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Identification of causal factor models of stationary time series


  • Chris Heaton
  • Victor Solo


We consider identification of a class of dynamic factor model. We show that identification holds under reasonably general conditions. The results apply to many of the dynamic factor models that have appeared in the literature and to many worthwhile generalizations of those models. Copyright Royal Economic Socciety 2004

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  • Chris Heaton & Victor Solo, 2004. "Identification of causal factor models of stationary time series," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 618-627, December.
  • Handle: RePEc:ect:emjrnl:v:7:y:2004:i:2:p:618-627

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    References listed on IDEAS

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    Cited by:

    1. Heaton, Chris & Oslington, Paul, 2010. "Micro vs macro explanations of post-war US unemployment movements," Economics Letters, Elsevier, vol. 106(2), pages 87-91, February.
    2. Gabriele Fiorentini & Alessandro Galesi & Enrique Sentana, 2016. "Fast ML Estimation of Dynamic Bifactor Models: An Application to European Inflation," Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 215-282 Emerald Publishing Ltd.
    3. repec:eee:insuma:v:75:y:2017:i:c:p:117-125 is not listed on IDEAS
    4. McCausland, William J. & Miller, Shirley & Pelletier, Denis, 2011. "Simulation smoothing for state-space models: A computational efficiency analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 199-212, January.
    5. Gabriele Fiorentini & Alessandro Galesi & Enrique Sentana, 2014. "A Spectral EM Algorithm for Dynamic Factor Models," Working Papers wp2014_1411, CEMFI.
    6. Gabriele Fiorentini & Enrique Sentana, 2013. "Dynamic Specification Tests for Dynamic Factor Models," Working Papers wp2013_1306, CEMFI.
    7. Bai, Jushan & Ng, Serena, 2013. "Principal components estimation and identification of static factors," Journal of Econometrics, Elsevier, vol. 176(1), pages 18-29.

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