CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL

Detalhes bibliográficos
Autor(a) principal: Rezende, José Luiz Pereira de
Data de Publicação: 2015
Outros Autores: Junior, Luiz Moreira Coelho, Oliveira, Antônio Donizette de, Sáfadi, Thelma
Tipo de documento: Artigo
Idioma: por
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/441
Resumo: The State of Minas Gerais is the largest producer and consumer of charcoal, that is used as term-reducer of iron ore, for producing pig iron. This study analyzed the time series of charcoal prices in four regions of Minas Gerais State. For the analysis of the price series, the SARIMA model was used, for finding a model that better forecasts prices for the four studied areas. The most appropriate models were chosen using graphical analyses of the standardized residues, autocorrelation functions and partial autocorrelations, stochastic tests and criteria of evaluation of the order of the model. It concluded that: the differences of charcoal prices occur, basically, due to the geographical location; the analyses of domain of the time and domain of the frequency showed that there is difference in the price series of the four studied areas; the areas of Sete Lagoas and Belo Horizonte, giving that they are closely located, possess similar prices and they generated similar model; the studied areas presented differentiated models and supplied good adjustments for the observed series. The best models were SARIMA (2,1,1)x(1,0,0)12, for Belo Horizonte; SARIMA (2,0,0)x(2,1,2)12, for Divinópolis; SARIMA (2,1,1)x(1,0,0)12, for Sete Lagoas and SARIMA (1,1,1)x(1,1,1)12, for Vertentes. Such models presented in a parsimonious way, containing a small number of parameters. All models SARIMA (p,d,q) (P,D,Q)s, for the four studied areas, presented white noise and supplied adequate price forecast.
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spelling CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZILcharcoalforestry economytime seriestendencyseasonalityThe State of Minas Gerais is the largest producer and consumer of charcoal, that is used as term-reducer of iron ore, for producing pig iron. This study analyzed the time series of charcoal prices in four regions of Minas Gerais State. For the analysis of the price series, the SARIMA model was used, for finding a model that better forecasts prices for the four studied areas. The most appropriate models were chosen using graphical analyses of the standardized residues, autocorrelation functions and partial autocorrelations, stochastic tests and criteria of evaluation of the order of the model. It concluded that: the differences of charcoal prices occur, basically, due to the geographical location; the analyses of domain of the time and domain of the frequency showed that there is difference in the price series of the four studied areas; the areas of Sete Lagoas and Belo Horizonte, giving that they are closely located, possess similar prices and they generated similar model; the studied areas presented differentiated models and supplied good adjustments for the observed series. The best models were SARIMA (2,1,1)x(1,0,0)12, for Belo Horizonte; SARIMA (2,0,0)x(2,1,2)12, for Divinópolis; SARIMA (2,1,1)x(1,0,0)12, for Sete Lagoas and SARIMA (1,1,1)x(1,1,1)12, for Vertentes. Such models presented in a parsimonious way, containing a small number of parameters. All models SARIMA (p,d,q) (P,D,Q)s, for the four studied areas, presented white noise and supplied adequate price forecast.CERNECERNE2015-09-25info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/441CERNE; Vol. 11 No. 3 (2005); 237-252CERNE; v. 11 n. 3 (2005); 237-2522317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAporhttps://cerne.ufla.br/site/index.php/CERNE/article/view/441/380Copyright (c) 2015 CERNEinfo:eu-repo/semantics/openAccessRezende, José Luiz Pereira deJunior, Luiz Moreira CoelhoOliveira, Antônio Donizette deSáfadi, Thelma2015-10-22T09:54:41Zoai:cerne.ufla.br:article/441Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:53:51.441784Cerne (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL
title CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL
spellingShingle CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL
Rezende, José Luiz Pereira de
charcoal
forestry economy
time series
tendency
seasonality
title_short CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL
title_full CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL
title_fullStr CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL
title_full_unstemmed CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL
title_sort CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL
author Rezende, José Luiz Pereira de
author_facet Rezende, José Luiz Pereira de
Junior, Luiz Moreira Coelho
Oliveira, Antônio Donizette de
Sáfadi, Thelma
author_role author
author2 Junior, Luiz Moreira Coelho
Oliveira, Antônio Donizette de
Sáfadi, Thelma
author2_role author
author
author
dc.contributor.author.fl_str_mv Rezende, José Luiz Pereira de
Junior, Luiz Moreira Coelho
Oliveira, Antônio Donizette de
Sáfadi, Thelma
dc.subject.por.fl_str_mv charcoal
forestry economy
time series
tendency
seasonality
topic charcoal
forestry economy
time series
tendency
seasonality
description The State of Minas Gerais is the largest producer and consumer of charcoal, that is used as term-reducer of iron ore, for producing pig iron. This study analyzed the time series of charcoal prices in four regions of Minas Gerais State. For the analysis of the price series, the SARIMA model was used, for finding a model that better forecasts prices for the four studied areas. The most appropriate models were chosen using graphical analyses of the standardized residues, autocorrelation functions and partial autocorrelations, stochastic tests and criteria of evaluation of the order of the model. It concluded that: the differences of charcoal prices occur, basically, due to the geographical location; the analyses of domain of the time and domain of the frequency showed that there is difference in the price series of the four studied areas; the areas of Sete Lagoas and Belo Horizonte, giving that they are closely located, possess similar prices and they generated similar model; the studied areas presented differentiated models and supplied good adjustments for the observed series. The best models were SARIMA (2,1,1)x(1,0,0)12, for Belo Horizonte; SARIMA (2,0,0)x(2,1,2)12, for Divinópolis; SARIMA (2,1,1)x(1,0,0)12, for Sete Lagoas and SARIMA (1,1,1)x(1,1,1)12, for Vertentes. Such models presented in a parsimonious way, containing a small number of parameters. All models SARIMA (p,d,q) (P,D,Q)s, for the four studied areas, presented white noise and supplied adequate price forecast.
publishDate 2015
dc.date.none.fl_str_mv 2015-09-25
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://cerne.ufla.br/site/index.php/CERNE/article/view/441
url https://cerne.ufla.br/site/index.php/CERNE/article/view/441
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/441/380
dc.rights.driver.fl_str_mv Copyright (c) 2015 CERNE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 CERNE
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv CERNE
CERNE
publisher.none.fl_str_mv CERNE
CERNE
dc.source.none.fl_str_mv CERNE; Vol. 11 No. 3 (2005); 237-252
CERNE; v. 11 n. 3 (2005); 237-252
2317-6342
0104-7760
reponame:Cerne (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Cerne (Online)
collection Cerne (Online)
repository.name.fl_str_mv Cerne (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv cerne@dcf.ufla.br||cerne@dcf.ufla.br
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