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A Spectral EM Algorithm for Dynamic Factor Models

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Abstract

We introduce a frequency domain version of the EM algorithm for general dynamic factor models. We consider both AR and ARMA processes, for which we develop iterative indirect inference procedures analogous to the algorithms in Hannan (1969). Although our proposed procedure allows researchers to estimate such models by maximum likelihood with many series even without good initial values, we recommend switching to a gradient method that uses the EM principle to swiftly compute frequency domain analytical scores near the optimum. We successfully employ our algorithm to construct an index that captures the common movements of US sectoral employment growth rates.

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  • Gabriele Fiorentini & Alessandro Galesi & Enrique Sentana, 2014. "A Spectral EM Algorithm for Dynamic Factor Models," Working Papers wp2014_1411, CEMFI.
  • Handle: RePEc:cmf:wpaper:wp2014_1411
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    Citations

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    Cited by:

    1. 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.
    2. Alonso Fernández, Andrés Modesto & Bastos, Guadalupe & García-Martos, Carolina, 2017. "BIAS correction for dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS 24029, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. repec:eme:aecozz:s0731-905320150000035010 is not listed on IDEAS
    4. Gabriele Fiorentini & Enrique Sentana, 2016. "Neglected serial correlation tests in UCARIMA models," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(1), pages 121-178, March.
    5. Pilar Poncela & Esther Ruiz, 2016. "Small- Versus Big-Data Factor Extraction in Dynamic Factor Models: An Empirical Assessment," Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 401-434 Emerald Publishing Ltd.

    More about this item

    Keywords

    Indirect inference; Kalman filter; sectoral employment; spectral maximum likelihood; Wiener-Kolmogorov filter.;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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