A robust data-driven version of the Berlin Method

Feng, Yuanhua; Heiler, Siegfried

A robust data-driven version of the Berlin Method

Dateien

497_1.pdfGröße: 308.08 KBDownloads: 92

Datum

2000

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Wirtschaftswissenschaften

Publikationstyp

Working Paper/Technical Report

Publikationsstatus

Published

Zusammenfassung

In this paper a robust data-driven procedure for decomposing seasonal time series based on a generalized Berlin Method (BV, Berliner Verfahren) as proposed by Heiler and Michels (1994) is discussed. The basic robust algorithm used here is an adaptation of the LOWESS (LOcally Weighted Scatterplot Smoothing) procedure (Cleveland, 1979). For selecting the optimal bandwidth the simple double smoothing rule (Heiler and Feng, 1999) is used. The optimal order of the local polynomial is selected with a BIC criterion. The proposed procedure is applied to the macroeconomic time series used in the recent empirical studies carried out by the German Federal Statistical Office (Speth, 1994 and Höpfner, 1998).

Fachgebiet (DDC)

330 Wirtschaft

Schlagwörter

time series decomposition, robust estimation, bandwidth selection

Zitieren

ISO 690

FENG, Yuanhua, Siegfried HEILER, 2000. A robust data-driven version of the Berlin Method

BibTex

@techreport{Feng2000robus-11817,
  year={2000},
  series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie},
  title={A robust data-driven version of the Berlin Method},
  number={2000/15},
  author={Feng, Yuanhua and Heiler, Siegfried}
}

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