RT Journal Article
T1 TF-MIDAS: a transfer function based mixed-frequency model
A1 Bonino-Gayoso, Nicolás
A1 García Hiernaux, Alfredo
AB This paper tackles the mixed-frequency modeling problem from a new perspective. Instead of drawing upon the common distributed lag polynomial model, we use a transfer function representation to develop a new type of models, named TF-MIDAS. We derive the theoretical TF-MIDAS implied by the high-frequency VARMA family models for two common aggregation schemes, flow and stock. This exact correspondence leads to potential gains in terms of nowcasting and forecasting performance against the current alternatives. The estimation of the model proposed is also addressed via its state space equivalent form. A Monte Carlo simulation exercise confirms that TF-MIDAS beats U-MIDAS models (its natural competitor) in terms of out-of-sample nowcasting performance for several data generating high-frequency processes.
YR 2020
FD 2020
LK https://hdl.handle.net/20.500.14352/6355
UL https://hdl.handle.net/20.500.14352/6355
LA eng
DS Docta Complutense
RD 28 abr 2024