The empirical distribution of sequential LS factors in Multi-level Dynamic Factor Models

Gian Pietro Enzo Bellocca, Ignacio Garrón Vedia, Carlos Rodriguez Caballero and Esther Ruiz Ortega

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: The research question we answer in this paper is whether the asymptotic distribution derived by Bai (2003) for Principal Components (PC) factors in dynamic factor models (DFMs) can approximate the empirical distribution of the sequential Least Squares (SLS) estimator of global and group-specific factors in multi-level dynamic factor models (ML-DFMs). Monte Carlo experiments confirm that under general forms of the idiosyncratic covariance matrix, the finite-sample distribution of SLS global and group-specific factors can be well approximated using the asymptotic distribution of PC factors. We also analyse the performance of alternative estimators of the asymptotic mean squared error (MSE) of the SLS factors and show that the MSE estimator that allows for idiosyncratic cross-sectional correlation and accounts for estimation uncertainty of factor loadings is best.

Keywords: Multi-Level; Dynamic; Factors; Models; Principal; Components; Sequential; Least; Squares; Subsampling (search for similar items in EconPapers)
JEL-codes: C13 C32 C55 F47 (search for similar items in EconPapers)
Date: 2026-02-16
New Economics Papers: this item is included in nep-ecm and nep-ets
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:49336

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