Determination of econometric factors impacting coffee production in Minas Gerais
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/29264 |
Resumo: | The study of the relationships between the econometric components of coffee production, estimated by correlations, for example, is of great relevance. These metrics provide useful information for the decision process in the production chain of this commodity. However, the quantification and interpretation of the correlation’s magnitude do not imply direct and indirect effects applicable to the agribusiness reality. In this context, trail analysis presents as a viable alternative. The objective of this work was, through trail analysis, to determine the direct and indirect effects of econometric components on coffee production. The data used are from coffee producing municipalities in Minas Gerais, in the period from 2008 to 2013, in which coffee production was observed as the basic (dependent) variable and as independent (explanatories) variables the harvested area of the grain, the average age of the workers in the field, the average remuneration of workers in the activity, the price paid for the product and the number of producing properties per municipality. There was a strong variation with year and municipality effects, with the rest of the explanation referring more to the primary variables (planted area and number of properties in the municipality), trail coefficients 0.38 and 0.05, respectively. The other variables interfere indirectly, through the modification of both. Path analysis proved to be useful in elucidating part of the coffee production chain variability and can be used as an aid in making business decisions in the sector. |
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Determination of econometric factors impacting coffee production in Minas GeraisDeterminación de factores econométricos que impactan la producción de café en Minas GeraisDeterminação dos fatores econométricos de impacto na produção cafeeira em Minas GeraisCaféAnálise de trilhaCorrelaçãoComponentes econométricos.Análise de rastroCaféCorrelaciónComponentes econométricos.Path analysisCorrelationCoffeeEconometric components.The study of the relationships between the econometric components of coffee production, estimated by correlations, for example, is of great relevance. These metrics provide useful information for the decision process in the production chain of this commodity. However, the quantification and interpretation of the correlation’s magnitude do not imply direct and indirect effects applicable to the agribusiness reality. In this context, trail analysis presents as a viable alternative. The objective of this work was, through trail analysis, to determine the direct and indirect effects of econometric components on coffee production. The data used are from coffee producing municipalities in Minas Gerais, in the period from 2008 to 2013, in which coffee production was observed as the basic (dependent) variable and as independent (explanatories) variables the harvested area of the grain, the average age of the workers in the field, the average remuneration of workers in the activity, the price paid for the product and the number of producing properties per municipality. There was a strong variation with year and municipality effects, with the rest of the explanation referring more to the primary variables (planted area and number of properties in the municipality), trail coefficients 0.38 and 0.05, respectively. The other variables interfere indirectly, through the modification of both. Path analysis proved to be useful in elucidating part of the coffee production chain variability and can be used as an aid in making business decisions in the sector.El estudio de las relaciones entre los componentes econométricos de la producción de café, estimados por correlaciones, es de gran relevancia. Ellas brindan información útil para el proceso de decisión en la cadena productiva de este producto básico. La cuantificación e interpretación de la magnitud de las correlaciones no implican efectos directos e indirectos aplicables a la realidad de los agronegocios. Así, el análisis de senderos se presenta como una alternativa viable. Este trabajo tuvo como objetivo, a través del análisis de senderos, determinar los efectos directos e indirectos de los componentes econométricos en la producción de café. Los datos son de municipios productores de café de Minas Gerais, período de 2008 a 2013, teniendo como variable básica (dependiente) la producción de café y como variables independientes (explicativas) el área cosechada del grano, la edad promedio de los trabajadores del campo, la remuneración promedio de los trabajadores de la actividad, el precio pagado por el producto y el número de propiedades productoras por municipio. Hubo una fuerte variación con los efectos de año y municipio, con el resto de la explicación refiriéndose más a las variables primarias (área sembrada y número de propiedades en el municipio), coeficientes de rastro 0.38 y 0.05, respectivamente. Las otras variables interfieren indirectamente, a través de la modificación de estas dos. El análisis de trayectoria demostró ser útil para dilucidar parte de la variabilidad de la cadena productiva del café y puede utilizarse como ayuda para la toma de decisiones comerciales en el sector.O estudo das relações existentes entre os componentes econométricos da produção de café, estimadas por correlações, por exemplo, é de grande relevância. Estas métricas fornecem informações úteis para o processo de decisão na cadeia produtiva dessa commodity. Todavia, a quantificação e a interpretação da magnitude das correlações não implicam efeitos diretos e indiretos aplicáveis a realidade do agronegócio. Nesse contexto, a análise de trilha apresenta-se como uma alternativa viável. O objetivo deste trabalho foi, através da análise de trilha, determinar os efeitos diretos e indiretos de componentes econométricos sobre a produção de café. Os dados utilizados são de municípios mineiros produtores de café, no período de 2008 a 2013, nos quais foi observada a produção de café como a variável básica (dependente) e como variáveis independentes (explicativas) a área colhida do grão, a idade média dos trabalhadores no campo, a remuneração média dos trabalhadores na atividade, o preço pago pelo produto e o número de propriedades produtoras por município. Observou-se forte variação com efeitos de ano e de município, sendo que o restante da explicação se refere mais às variáveis primárias (área plantada e número de propriedades do município - coeficientes de trilha 0,38 e 0,05, respectivamente). As demais variáveis interferem indiretamente, por meio da modificação dessas duas. A análise de trilha mostrou-se útil em elucidar parte da variabilidade da cadeia produtiva do café e poderá ser usada como auxiliar na tomada de decisões de negócio do setor.Research, Society and Development2022-05-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2926410.33448/rsd-v11i6.29264Research, Society and Development; Vol. 11 No. 6; e39611629264Research, Society and Development; Vol. 11 Núm. 6; e39611629264Research, Society and Development; v. 11 n. 6; e396116292642525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/29264/25335Copyright (c) 2022 Luciano Ribeiro Galvão; Júlio Sílvio de Sousa Bueno Filho; Andrezza Kellen Alves Pamplona; Caio Peixoto Chainhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessGalvão, Luciano Ribeiro Bueno Filho, Júlio Sílvio de Sousa Pamplona, Andrezza Kellen Alves Chain, Caio Peixoto 2022-05-13T18:04:10Zoai:ojs.pkp.sfu.ca:article/29264Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:46:24.079302Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Determination of econometric factors impacting coffee production in Minas Gerais Determinación de factores econométricos que impactan la producción de café en Minas Gerais Determinação dos fatores econométricos de impacto na produção cafeeira em Minas Gerais |
title |
Determination of econometric factors impacting coffee production in Minas Gerais |
spellingShingle |
Determination of econometric factors impacting coffee production in Minas Gerais Galvão, Luciano Ribeiro Café Análise de trilha Correlação Componentes econométricos. Análise de rastro Café Correlación Componentes econométricos. Path analysis Correlation Coffee Econometric components. |
title_short |
Determination of econometric factors impacting coffee production in Minas Gerais |
title_full |
Determination of econometric factors impacting coffee production in Minas Gerais |
title_fullStr |
Determination of econometric factors impacting coffee production in Minas Gerais |
title_full_unstemmed |
Determination of econometric factors impacting coffee production in Minas Gerais |
title_sort |
Determination of econometric factors impacting coffee production in Minas Gerais |
author |
Galvão, Luciano Ribeiro |
author_facet |
Galvão, Luciano Ribeiro Bueno Filho, Júlio Sílvio de Sousa Pamplona, Andrezza Kellen Alves Chain, Caio Peixoto |
author_role |
author |
author2 |
Bueno Filho, Júlio Sílvio de Sousa Pamplona, Andrezza Kellen Alves Chain, Caio Peixoto |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Galvão, Luciano Ribeiro Bueno Filho, Júlio Sílvio de Sousa Pamplona, Andrezza Kellen Alves Chain, Caio Peixoto |
dc.subject.por.fl_str_mv |
Café Análise de trilha Correlação Componentes econométricos. Análise de rastro Café Correlación Componentes econométricos. Path analysis Correlation Coffee Econometric components. |
topic |
Café Análise de trilha Correlação Componentes econométricos. Análise de rastro Café Correlación Componentes econométricos. Path analysis Correlation Coffee Econometric components. |
description |
The study of the relationships between the econometric components of coffee production, estimated by correlations, for example, is of great relevance. These metrics provide useful information for the decision process in the production chain of this commodity. However, the quantification and interpretation of the correlation’s magnitude do not imply direct and indirect effects applicable to the agribusiness reality. In this context, trail analysis presents as a viable alternative. The objective of this work was, through trail analysis, to determine the direct and indirect effects of econometric components on coffee production. The data used are from coffee producing municipalities in Minas Gerais, in the period from 2008 to 2013, in which coffee production was observed as the basic (dependent) variable and as independent (explanatories) variables the harvested area of the grain, the average age of the workers in the field, the average remuneration of workers in the activity, the price paid for the product and the number of producing properties per municipality. There was a strong variation with year and municipality effects, with the rest of the explanation referring more to the primary variables (planted area and number of properties in the municipality), trail coefficients 0.38 and 0.05, respectively. The other variables interfere indirectly, through the modification of both. Path analysis proved to be useful in elucidating part of the coffee production chain variability and can be used as an aid in making business decisions in the sector. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-05-01 |
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://rsdjournal.org/index.php/rsd/article/view/29264 10.33448/rsd-v11i6.29264 |
url |
https://rsdjournal.org/index.php/rsd/article/view/29264 |
identifier_str_mv |
10.33448/rsd-v11i6.29264 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/29264/25335 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 11 No. 6; e39611629264 Research, Society and Development; Vol. 11 Núm. 6; e39611629264 Research, Society and Development; v. 11 n. 6; e39611629264 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1797052836125605888 |