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Tests for group-specific heterogeneity in high-dimensional factor models

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  • Djogbenou, Antoine
  • Sufana, Razvan

Abstract

Standard high-dimensional factor models assume that the comovements in a large set of variables could be modeled using a small number of latent factors that affect all variables. In many relevant applications in economics and finance, heterogeneous comovements specific to some known groups of variables naturally arise, and reflect distinct cyclical movements within those groups. This paper develops two new statistical tests that can be used to investigate whether there is evidence supporting group-specific heterogeneity in the data. The paper also proposes and proves the validity of a permutation approach for approximating the asymptotic distributions of the two test statistics.

Suggested Citation

  • Djogbenou, Antoine & Sufana, Razvan, 2024. "Tests for group-specific heterogeneity in high-dimensional factor models," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:jmvana:v:199:y:2024:i:c:s0047259x23000799
    DOI: 10.1016/j.jmva.2023.105233
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