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Investigating Finite Sample Properties of Estimators for Approximate Factor Models When N Is Small

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  • Shinya Tanaka
  • Eiji Kurozumi

Abstract

This paper examines the finite sample properties of estimators for approximate factor models when N is small via simulation study. Although the "rule-of-thumb" for factor models does not support using approximate factor models when N is small, we find that the principal component analysis estimator and quasi-maximum likelihood estimator proposed by Doz et al. (2008) perform very well even in this case. Our findings provide an opportunity for applying approximate factor models to low-dimensional data, which was thought to have been inappropriate for a long time.

Suggested Citation

  • Shinya Tanaka & Eiji Kurozumi, 2010. "Investigating Finite Sample Properties of Estimators for Approximate Factor Models When N Is Small," Global COE Hi-Stat Discussion Paper Series gd10-156, Institute of Economic Research, Hitotsubashi University.
    • Handle: RePEc:hst:ghsdps:gd10-156
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    2. Juraj Hucek & Alexander Karsay & Marian Vavra, 2015. "Short-term Forecasting of Real GDP Using Monthly Data," Working and Discussion Papers OP 1/2015, Research Department, National Bank of Slovakia.

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    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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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