IDEAS home Printed from https://ideas.repec.org/a/spr/aistmt/v65y2013i5p959-992.html
   My bibliography  Save this article

Estimation in threshold autoregressive models with correlated innovations

Author

Listed:
  • P. Chigansky
  • Yu. Kutoyants

Abstract

Large sample statistical analysis of threshold autoregressive models is usually based on the assumption that the underlying driving noise is uncorrelated. In this paper, we consider a model, driven by Gaussian noise with geometric correlation tail and derive a complete characterization of the asymptotic distribution for the Bayes estimator of the threshold parameter. Copyright The Institute of Statistical Mathematics, Tokyo 2013

Suggested Citation

  • P. Chigansky & Yu. Kutoyants, 2013. "Estimation in threshold autoregressive models with correlated innovations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(5), pages 959-992, October.
  • Handle: RePEc:spr:aistmt:v:65:y:2013:i:5:p:959-992
    DOI: 10.1007/s10463-013-0402-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10463-013-0402-4
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10463-013-0402-4?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mehmet Caner & Bruce E. Hansen, 2001. "Threshold Autoregression with a Unit Root," Econometrica, Econometric Society, vol. 69(6), pages 1555-1596, November.
    2. Yury Kutoyants, 2012. "On identification of the threshold diffusion processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(2), pages 383-413, April.
    3. Doukhan, Paul & Louhichi, Sana, 1999. "A new weak dependence condition and applications to moment inequalities," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 313-342, December.
    4. Ngai Chan & Yury Kutoyants, 2012. "On parameter estimation of threshold autoregressive models," Statistical Inference for Stochastic Processes, Springer, vol. 15(1), pages 81-104, April.
    5. Dedecker, Jérôme & Doukhan, Paul, 2003. "A new covariance inequality and applications," Stochastic Processes and their Applications, Elsevier, vol. 106(1), pages 63-80, July.
    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. Victor V. Konev & Sergey E. Vorobeychikov, 2022. "Fixed accuracy estimation of parameters in a threshold autoregressive model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 685-711, August.

    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. Jean-Marc Le Caillec, 2021. "Threshold autoregressive model blind identification based on array clustering," Post-Print hal-03210735, HAL.
    2. Hélène Cossette & Etienne Marceau & Véronique Maume-Deschamps, 2011. "Adjustment Coefficient for Risk Processes in Some Dependent Contexts," Methodology and Computing in Applied Probability, Springer, vol. 13(4), pages 695-721, December.
    3. Doukhan, P. & Pommeret, D. & Reboul, L., 2015. "Data driven smooth test of comparison for dependent sequences," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 147-165.
    4. Paul Doukhan & Gilles Teyssière & Pablo Winant, 2005. "A Larch Vector Valued Process," Working Papers 2005-49, Center for Research in Economics and Statistics.
    5. Paul Doukhan & Olivier Wintenberger, 2005. "An Invariance Principle for New Weakly Dependent Stationary Models using Sharp Moment Assumptions," Working Papers 2005-51, Center for Research in Economics and Statistics.
    6. Doukhan, Paul & Fokianos, Konstantinos & Li, Xiaoyin, 2012. "On weak dependence conditions: The case of discrete valued processes," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 1941-1948.
    7. Jean-Marc Bardet & Paul Doukhan & José Rafael Leon_, 2005. "Uniform Limit Theorems for the Integrated Periodogram of Weakly Dependent Time Series and their Applications to Whittle's Estimate," Working Papers 2005-46, Center for Research in Economics and Statistics.
    8. Giuliano-Antonini, R. & Weber, M., 2008. "The theta-dependence coefficient and an Almost Sure Limit Theorem for random iterative models," Statistics & Probability Letters, Elsevier, vol. 78(5), pages 564-575, April.
    9. Manel Kacem & Stéphane Loisel & Véronique Maume-Deschamps, 2016. "Some mixing properties of conditionally independent processes," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(5), pages 1241-1259, March.
    10. Sancetta, Alessio, 2005. "Distance between nonidentically weakly dependent random vectors and Gaussian random vectors under the bounded Lipschitz metric," Statistics & Probability Letters, Elsevier, vol. 75(3), pages 158-168, December.
    11. Rootzén, Holger, 2009. "Weak convergence of the tail empirical process for dependent sequences," Stochastic Processes and their Applications, Elsevier, vol. 119(2), pages 468-490, February.
    12. Doukhan, Paul & Wintenberger, Olivier, 2008. "Weakly dependent chains with infinite memory," Stochastic Processes and their Applications, Elsevier, vol. 118(11), pages 1997-2013, November.
    13. Paul Doukhan & Hélène Madre & Mathieu Rosenbaum, 2005. "Weak Dependence Beyond Mixing for Infinite ARCH-type Bilinear Models," Working Papers 2005-50, Center for Research in Economics and Statistics.
    14. Jean‐Marc Bardet & Paul Doukhan & José Rafael León, 2008. "Uniform limit theorems for the integrated periodogram of weakly dependent time series and their applications to Whittle's estimate," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 906-945, September.
    15. Doukhan, Paul & Neumann, Michael H., 2007. "Probability and moment inequalities for sums of weakly dependent random variables, with applications," Stochastic Processes and their Applications, Elsevier, vol. 117(7), pages 878-903, July.
    16. El Ghouch, Anouar & Genton, Marc G. & Bouezmarni , Taoufik, 2012. "Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing," LIDAM Discussion Papers ISBA 2012001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. Shyh-Wei Chen, 2008. "Non-stationarity and Non-linearity in Stock Prices: Evidence from the OECD Countries," Economics Bulletin, AccessEcon, vol. 3(11), pages 1-11.
    18. Jerôme Dedecker & Paul Doukhan, 2002. "A New Covariance Inequality and Applications," Working Papers 2002-25, Center for Research in Economics and Statistics.
    19. Sibel Cengiz & Afsin Sahin, 2014. "Modelling nonlinear behavior of labor force participation rate by STAR: An application for Turkey," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 7(1), pages 113-127, April.
    20. Pitarakis Jean-Yves, 2006. "Model Selection Uncertainty and Detection of Threshold Effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(1), pages 1-30, March.

    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:spr:aistmt:v:65:y:2013:i:5:p:959-992. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.