Locally Stationary Factor Models: Identification And Nonparametric Estimation

  title={Locally Stationary Factor Models: Identification And Nonparametric Estimation},
  author={G. Motta and Christian M. Hafner and Rainer von Sachs},
In this paper we propose a new approximate factor model for large cross-section and time dimensions. Factor loadings are assumed to be smooth functions of time, which allows to consider the model as locally stationary while permitting empirically observed time-varying second moments. Factor loadings are estimated by the eigenvectors of a nonparametrically estimated covariance matrix. As is well-known in the stationary case, this principal components estimator is consistent in approximate factor… CONTINUE READING

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