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Consistent Noisy Independent Component Analysis

Author

Listed:
  • Stéphane Bonhomme

    (CEMFI - Centre de Estudios monetarios y financierios - Banco de España)

  • Jean-Marc Robin

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

We study linear factor models under the assumptions that factors are mutually independent and independent of errors, and errors can be correlated to some extent. Under the factor non-Gaussianity, second-to-fourth-order moments are shown to yield full identification of the matrix of factor loadings. We develop a simple algorithm to estimate the matrix of factor loadings from these moments. We run Monte Carlo simulations and apply our methodology to data on cognitive test scores, and financial data on stock returns.

Suggested Citation

  • Stéphane Bonhomme & Jean-Marc Robin, 2009. "Consistent Noisy Independent Component Analysis," PSE-Ecole d'économie de Paris (Postprint) hal-00642732, HAL.
    • Handle: RePEc:hal:pseptp:hal-00642732
    DOI: 10.1016/j.jeconom.2008.12.019
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    References listed on IDEAS

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    More about this item

    Keywords

    Independent Component Analysis; Factor Analysis; High-order moments; Noisy ICA;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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