RT Report
T1 An ARMA representation of unobserved component models under generalized random walk specifications: new algorithms and examples
A1 Bujosa Brun, Marcos
A1 García Ferrer, Antonio
A1 Young, Peter C.
AB Among the alternative Unobserved Components formulations within the stochastic state space setting, the Dynamic Harmonic Regression (DHR) has proved particularly useful for adaptive seasonal adjustmentsignal extraction, forecasting and back-casting of time series.Here, we show first how to obtain ARMA  representations for the Dynamic Harmonic Regression (DHR) components under several random walk specifications. Later, we uses these theoretical results to derive an alternative algorithm based on the frequency domain for the identification and estimation of DHR models. The main advantages of this algorithm are linearity, fast computing, avoidance of some numerical issues, and automatic identification of the DHR model. To compareit with other alternatives, empirical applications are provided.
PB Instituto Complutense de Análisis Económico. Universidad Complutense de Madrid
YR 2002
FD 2002-03
LK https://hdl.handle.net/20.500.14352/64494
UL https://hdl.handle.net/20.500.14352/64494
LA eng
DS Docta Complutense
RD 4 abr 2025