Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazil

Autores
de Oliveira, Sandra Cristina; Rodrigues de Amorim, Fernando; Ceron Barbosa, Cássio; Galvez de Andrade, Alequexandre; Del Giorgio Solfa, Federico
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The costs of agricultural inputs added to those of labor represent almost a third of the total cost of Brazilian sugarcane production. This study analyzes the behavior of the price per ton of sugarcane in Brazil, relating it to the main production costs of this cultivation. Twelve price indicators from January 2015 to December 2020 were evaluated. First, the data were adjusted to a multiple linear regression model to identify the significant variables on variation in the price per ton of sugarcane. Then, the Monte Carlo simulation was used to measure the level of certainty of occurrence of these variables, and forecasts were obtained from the adjustment of ARIMA models. The results showed the influence of the costs of diesel oil, two agricultural pesticides, and daily laborers on the price of sugarcane, besides an increasing trend of its, providing relevant short-term projections for decision-making about investments in the agribusiness sector.
Materia
Economía y Negocios
Brazilian agribusiness
sugarcane production
linear regression
Monte Carlo simulation
ARIMA models
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/11674
Acceder
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network_acronym_str CICBA
repository_id_str 9441
network_name_str CIC Digital (CICBA)
spelling Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazilde Oliveira, Sandra CristinaRodrigues de Amorim, FernandoCeron Barbosa, CássioGalvez de Andrade, AlequexandreDel Giorgio Solfa, FedericoEconomía y NegociosBrazilian agribusinesssugarcane productionlinear regressionMonte Carlo simulationARIMA modelsThe costs of agricultural inputs added to those of labor represent almost a third of the total cost of Brazilian sugarcane production. This study analyzes the behavior of the price per ton of sugarcane in Brazil, relating it to the main production costs of this cultivation. Twelve price indicators from January 2015 to December 2020 were evaluated. First, the data were adjusted to a multiple linear regression model to identify the significant variables on variation in the price per ton of sugarcane. Then, the Monte Carlo simulation was used to measure the level of certainty of occurrence of these variables, and forecasts were obtained from the adjustment of ARIMA models. The results showed the influence of the costs of diesel oil, two agricultural pesticides, and daily laborers on the price of sugarcane, besides an increasing trend of its, providing relevant short-term projections for decision-making about investments in the agribusiness sector.2022-09-23info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/11674enginfo:eu-repo/semantics/altIdentifier/hdl/10915/142724info:eu-repo/semantics/altIdentifier/doi/10.11114/ijsss.v10i6.5688info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-10-16T09:27:22Zoai:digital.cic.gba.gob.ar:11746/11674Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-10-16 09:27:22.422CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazil
title Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazil
spellingShingle Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazil
de Oliveira, Sandra Cristina
Economía y Negocios
Brazilian agribusiness
sugarcane production
linear regression
Monte Carlo simulation
ARIMA models
title_short Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazil
title_full Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazil
title_fullStr Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazil
title_full_unstemmed Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazil
title_sort Effect of Production Costs on the Price per Ton of Sugarcane: The Case of Brazil
dc.creator.none.fl_str_mv de Oliveira, Sandra Cristina
Rodrigues de Amorim, Fernando
Ceron Barbosa, Cássio
Galvez de Andrade, Alequexandre
Del Giorgio Solfa, Federico
author de Oliveira, Sandra Cristina
author_facet de Oliveira, Sandra Cristina
Rodrigues de Amorim, Fernando
Ceron Barbosa, Cássio
Galvez de Andrade, Alequexandre
Del Giorgio Solfa, Federico
author_role author
author2 Rodrigues de Amorim, Fernando
Ceron Barbosa, Cássio
Galvez de Andrade, Alequexandre
Del Giorgio Solfa, Federico
author2_role author
author
author
author
dc.subject.none.fl_str_mv Economía y Negocios
Brazilian agribusiness
sugarcane production
linear regression
Monte Carlo simulation
ARIMA models
topic Economía y Negocios
Brazilian agribusiness
sugarcane production
linear regression
Monte Carlo simulation
ARIMA models
dc.description.none.fl_txt_mv The costs of agricultural inputs added to those of labor represent almost a third of the total cost of Brazilian sugarcane production. This study analyzes the behavior of the price per ton of sugarcane in Brazil, relating it to the main production costs of this cultivation. Twelve price indicators from January 2015 to December 2020 were evaluated. First, the data were adjusted to a multiple linear regression model to identify the significant variables on variation in the price per ton of sugarcane. Then, the Monte Carlo simulation was used to measure the level of certainty of occurrence of these variables, and forecasts were obtained from the adjustment of ARIMA models. The results showed the influence of the costs of diesel oil, two agricultural pesticides, and daily laborers on the price of sugarcane, besides an increasing trend of its, providing relevant short-term projections for decision-making about investments in the agribusiness sector.
description The costs of agricultural inputs added to those of labor represent almost a third of the total cost of Brazilian sugarcane production. This study analyzes the behavior of the price per ton of sugarcane in Brazil, relating it to the main production costs of this cultivation. Twelve price indicators from January 2015 to December 2020 were evaluated. First, the data were adjusted to a multiple linear regression model to identify the significant variables on variation in the price per ton of sugarcane. Then, the Monte Carlo simulation was used to measure the level of certainty of occurrence of these variables, and forecasts were obtained from the adjustment of ARIMA models. The results showed the influence of the costs of diesel oil, two agricultural pesticides, and daily laborers on the price of sugarcane, besides an increasing trend of its, providing relevant short-term projections for decision-making about investments in the agribusiness sector.
publishDate 2022
dc.date.none.fl_str_mv 2022-09-23
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/11674
url https://digital.cic.gba.gob.ar/handle/11746/11674
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/hdl/10915/142724
info:eu-repo/semantics/altIdentifier/doi/10.11114/ijsss.v10i6.5688
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:CIC Digital (CICBA)
instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron:CICBA
reponame_str CIC Digital (CICBA)
collection CIC Digital (CICBA)
instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron_str CICBA
institution CICBA
repository.name.fl_str_mv CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
repository.mail.fl_str_mv marisa.degiusti@sedici.unlp.edu.ar
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