[Submitted on 28 Oct 2024 (v1), last revised 6 Jun 2026 (this version, v3)]

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Abstract:We propose a simple estimator for the dynamic decomposition of the Generalized Dynamic Factor Model that avoids frequency-domain methods. First, we show that it is a reasonable approximation to assume that the dynamic common component of the Generalized Dynamic Factor Model admits a representation in terms of current and lagged statically pervasive factors. Then, assuming finite lag order, this simplification reduces estimation to a regression of the observed variables on estimated factors and their lags, where the factors are extracted via static principal components. The proposed approach naturally accommodates weak, non-pervasive factors within the dynamic common space. We establish consistency and asymptotic normality for both the dynamic and weak common components under a new asymptotic framework that allows for such weak factors. In an application to three high-dimensional time series panels of European macroeconomic data we detect a sizeable weak common component share in several key macroeconomic indicators.

Submission history

From: Philipp Gersing [view email]
[v1] Mon, 28 Oct 2024 10:07:06 UTC (108 KB)
[v2] Wed, 6 May 2026 20:23:53 UTC (79 KB)
[v3] Sat, 6 Jun 2026 16:43:28 UTC (78 KB)

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