IDEAS home Printed from https://ideas.repec.org/a/jss/jstsof/v041i03.html
   My bibliography  Save this article

State Space Methods in Ox/SsfPack

Author

Listed:
  • Pelagatti, Matteo M.

Abstract

The use of state space models and their inference is illustrated using the package SsfPack for Ox. After a rather long introduction that explains the use of SsfPack and many of its functions, four case-studies illustrate the practical implementation of the software to real world problems through short sample programs. The first case consists in the analysis of the well-known (at least to time series analysis experts) Nile data with a local level model. The other case-studies deal with ARIMA and RegARIMA models applied to the (also well-known) Airline time series, structural time series models applied to the Italian industrial production index and stochastic volatility models applied to the FTSE100 index. In all applications inference on the model (hyper-) parameters is carried out by maximum likelihood, but in one case (stochastic volatility) also an MCMC-based approach is illustrated. Cubic splines are covered in a very short example as well.

Suggested Citation

  • Pelagatti, Matteo M., 2011. "State Space Methods in Ox/SsfPack," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i03).
    • Handle: RePEc:jss:jstsof:v:041:i03
    DOI: http://hdl.handle.net/10.18637/jss.v041.i03
    as

    Download full text from publisher

    File URL: https://www.jstatsoft.org/index.php/jss/article/view/v041i03/v41i03.pdf
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v041i03/v41i03-replication.zip
    Download Restriction: no
    File URL: https://libkey.io/http://hdl.handle.net/10.18637/jss.v041.i03?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Atkinson, A. C. & Koopman, S. J. & Shephard, N., 1997. "Detecting shocks: Outliers and breaks in time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 387-422, October.
    2. Commandeur, Jacques J.F. & Koopman, Siem Jan, 2007. "An Introduction to State Space Time Series Analysis," OUP Catalogue, Oxford University Press, number 9780199228874.
    3. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Allin Cottrell & Riccardo (Jack) Lucchetti & Matteo Pelagatti, 2016. "Measures of variance for smoothed disturbances in linear state-space models: a clarification," gretl working papers 3, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    2. T. R. Santos, 2018. "A Bayesian GED-Gamma stochastic volatility model for return data: a marginal likelihood approach," Papers 1809.01489, arXiv.org.

    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. Xiaoshan Chen & Terence Mills, 2012. "Measuring the Euro area output gap using a multivariate unobserved components model containing phase shifts," Empirical Economics, Springer, vol. 43(2), pages 671-692, October.
    2. Martyna Marczak & Thomas Beissinger, 2013. "Real wages and the business cycle in Germany," Empirical Economics, Springer, vol. 44(2), pages 469-490, April.
    3. Vujić, Sunčica & Commandeur, Jacques J.F. & Koopman, Siem Jan, 2016. "Intervention time series analysis of crime rates: The case of sentence reform in Virginia," Economic Modelling, Elsevier, vol. 57(C), pages 311-323.
    4. Suncica Vujic & Jacques Commandeur & Siem Jan Koopman, 2012. "Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia," Tinbergen Institute Discussion Papers 12-007/4, Tinbergen Institute.
    5. Donadelli, M. & Paradiso, A. & Livieri, G., 2019. "Adding cycles into the neoclassical growth model," Economic Modelling, Elsevier, vol. 78(C), pages 162-171.
    6. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    7. repec:jss:jstsof:41:i03 is not listed on IDEAS
    8. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    9. Alexander Vlasenko & Nataliia Vlasenko & Olena Vynokurova & Dmytro Peleshko, 2018. "A Novel Neuro-Fuzzy Model for Multivariate Time-Series Prediction," Data, MDPI, vol. 3(4), pages 1-14, December.
    10. Mr. Thomas Helbling & Mr. Tamim Bayoumi, 2003. "Are they All in the Same Boat? the 2000-2001 Growth Slowdown and the G-7 Business Cycle Linkages," IMF Working Papers 2003/046, International Monetary Fund.
    11. David Shepherd & Robert Dixon, 2008. "The Cyclical Dynamics and Volatility of Australian Output and Employment," The Economic Record, The Economic Society of Australia, vol. 84(264), pages 34-49, March.
    12. Charles Ka Yui Leung & Joe Cho Yiu Ng & Edward Tang, 2020. "Why is the Hong Kong Housing Market Unaffordable? Some Stylized Facts and Estimations," Globalization Institute Working Papers 380, Federal Reserve Bank of Dallas.
    13. Marczak, Martyna & Proietti, Tommaso, 2016. "Outlier detection in structural time series models: The indicator saturation approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 180-202.
    14. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 9473, Victoria University of Wellington, School of Economics and Finance.
    15. Barunik, Jozef & Krehlik, Tomas, 2016. "Measuring the frequency dynamics of financial and macroeconomic connectedness," FinMaP-Working Papers 54, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    16. Siem Jan Koopman & Joao Valle e Azevedo, 2003. "Measuring Synchronisation and Convergence of Business Cycles," Tinbergen Institute Discussion Papers 03-052/4, Tinbergen Institute.
    17. Kapetanios, G. & Tzavalis, E., 2010. "Modeling structural breaks in economic relationships using large shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 417-436, March.
    18. Omar H. M. N. Bashar, 2015. "The Trickle‐down Effect of the Mining Boom in Australia: Fact or Myth?," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 94-108, June.
    19. Chen, Xiaoshan & Mills, Terence C., 2009. "Evaluating growth cycle synchronisation in the EU," Economic Modelling, Elsevier, vol. 26(2), pages 342-351, March.
    20. Amélie Charles & Olivier Darné & Laurent Ferrara, 2018. "Does The Great Recession Imply The End Of The Great Moderation? International Evidence," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 745-760, April.
    21. Martin Larch & João Nogueira Martins, 2007. "Fiscal indicators - Proceedings of the the Directorate-General for Economic and Financial Affairs Workshop held on 22 September 2006 in Brussels," European Economy - Economic Papers 2008 - 2015 297, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

    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:jss:jstsof:v:041:i03. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.jstatsoft.org/ .

    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.