Advanced Search
MyIDEAS: Login

Forecasting with Unobserved Components Time Series Models

Contents:

Author Info

  • Harvey, Andrew

Abstract

Structural time series models are formulated in terms of components, such as trends, seasonals and cycles, that have a direct interpretation. As well as providing a framework for time series decomposition by signal extraction, they can be used for forecasting and for `nowcasting'. The structural interpretation allows extensions to classes of models that are able to deal with various issues in multivariate series and to cope with non-Gaussian observations and nonlinear models. The statistical treatment is by the state space form and hence data irregularities such as missing observations are easily handled. Continuous time models offer further flexibility in that they can handle irregular spacing. The paper compares the forecasting performance of structural time series models with ARIMA and autoregressive models. Results are presented showing how observations in linear state space models are implicitly weighted in making forecasts and hence how autoregressive and vector error correction representations can be obtained. The use of an auxiliary series in forecasting and nowcasting is discussed. A final section compares stochastic volatility models with GARCH.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.sciencedirect.com/science/article/B7P5J-4JSMTWJ-B/2/c0e9a97c28fc8836339bcdccc4be54b6
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

as in new window

This chapter was published in:

  • G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1, January.
    This item is provided by Elsevier in its series Handbook of Economic Forecasting with number 1-07.

    Handle: RePEc:eee:ecofch:1-07

    Contact details of provider:
    Web page: http://www.elsevier.com/wps/find/bookseriesdescription.cws_home/BS_HE/description

    Related research

    Keywords:

    Find related papers by JEL classification:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2011. "Measuring Output Gap Nowcast Uncertainty," CAMA Working Papers 2011-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, Elsevier.
    3. Katharina Hampel & Marcus Kunz & Norbert Schanne & Ruediger Wapler & Antje Weyh, 2006. "Regional Unemployment Forecasting Using Structural Component Models With Spatial Autocorrelation," ERSA conference papers ersa06p196, European Regional Science Association.
    4. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    5. Steven Clark & T. Coggin, 2009. "Trends, Cycles and Convergence in U.S. Regional House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 264-283, October.
    6. Chen, Yen-Hsiao & Quan, Lianfeng & Liu, Yang, 2013. "An empirical investigation on the temporal properties of China's GDP," China Economic Review, Elsevier, vol. 27(C), pages 69-81.
    7. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    8. El-Shagi, Makram & Giesen, Sebastian, 2013. "Money and inflation: Consequences of the recent monetary policy," Journal of Policy Modeling, Elsevier, vol. 35(4), pages 520-537.
    9. Helmut Lütkepohl, 2010. "Forecasting Aggregated Time Series Variables: A Survey," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2010(2), pages 1-26.
    10. Vipin Arora, 2013. "Comparisons of Chinese and Indian Energy Consumption Forecasting Models," Economics Bulletin, AccessEcon, vol. 33(3), pages 2110-2121.
    11. Öğünç, Fethi & Akdoğan, Kurmaş & Başer, Selen & Chadwick, Meltem Gülenay & Ertuğ, Dilara & Hülagü, Timur & Kösem, Sevim & Özmen, Mustafa Utku & Tekatlı, Necati, 2013. "Short-term inflation forecasting models for Turkey and a forecast combination analysis," Economic Modelling, Elsevier, vol. 33(C), pages 312-325.
    12. Schanne, N. & Wapler, R. & Weyh, A., 2010. "Regional unemployment forecasts with spatial interdependencies," International Journal of Forecasting, Elsevier, vol. 26(4), pages 908-926, October.
    13. Christophe Planas & Alessandro Rossi & Gabriele Fiorentini, 2008. "The marginal likelihood of Structural Time Series Models, with application to the euroareaa nd US NAIRU," Working Paper Series 21-08, The Rimini Centre for Economic Analysis, revised Jan 2008.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:eee:ecofch:1-07. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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