• DocumentCode
    1664556
  • Title

    On the consistency of identification by dynamic factor models

  • Author

    Heij, C. ; Scherrer, W.

  • Author_Institution
    Tinbergen Inst., Erasmus Univ., Rotterdam, Netherlands
  • Volume
    3
  • fYear
    1994
  • Firstpage
    2880
  • Abstract
    In this paper we present a new type of dynamic factor model. Here the observed process is decomposed into a factor part and a noise part. The factor part contains less freedom than the original process, in the sense that it satisfies linear system restrictions. Stated otherwise, the observed stochastic process is modelled by a deterministic behaviour. We pay special attention to consistency properties for this type of model
  • Keywords
    identification; least squares approximations; linear systems; stochastic processes; consistency; dynamic factor models; identification; least squares; linear system; stochastic process; Econometrics; Economic forecasting; Least squares methods; Linear systems; Operations research; Predictive models; Psychometric testing; Statistical analysis; Stochastic processes; System identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
  • Conference_Location
    Lake Buena Vista, FL
  • Print_ISBN
    0-7803-1968-0
  • Type

    conf

  • DOI
    10.1109/CDC.1994.411360
  • Filename
    411360