This paper sets out the theoretical foundations for continuous-time signal extraction in econometrics.
Continuous-time modeling gives an effective strategy for treating stock and flow data,
irregularly spaced data, and changing frequency of observation.
We rigorously derive the optimal continuous-lag filter when the signal component is nonstationary, and provide several illustrations, including a new class of continuous-lag Butterworth filters for trend and cycle estimation.
signal extraction, continuous time processes, linear filtering, Hodrick-Prescott Filter, Band-Pass Filter
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