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| Registros recuperados : 6 | |
| 5. |  | NICHOLSON, C. F.; THORNTON, P. K.; MOHAMMED, L.; MUINGA, R. W.; MWAMACHI, D. M.; ELBASHA, E. H.; STAAL, S. J.; THORPE, W. Smallholder dairy technology in Coastal Kenya: an adoption and impact study. Nairobi: ILRI, 1999. 59p. (ILRI. Impact Assessment Series, 5).| Biblioteca(s): Embrapa Pantanal. |
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| 6. | | RUEDA, B. L.; BLAKE, R. W.; NICHOLSON, C. F.; FOX, D. G.; TEDESCHI, L. O.; PELL, A. N.; FERNANDES, E. C. M.; VALENTIM, J. F.; CARNEIRO JUNIOR, J. M. Production and economic potentials of cattle in pasture-based systems of the Western Amazon region of Brazil. Journal of Animal Science, Champaign, v. 81, n. 12, p. 2923-2937, 2003.| Biblioteca(s): Embrapa Acre. |
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| Registros recuperados : 6 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
17/07/2023 |
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Data da última atualização: |
17/07/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
A - 2 |
|
Autoria: |
SIMÕES, A. R. P.; NICHOLSON, C. F.; CARVALHO, G. R. |
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Afiliação: |
ANDRE ROZEMBERG PEIXOTO SIMÕES, Universidade Estadual de Mato Grosso do Sul; CHARLES FREDERICK NICHOLSON, University of Wisconsin; GLAUCO RODRIGUES CARVALHO, CNPGL. |
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Título: |
Components of farm milk price behavior in Brazil from 2005 to 2020. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Revista Brasileira de Zootecnia, v. 52, e20220116, 2023. |
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DOI: |
https://doi.org/10.37496/rbz5220220116 |
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Idioma: |
Inglês |
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Conteúdo: |
The objective of this study was to assess behavior patterns in Brazilian farm milk prices. We employed a structural time series techniques model, the Unobserved Component Model (UCM), which is part of the family of State Space models, to assess the trend, seasonality, cyclical behavior, and impacts of exogenous regressors on aggregated farm milk price behavior in Brazil from January 2005 to December 2019. We tested five alternative models with different regressors using the monthly national average prices of milk paid to farmers. The fit of the models was assessed with Akaike information criterion and Bayesian information criterion. Predictions were assessed by the root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). All models demonstrated a high degree of accuracy. Trends, seasonality, and two cycles were statistically significant, with the trend and long-period cycle contributing the most to price variation. Exogenous factors such as feed cost and international dairy product prices also had significant positive effects on the level of Brazil?s farm milk prices. All models demonstrated a high degree of accuracy, which may indicate their usefulness for price forecasting and policy formulation. |
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Thesagro: |
Laticínio; Leite; Preço; Produto Derivado do Leite. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1154974/1/Components-of-farm-milk-price-behaviour-Brazil-from-2005-to-2020.pdf
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Marc: |
LEADER 01875naa a2200205 a 4500
001 2154974
005 2023-07-17
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.37496/rbz5220220116$2DOI
100 1 $aSIMÕES, A. R. P.
245 $aComponents of farm milk price behavior in Brazil from 2005 to 2020.$h[electronic resource]
260 $c2023
520 $aThe objective of this study was to assess behavior patterns in Brazilian farm milk prices. We employed a structural time series techniques model, the Unobserved Component Model (UCM), which is part of the family of State Space models, to assess the trend, seasonality, cyclical behavior, and impacts of exogenous regressors on aggregated farm milk price behavior in Brazil from January 2005 to December 2019. We tested five alternative models with different regressors using the monthly national average prices of milk paid to farmers. The fit of the models was assessed with Akaike information criterion and Bayesian information criterion. Predictions were assessed by the root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). All models demonstrated a high degree of accuracy. Trends, seasonality, and two cycles were statistically significant, with the trend and long-period cycle contributing the most to price variation. Exogenous factors such as feed cost and international dairy product prices also had significant positive effects on the level of Brazil?s farm milk prices. All models demonstrated a high degree of accuracy, which may indicate their usefulness for price forecasting and policy formulation.
650 $aLaticínio
650 $aLeite
650 $aPreço
650 $aProduto Derivado do Leite
700 1 $aNICHOLSON, C. F.
700 1 $aCARVALHO, G. R.
773 $tRevista Brasileira de Zootecnia$gv. 52, e20220116, 2023.
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Embrapa Gado de Leite (CNPGL) |
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