![]() The common component is assumed to be driven by a few common factors, thereby reducing the dimension of the system. The basic idea is to separate a possibly large number of observable time series into two independent and unobservable, yet estimable, components: a ‘common component’ that captures the main bulk of co-movement between the observable series, and an ‘idiosyncratic component’ that captures any remaining individual movement. ![]() ![]() Dynamic factor models are used in data-rich environments.
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