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A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models

Author

Listed:
  • Catherine Doz

    (Paris School of Economics and University Paris 1 Panthéon-Sorbonne)

  • Domenico Giannone

    (Université libre de Bruxelles, ECARES, and CEPR)

  • Lucrezia Reichlin

    (London Business School and CEPR)

Abstract

Is maximum likelihood suitable for factor models in large cross-sections of time series? We answer this question from both an asymptotic and an empirical perspective. We show that estimates of the common factors based on maximum likelihood are consistent for the size of the cross-section (n) and the sample size (T), going to infinity along any path, and that maximum likelihood is viable for n large. The estimator is robust to misspecification of cross-sectional and time series correlation of the idiosyncratic components. In practice, the estimator can be easily implemented using the Kalman smoother and the EM algorithm as in traditional factor analysis. © 2012 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
  • Handle: RePEc:tpr:restat:v:94:y:2012:i:4:p:1014-1024
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    as
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    More about this item

    Keywords

    factor models; large cross-sections; quasi-maximum likelihood;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • 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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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    1. A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models (REStat 2012) in ReplicationWiki

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