Agricultura
“Lei” de Kaldor-Verdoorn
Modelos espaciais
Agriculture
Kaldor-Verdoorn “Law”
Spatial models
CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA
title_short Aplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017
title_full Aplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017
title_fullStr Aplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017
title_full_unstemmed Aplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017
title_sort Aplicação da “Lei” de Kaldor-Verdoorn para a agricultura brasileira: análise para o ano de 2017
author Souza, Fábio Roberto de
author_facet Souza, Fábio Roberto de
author_role author
dc.contributor.advisor1.fl_str_mv Coronel, Daniel Arruda
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/9265604274170933
dc.contributor.advisor-co1.fl_str_mv Freitas, Clailton Ataídes de
dc.contributor.referee1.fl_str_mv Massuquetti, Angélica
dc.contributor.referee2.fl_str_mv Bender Filho, Reisoli
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/1676737747170911
dc.contributor.author.fl_str_mv Souza, Fábio Roberto de
contributor_str_mv Coronel, Daniel Arruda
Freitas, Clailton Ataídes de
Massuquetti, Angélica
Bender Filho, Reisoli
dc.subject.por.fl_str_mv Agricultura
“Lei” de Kaldor-Verdoorn
Modelos espaciais
topic Agricultura
“Lei” de Kaldor-Verdoorn
Modelos espaciais
Agriculture
Kaldor-Verdoorn “Law”
Spatial models
CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA
dc.subject.eng.fl_str_mv Agriculture
Kaldor-Verdoorn “Law”
Spatial models
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA
description Directed to the application of the Kaldor-Verdoorn "Law", to Brazilian agriculture for the year 2017, due to the active role that the agricultural sector has in the economic and social spheres of Brazil, the present study aimed to investigate the relationship between productivity of labor and the production of the national agricultural sector, aiming to analyze the performance of labor productivity in crops located in Brazilian geographic micro-regions in the year 2017, examining the structure of spatial clusters to know the sources of growth in agriculture. For this, two methodologies were used to investigate the relationship of Kaldor's second "Law", the first being the exploratory analysis of spatial data (AEDE) and the second a simple regression with the models of spatial dependence: SAR, SEM and SAC. The results originated by the exploratory analysis of spatial data (AEDE), found that both for the univariate and for the bivariate case, referring to the Kaldor-Verdoorn relationship, the highest concentrations of spatial clusters were located in the microregions that obtained high and low indexes of agricultural production and productivity. However, specifically, for the bivariate case, that is, Kaldor's “Law” relation, there was also a high concentration of spatial clusters of the Low-High type. As for the spatial independence models applied in the Kaldor-Verdoorn relationship, after performing and interpreting all the tests, the one that proved to be the most suitable for the inferences of the present study was the SAC spatial autoregressive error model. The results evidenced by this spatial model showed that for the five hundred and fifty-four geographic micro-regions, the relationship of Kaldor's second "Law", between the people occupied, or employed, in agriculture and the value of Brazilian agricultural production, presented elasticity superior to 0.65%, thus, indicating a high degree of influence of the second variable on the first.
publishDate 2022
dc.date.issued.fl_str_mv 2022-09-30
dc.date.accessioned.fl_str_mv 2023-02-22T20:02:06Z
dc.date.available.fl_str_mv 2023-02-22T20:02:06Z
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rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
Centro de Ciências Sociais e Humanas
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dc.publisher.initials.fl_str_mv UFSM
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Economia
publisher.none.fl_str_mv Universidade Federal de Santa Maria
Centro de Ciências Sociais e Humanas
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