Time series factor analysis model: Factors generated by autoregression and moving average process

Hideki Toyoda*

*この研究の対応する著者

研究成果: Article査読

抄録

The dynamic factor analysis model (Molenaar, 1985) which is one of the generalizations of the p-technique factor analysis model, can explain the lagged covariance structure among observed variables. Hershberger, Corneal, and Molenaar (1994) showed that the dynamic factor model can be easily evaluated within a structural equation modeling (SEM) program such as LISREL. In this paper, an alternative time series model containing the latent factors which are generated by the autoregression and moving average (ARMA) process is proposed. This model, which has been named the time series factor analysis model, can also be easily evaluated with a SEM program. The application of this model to the leading index, the coincident index and the lagging index of the Japanese economy revealed a latent common factor series generated by considerable autoregression.

本文言語English
ページ(範囲)1-14
ページ数14
ジャーナルSociological Theory and Methods
12
1
出版ステータスPublished - 1997 12 1
外部発表はい

ASJC Scopus subject areas

  • 社会科学(その他)
  • 社会学および政治科学

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