A study about the performance of time series models for the analysis of agricultural prices
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Data de Publicação: | 2012 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | GEPROS. Gestão da Produção. Operações e Sistemas |
Texto Completo: | https://revista.feb.unesp.br/gepros/article/view/770 |
Resumo: | Agribusiness is one of the most relevant achievements in Brazilian and world economies. Price is an important variable within this sector since economic and market conditions vary over time. Efficient modeling methods are needed to describe better the trends and the characteristics of that variable. The performance of time series techniques of fixed and open models for analysis of agricultural prices will be provided to demonstrate the feasibility of techniques for the generation of results in the wake of economic decisions. Historical time series of monthly average price of cash crops, such as groundnut, sugarcane, banana and orange, received by Brazilian producers, were analyzed for the period between August 1994 and December 2009 and updated by the General Price Index - Internal Availability. Current study shows that exponential smoothing models and Box & Jenkins modeling are viable alternatives for the adjustment of the above price series, each one with its specific characteristics. Keywords: Statistical Models; Agricultural Marketing; Resource Efficiency; Management; Decision Taking. |
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oai:ojs.gepros.emnuvens.com.br:article/770 |
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UNESP-2 |
network_name_str |
GEPROS. Gestão da Produção. Operações e Sistemas |
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A study about the performance of time series models for the analysis of agricultural pricesAgribusiness is one of the most relevant achievements in Brazilian and world economies. Price is an important variable within this sector since economic and market conditions vary over time. Efficient modeling methods are needed to describe better the trends and the characteristics of that variable. The performance of time series techniques of fixed and open models for analysis of agricultural prices will be provided to demonstrate the feasibility of techniques for the generation of results in the wake of economic decisions. Historical time series of monthly average price of cash crops, such as groundnut, sugarcane, banana and orange, received by Brazilian producers, were analyzed for the period between August 1994 and December 2009 and updated by the General Price Index - Internal Availability. Current study shows that exponential smoothing models and Box & Jenkins modeling are viable alternatives for the adjustment of the above price series, each one with its specific characteristics. Keywords: Statistical Models; Agricultural Marketing; Resource Efficiency; Management; Decision Taking.A Fundacao para o Desenvolvimento de Bauru (FunDeB)2012-09-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttps://revista.feb.unesp.br/gepros/article/view/77010.15675/gepros.v7i3.770Revista Gestão da Produção Operações e Sistemas; n. 3 (2012); 111984-2430reponame:GEPROS. Gestão da Produção. Operações e Sistemasinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporhttps://revista.feb.unesp.br/gepros/article/view/770/448https://revista.feb.unesp.br/gepros/article/view/770/1249https://revista.feb.unesp.br/gepros/article/view/770/1250https://revista.feb.unesp.br/gepros/article/view/770/1321Oliveira, Sandra Cristina dePereira, Leonardo Matheus MarcondesHanashiro, Juliana Tiemi SakaguchiVal, Patricia Carvalho doinfo:eu-repo/semantics/openAccess2012-10-01T02:47:05Zoai:ojs.gepros.emnuvens.com.br:article/770Revistahttps://revista.feb.unesp.br/geprosPUBhttps://revista.feb.unesp.br/gepros/oaigepros@feb.unesp.br||abjabbour@feb.unesp.br1984-24301809-614Xopendoar:2012-10-01T02:47:05GEPROS. Gestão da Produção. Operações e Sistemas - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A study about the performance of time series models for the analysis of agricultural prices |
title |
A study about the performance of time series models for the analysis of agricultural prices |
spellingShingle |
A study about the performance of time series models for the analysis of agricultural prices Oliveira, Sandra Cristina de |
title_short |
A study about the performance of time series models for the analysis of agricultural prices |
title_full |
A study about the performance of time series models for the analysis of agricultural prices |
title_fullStr |
A study about the performance of time series models for the analysis of agricultural prices |
title_full_unstemmed |
A study about the performance of time series models for the analysis of agricultural prices |
title_sort |
A study about the performance of time series models for the analysis of agricultural prices |
author |
Oliveira, Sandra Cristina de |
author_facet |
Oliveira, Sandra Cristina de Pereira, Leonardo Matheus Marcondes Hanashiro, Juliana Tiemi Sakaguchi Val, Patricia Carvalho do |
author_role |
author |
author2 |
Pereira, Leonardo Matheus Marcondes Hanashiro, Juliana Tiemi Sakaguchi Val, Patricia Carvalho do |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Oliveira, Sandra Cristina de Pereira, Leonardo Matheus Marcondes Hanashiro, Juliana Tiemi Sakaguchi Val, Patricia Carvalho do |
description |
Agribusiness is one of the most relevant achievements in Brazilian and world economies. Price is an important variable within this sector since economic and market conditions vary over time. Efficient modeling methods are needed to describe better the trends and the characteristics of that variable. The performance of time series techniques of fixed and open models for analysis of agricultural prices will be provided to demonstrate the feasibility of techniques for the generation of results in the wake of economic decisions. Historical time series of monthly average price of cash crops, such as groundnut, sugarcane, banana and orange, received by Brazilian producers, were analyzed for the period between August 1994 and December 2009 and updated by the General Price Index - Internal Availability. Current study shows that exponential smoothing models and Box & Jenkins modeling are viable alternatives for the adjustment of the above price series, each one with its specific characteristics. Keywords: Statistical Models; Agricultural Marketing; Resource Efficiency; Management; Decision Taking. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-09-12 |
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://revista.feb.unesp.br/gepros/article/view/770 10.15675/gepros.v7i3.770 |
url |
https://revista.feb.unesp.br/gepros/article/view/770 |
identifier_str_mv |
10.15675/gepros.v7i3.770 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://revista.feb.unesp.br/gepros/article/view/770/448 https://revista.feb.unesp.br/gepros/article/view/770/1249 https://revista.feb.unesp.br/gepros/article/view/770/1250 https://revista.feb.unesp.br/gepros/article/view/770/1321 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
A Fundacao para o Desenvolvimento de Bauru (FunDeB) |
publisher.none.fl_str_mv |
A Fundacao para o Desenvolvimento de Bauru (FunDeB) |
dc.source.none.fl_str_mv |
Revista Gestão da Produção Operações e Sistemas; n. 3 (2012); 11 1984-2430 reponame:GEPROS. Gestão da Produção. Operações e Sistemas instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
GEPROS. Gestão da Produção. Operações e Sistemas |
collection |
GEPROS. Gestão da Produção. Operações e Sistemas |
repository.name.fl_str_mv |
GEPROS. Gestão da Produção. Operações e Sistemas - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
gepros@feb.unesp.br||abjabbour@feb.unesp.br |
_version_ |
1800215695877734400 |