The Canonical Decomposition of Factor Models: Weak Factors are Everywhere
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We derive a novel canonical decomposition of factor models encompassing both the static factor model - where factors are loaded only contemporaneously - and the Generalised Dynamic Factor Model - where factors are loaded with lags. This decomposition features a new term: the weak common component, defined as the difference between the dynamic and static common components. It is driven by (possibly infinitely many) non-pervasive weak factors which belong to the dynamically common space. Through theoretical and empirical examples - both on U.S. macroeconomic indicators and global financial volatilities - we show that, in general, the weak common component shall not be neglected. Furthermore, we show that, by accounting for the presence of weak common components, we are likely to obtain Impulse Response Functions with more plausible shapes than those obtained from purely static approaches. In addition, we provide consistent estimators for all terms of the canonical decomposition and for the weak factors.
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Cited by 1 Pith paper
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A Distributed Lag Approach to the Generalised Dynamic Factor Model
Introduces a lag-based OLS estimator for GDFM using static PCA factors, establishes consistency and asymptotic normality, and applies it to European macro data to identify sizeable weak common components.
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