IDEAS home Printed from https://ideas.repec.org/p/zbw/kondp2/141.html
   My bibliography  Save this paper

Überlegungen zum Vergleich von Verfahren der Komponentenzerlegung saisonabhängiger Zeitreihen

Author

Listed:
  • Heiler, Siegfried

Abstract

Zur Analyse saisonbehafteter Zeitreihen stehen heutzutage eine größere Anzahl von unterschiedlichen methodischen Ansätzen und auch von fertigen Software-Systemen zur Verfügung. Für die praktischen Anwendungen spielen nicht nur methodische Gesichtspunkte, sondern teilweise auch rein pragmatische Überlegungen eine Rolle. In diesem Beitrag werden die Grundtypen der vorhandenen Analysesysteme vorgestellt, Anforderungen an ihre Ergebnisse diskutiert und einige Maßzahlen zur Quantifizierung von Beurteilungskriterien vorgestellt. Als wichtiges Resultat bleibt festzuhalten, daß es ein in jeder Hinsicht "bestes" Verfahren nicht geben kann.

Suggested Citation

  • Heiler, Siegfried, 1991. "Überlegungen zum Vergleich von Verfahren der Komponentenzerlegung saisonabhängiger Zeitreihen," Discussion Papers, Series II 141, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
  • Handle: RePEc:zbw:kondp2:141
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/101476/1/756477751.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Grether, D M & Nerlove, M, 1970. "Some Properties of 'Optimal' Seasonal Adjustment," Econometrica, Econometric Society, vol. 38(5), pages 682-703, September.
    2. Schlicht, Ekkehart & Pauly, Ralf, 1982. "Descriptive Seasonal Adjustment by Minimizing Perturbations," Darmstadt Discussion Papers in Economics 16, Darmstadt University of Technology, Department of Law and Economics.
    3. Schlicht, Ekkehart, 1981. "A Seasonal Adjustment Principle and a Seasonal Adjustment Method Derived From this Principle," Munich Reprints in Economics 3374, University of Munich, Department of Economics.
    4. Rainer Metz, 1984. "Zur empirischen Evidenz ≫langer Wellen≪," Kyklos, Wiley Blackwell, vol. 37(2), pages 266-290, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Schlicht, Ekkehart, 1982. "Seasonal Adjustment in a Stochastic Model," Darmstadt Discussion Papers in Economics 25, Darmstadt University of Technology, Department of Law and Economics.
    2. Schlicht, Ekkehart, 2006. "VC - A Method For Estimating Time-Varying Coefficients in Linear Models," Discussion Papers in Economics 61656, University of Munich, Department of Economics.
    3. Jerry A. Hausman & Mark W. Watson, 1983. "Seasonal Adjustment with Measurement Error Present," NBER Working Papers 1133, National Bureau of Economic Research, Inc.
    4. Ehlgen, Jurgen, 1998. "Distortionary effects of the optimal Hodrick-Prescott filter," Economics Letters, Elsevier, vol. 61(3), pages 345-349, December.
    5. Schlicht, Ekkehart, 2004. "Estimating the Smoothing Parameter in the So-Called Hodrick-Prescott Filter," IZA Discussion Papers 1054, Institute of Labor Economics (IZA).
    6. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
    7. Baxa, Jaromír & Horváth, Roman & Vašíček, Bořek, 2013. "Time-varying monetary-policy rules and financial stress: Does financial instability matter for monetary policy?," Journal of Financial Stability, Elsevier, vol. 9(1), pages 117-138.
    8. Steven Yee & Miguel D. Ramirez, 2016. "Purchasing Power Parity: A Time Series Analysis of the U.S. and Mexico, 1995–2007," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(4), pages 409-419, November.
    9. Neil R. Ericsson & David F. Hendry & Hong-Anh Tran, 1993. "Cointegration, seasonality, encompassing, and the demand for money in the United Kingdom," International Finance Discussion Papers 457, Board of Governors of the Federal Reserve System (U.S.).
    10. repec:zbw:bofrdp:2020_006 is not listed on IDEAS
    11. Jaromír Baxa & Roman Horváth & Bořek Vašíček, 2011. "Time Varying Monetary Policy Rules and Financial Stress," Chapters, in: Sylvester Eijffinger & Donato Masciandaro (ed.), Handbook of Central Banking, Financial Regulation and Supervision, chapter 10, Edward Elgar Publishing.
    12. William S. Cleveland & Douglas M. Dunn & Irma J. Terpenning, 1979. "SABL: A Resistant Seasonal Adjustment Procedure with Graphical Methods for Interpretation and Diagnosis," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 201-241, National Bureau of Economic Research, Inc.
    13. Erich Spörndli, 1979. "Konjunkturdiagnose und -prognose in der Schweiz: Die Verwendung quantitativer Indikatoren," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 115(III), pages 323-350, September.
    14. Steven G. Cochrane & Daniel R. Vining Jr., 1988. "Population Migration in the Developed World: Some Further Comments," International Regional Science Review, , vol. 11(3), pages 277-278, December.
    15. Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 374-386, July.
    16. Travis D. Nesmith, 2007. "Rational Seasonality," International Symposia in Economic Theory and Econometrics, in: Functional Structure Inference, pages 227-255, Emerald Group Publishing Limited.
    17. Baxa, Jaromír & Horváth, Roman & Vašíček, Bořek, 2014. "How Does Monetary Policy Change? Evidence On Inflation-Targeting Countries," Macroeconomic Dynamics, Cambridge University Press, vol. 18(3), pages 593-630, April.
    18. Jang Hyung Cho & Robert T. Daigler, 2012. "An unbiased autoregressive conditional intraday seasonal variance filtering process," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 231-247, October.
    19. McElroy, Tucker S. & Politis, Dimitris N., 2014. "Spectral density and spectral distribution inference for long memory time series via fixed-b asymptotics," Journal of Econometrics, Elsevier, vol. 182(1), pages 211-225.
    20. Schlicht, Ekkehart, . "Grundlagen der ökonomischen Analyse," Monographs in Economics, University of Munich, Department of Economics, number 25821, November.
    21. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:kondp2:141. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/fwkonde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.