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Identification of matrix-valued factor models

Author

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  • Ying Lun Cheung

    (Capital University of Economics and Business)

Abstract

The analysis of matrix-valued time series has been popular in recent years. When the dimensions of the matrix observations are large, one can use the matrix-valued factor model to extract information from the data. However, as in standard factor analysis, the common factors and factor loadings are not separately identifiable. This note considers two sets of identification restrictions that help exactly identify the model.

Suggested Citation

  • Ying Lun Cheung, 2024. "Identification of matrix-valued factor models," Economics Bulletin, AccessEcon, vol. 44(2), pages 550-556.
    • Handle: RePEc:ebl:ecbull:eb-23-00461
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Approximate factor models; Matrix-valued time series; Principal components; 2DSVD;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • G1 - Financial Economics - - General Financial Markets

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