| Registro completo |
| Provedor de dados: |
Ciência Rural
|
| País: |
Brazil
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| Título: |
Persistence effect determination of variability in forecasting of agricultural and road machinery national production
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| Autores: |
Martins,Tailon
Barreto,Alisson Castro
Coronel,Daniel Arruda
Jacobi,Luciane Flores
Lirio,Valentina Wolff
Souza,Adriano Mendonça
|
| Data: |
2020-01-01
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| Ano: |
2020
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| Palavras-chave: |
Time series
Prediction
Volatility
Agricultural machinery
Road machinery
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| Resumo: |
ABSTRACT: The objective of this research was to forecast the Brazilian national production of agricultural and road machinery in the short term by BOX & JENKINS methodology and determine the persistence effect. Data were obtained at National Association of Automotive Vehicle Manufacturers (ANFAVEA) from January 1960 to October 2019, totaling 718 monthly observations. The Autoregressive Integrated Moving Average (ARIMA) and Autoregressive Conditional Heteroscedasticity (ARCH) methodology were used. The ARIMA (2,1,1)-ARCH (2) model was fitted and persistence of 0.60 was determined, showing that the instability in the series will be for a long period of time.
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| Tipo: |
Info:eu-repo/semantics/article
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| Idioma: |
Inglês
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| Identificador: |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782020000600351
|
| Editor: |
Universidade Federal de Santa Maria
|
| Relação: |
10.1590/0103-8478cr20190631
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| Formato: |
text/html
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| Fonte: |
Ciência Rural v.50 n.6 2020
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| Direitos: |
info:eu-repo/semantics/openAccess
|
