Philipp Gersing:
A Distributed Lag Approach to the Generalised Dynamic Factor Model

We propose a new estimator for the Generalised Dynamic Factor Model (GDFM) that simplifies estimation by avoiding frequency-domain methods. Our key theoretical insight shows that the dynamic common component can be represented by a finite number of lags of contemporaneously pervasive factors under general conditions. This result reduces GDFM estimation to a simple OLS regression of observed variables on estimated factors and their lags, with factors obtained via static principal components. The approach naturally accommodates weak (non-pervasive) factors within the dynamic common space, addressing an important limitation of existing methods. We establish consistency and asymptotic normality for both the dynamic and weak common components. An application to a large European macroeconomic dataset demonstrates strong empirical performance and uncovers a sizeable weak common component - particularly in sentiment indicators and several other variables - revealing dynamics that standard methods overlook.