A two-step estimator for large approximate dynamic factor models based on Kalman filtering ∗

  title={A two-step estimator for large approximate dynamic factor models based on Kalman filtering ∗},
  author={Catherine Doz and Domenico Giannone},
This paper shows consistency of a two step estimation of the factors in a dynamic approximate factor model when the panel of time series is large (n large). In the first step, the parameters of the model are first estimated from an OLS on principal components. In the second step, the factors are estimated via the Kalman smoother. This projection allows to consider dynamics in the factors and in the idiosyncratic component, and heteroscedasticity in the idiosyncratic variance. The analysis… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 23 references

A dynamic index model for large cross-section

  • Danny Quah, Thomas J. Sargent
  • 1992
Highly Influential
5 Excerpts

Arbitrage, factor structure and meanvariance analysis in large asset

  • Gari Chamberlain, Michael Rothschild
  • markets. Econometrica,
  • 1983
Highly Influential
5 Excerpts

Maximum likelihood estimation from incomplete data

  • A. N. Laird Dempster, D. Rubin
  • Journal of the Royal Statistical Society,
  • 1977
Highly Influential
5 Excerpts

A maximum likelihood approach for large approximate dynamic factor models

  • Catherine Doz, Domenico Giannone, Lucrezia Reichlin
  • Unpublished manuscript,
  • 2005
5 Excerpts

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