Applications: The Surrogate Henderson Filters in X‐11

Doherty, Mike

doi:10.1111/1467-842x.00187

Cited by 28 publications

(29 citation statements)

References 8 publications

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“…This class generalizes the well-known Musgrave's asymmetric approximation of the Henderson filters [Musgrave (1964), see also Doherty (2001), Gray and Thomson (2002) and Quenneville, Ladiray and Lefrancois (2003)], which is implemented in the seasonal adjustment filter X-11, developed by the US Census Bureau [see Findley et al (1998) and Ladiray and Quenneville (2001)]. The class of filters depends on the properties of the true underlying signal, namely, its level, slope, curvature and so forth, which can be estimated from the data.…”

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confidence: 68%

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Real Time Estimation in Local Polynomial Regression, with Application to Trend-Cycle Analysis

Proietti

Luati

2008

SSRN Journal

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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.

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confidence: 68%

“…As a result, the usual expression for v [i] , the ith element of the vector v, as presented in Doherty (2001), Findley et al (1998) and Ladiray and Quenneville (2001), in terms of the elements of the vector w = {w [j] , j = 1, . .…”

Section: Replacing Into the Expression For V Yieldsmentioning

confidence: 99%

Real Time Estimation in Local Polynomial Regression, with Application to Trend-Cycle Analysis

Proietti

Luati

2008

SSRN Journal

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“…The logic of that method has been uncovered by Doherty (2001), who has referenced the unpublished papers of Musgrave (1964aMusgrave ( , 1964b and of Laniel (1986) (see also Gray and Thomson (2002) for a discourse on the end-of-sample problem).…”

Section: A Classical Econometric Filtermentioning

confidence: 99%

Filters, Waves and Spectra

Pollock

2018

Econometrics

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Econometric analysis requires filtering techniques that are adapted to cater to data sequences that are short and that have strong trends. Whereas the economists have tended to conduct their analyses in the time domain, the engineers have emphasised the frequency domain. This paper places its emphasis in the frequency domain; and it shows how the frequency-domain methods can be adapted to cater to short trended sequences. Working in the frequency domain allows an unrestricted choice to be made of the frequency response of a filter. It also requires that the data should be free of trends. Methods for extracting the trends prior to filtering and for restoring them thereafter are described.

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“…Doherty (2001) has given an account of the origin of these filters and of the theory that lies behind them. Gray and Thomson (2002) have provided an exhaustive treatment of the theory of end-of-sample filters.…”

Section: Now Observe Thatmentioning

confidence: 99%

Statistical Signal Extraction and Filtering: A Partial Survey

Pollock

2009

Handbook of Computational Econometrics

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A wide variety of techniques have been devised for the purpose of extracting the components of econometric data sequences. The traditional approach, which continues to prevail in the central statistical agencies of many countries, has relied upon filters that have been derived with refernce to the principles of actuarial graduation. Latterly, filters that are grounded in the Wiener-Kolmogorov theory of signal extraction have become prominent in academic research. There are several alternative ways of applying the Wiener-Kolmogorov filters to the data.

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Applications: The Surrogate Henderson Filters in X‐11

Cited by 28 publications

References 8 publications

Real Time Estimation in Local Polynomial Regression, with Application to Trend-Cycle Analysis

Real Time Estimation in Local Polynomial Regression, with Application to Trend-Cycle Analysis

Filters, Waves and Spectra

Statistical Signal Extraction and Filtering: A Partial Survey

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