The paper focuses on the adaptation of local polynomial filters at the end of the sample period. We show that for real time estimation of signals (i.e., exactly at the boundary of the time support) we cannot rely on the automatic adaptation of the local polynomial smoothers, since the direct real time filter turns out to be strongly localized, and thereby yields extremely volatile estimates. As an alternative, we evaluate a general family of asymmetric filters that minimizes the mean square revision error subject to polynomial reproduction constraints; in the case of the Henderson filter it nests the well-known Musgrave's surrogate filters. The class of filters depends on unknown features of the series such as the slope and the curvature of the underlying signal, which can be estimated from the data. Several empirical examples illustrate the effectiveness of our proposal.

Proietti, T., & Luati, A. (2008). Real time estimation in local polynomial regression, with application to trend-cycle analysis. THE ANNALS OF APPLIED STATISTICS, 2(4), 1523-1553 [10.1214/08-AOAS195].

Real time estimation in local polynomial regression, with application to trend-cycle analysis

PROIETTI, TOMMASO;
2008

Abstract

The paper focuses on the adaptation of local polynomial filters at the end of the sample period. We show that for real time estimation of signals (i.e., exactly at the boundary of the time support) we cannot rely on the automatic adaptation of the local polynomial smoothers, since the direct real time filter turns out to be strongly localized, and thereby yields extremely volatile estimates. As an alternative, we evaluate a general family of asymmetric filters that minimizes the mean square revision error subject to polynomial reproduction constraints; in the case of the Henderson filter it nests the well-known Musgrave's surrogate filters. The class of filters depends on unknown features of the series such as the slope and the curvature of the underlying signal, which can be estimated from the data. Several empirical examples illustrate the effectiveness of our proposal.
Pubblicato
Rilevanza internazionale
Articolo
Sì, ma tipo non specificato
Settore SECS-S/03 - Statistica Economica
eng
Con Impact Factor ISI
Henderson filter; trend estimation; Musgrave asymmetric filters
31
Proietti, T., & Luati, A. (2008). Real time estimation in local polynomial regression, with application to trend-cycle analysis. THE ANNALS OF APPLIED STATISTICS, 2(4), 1523-1553 [10.1214/08-AOAS195].
Proietti, T; Luati, A
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2108/41297
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