CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
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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Cerne (Online) |
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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 |
_version_ |
1799874940576464896 |