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Registro Completo |
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Biblioteca(s): |
Embrapa Hortaliças; Embrapa Unidades Centrais. |
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Data corrente: |
03/03/1997 |
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Data da última atualização: |
12/12/2007 |
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Autoria: |
SILVA, J. G. C. da. |
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Afiliação: |
EMBRAPA/DMQ. |
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Título: |
The analysis of cross-sectional time series data. |
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Ano de publicação: |
1975 |
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Fonte/Imprenta: |
1975 . |
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Idioma: |
Inglês |
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Notas: |
Tese (Doutorado)- Graduate Faculty of Norts Carolina State University at Raleigh, Raleigh. |
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Conteúdo: |
This study is concerned with the estimation of linear relationships from cross-sectional time series data. The subject has been extensively discussed in the econometric literature. The diversity of the approaches proposed in the literature sistems both from the different sets of assumptions and the different estimation procedures adopted. Most of the alternative approahes are based on simpler assumptions than the more realistic assumptions used here. The variance component approaches ignore the possibility of serial correlation in the time direction. The seemingly unrelated regressions approaches assume a specific first order autoregressive error structure and treat cross-sectional unit effects as fixed rather than random. Two models are proposed to fit alternative situations. Model A assumes that the linear relationship is affected by a random disturbance with three... |
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Palavras-Chave: |
Analysis; Analysis statistic; Corte transversal; Cross section; Data; Econometric; Econometry; Estatistica experimental; Experimental statistic; Linear model; Mathematical model; Modelo linear; Serie de tempo; Série temporal; Time series; Tyme series analysis. |
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Thesagro: |
Análise Estatística; Dado; Econometria; Modelo Matemático. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01882nam a2200361 a 4500
001 1099197
005 2007-12-12
008 1975 bl uuuu m 00u1 u #d
100 1 $aSILVA, J. G. C. da
245 $aThe analysis of cross-sectional time series data.
260 $a1975 .$c1975
500 $aTese (Doutorado)- Graduate Faculty of Norts Carolina State University at Raleigh, Raleigh.
520 $aThis study is concerned with the estimation of linear relationships from cross-sectional time series data. The subject has been extensively discussed in the econometric literature. The diversity of the approaches proposed in the literature sistems both from the different sets of assumptions and the different estimation procedures adopted. Most of the alternative approahes are based on simpler assumptions than the more realistic assumptions used here. The variance component approaches ignore the possibility of serial correlation in the time direction. The seemingly unrelated regressions approaches assume a specific first order autoregressive error structure and treat cross-sectional unit effects as fixed rather than random. Two models are proposed to fit alternative situations. Model A assumes that the linear relationship is affected by a random disturbance with three...
650 $aAnálise Estatística
650 $aDado
650 $aEconometria
650 $aModelo Matemático
653 $aAnalysis
653 $aAnalysis statistic
653 $aCorte transversal
653 $aCross section
653 $aData
653 $aEconometric
653 $aEconometry
653 $aEstatistica experimental
653 $aExperimental statistic
653 $aLinear model
653 $aMathematical model
653 $aModelo linear
653 $aSerie de tempo
653 $aSérie temporal
653 $aTime series
653 $aTyme series analysis
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Registro original: |
Embrapa Unidades Centrais (AI-SEDE) |
