IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v37y2016i5p603-623.html
   My bibliography  Save this article

Quantile Autoregression for Censored Data

Author

Listed:
  • Seokwoo Jake Choi
  • Stephen Portnoy

Abstract

No abstract is available for this item.

Suggested Citation

  • Seokwoo Jake Choi & Stephen Portnoy, 2016. "Quantile Autoregression for Censored Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(5), pages 603-623, September.
  • Handle: RePEc:bla:jtsera:v:37:y:2016:i:5:p:603-623
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/jtsa.12174
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    2. Portnoy, Stephen, 1991. "Asymptotic behavior of regression quantiles in non-stationary, dependent cases," Journal of Multivariate Analysis, Elsevier, vol. 38(1), pages 100-113, July.
    3. Weiss, Andrew A., 1991. "Estimating Nonlinear Dynamic Models Using Least Absolute Error Estimation," Econometric Theory, Cambridge University Press, vol. 7(1), pages 46-68, March.
    4. Marc Hallin & Jana Jureckova, 1999. "Optimal tests for autoregressive models based on autoregression rank scores," ULB Institutional Repository 2013/2089, ULB -- Universite Libre de Bruxelles.
    5. Stephen Portnoy & Guixian Lin, 2010. "Asymptotics for censored regression quantiles," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(1), pages 115-130.
    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. Jian Li & Jean‐Paul Chavas & Chongguang Li, 2022. "The dynamic effects of price support policy on price volatility: The case of the rice market in China," Agricultural Economics, International Association of Agricultural Economists, vol. 53(2), pages 307-320, March.
    2. Jau-er Chen & Masanori Kashiwagi, 2017. "The Japanese Taylor rule estimated using censored quantile regressions," Empirical Economics, Springer, vol. 52(1), pages 357-371, February.

    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. Gourieroux, C. & Jasiak, J., 2008. "Dynamic quantile models," Journal of Econometrics, Elsevier, vol. 147(1), pages 198-205, November.
    2. Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2009. "Copula-based nonlinear quantile autoregression," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 50-67, January.
    3. He, Fengyang & Wang, Huixia Judy & Zhou, Yuejin, 2022. "Extremal quantile autoregression for heavy-tailed time series," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
    4. Hongtao Guo & Miranda S. Lam & Guojun Wu & Zhijie Xiao, 2013. "Risk Analysis Using Regression Quantiles: Evidence from International Equity Markets," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 7(2), pages 1-15.
    5. Mukherjee, Kanchan, 2000. "Linearization Of Randomly Weighted Empiricals Under Long Range Dependence With Applications To Nonlinear Regression Quantiles," Econometric Theory, Cambridge University Press, vol. 16(3), pages 301-323, June.
    6. Alain Hecq & Li Sun, 2021. "Adaptive Random Bandwidth for Inference in CAViaR Models," Papers 2102.01636, arXiv.org.
    7. Escanciano, Juan Carlos & Velasco, Carlos, 2010. "Specification tests of parametric dynamic conditional quantiles," Journal of Econometrics, Elsevier, vol. 159(1), pages 209-221, November.
    8. Fitzenberger, Bernd, 1994. "A note on estimating censored quantile regressions," Discussion Papers 14, University of Konstanz, Center for International Labor Economics (CILE).
    9. Elise Coudin & Jean-Marie Dufour, 2017. "Finite-sample generalized confidence distributions and sign-based robust estimators in median regressions with heterogenous dependent errors," CIRANO Working Papers 2017s-06, CIRANO.
    10. Escanciano, Juan Carlos & Velasco, Carlos, 2010. "Specification tests of parametric dynamic conditional quantiles," Journal of Econometrics, Elsevier, vol. 159(1), pages 209-221, November.
    11. Jana Jurečková & Olcay Arslan & Yeşim Güney & Jan Picek & Martin Schindler & Yetkin Tuaç, 2023. "Nonparametric tests in linear model with autoregressive errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(4), pages 443-453, May.
    12. Zhu, Xuening & Wang, Weining & Wang, Hansheng & Härdle, Wolfgang Karl, 2019. "Network quantile autoregression," Journal of Econometrics, Elsevier, vol. 212(1), pages 345-358.
    13. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    14. repec:hal:journl:peer-00732534 is not listed on IDEAS
    15. Catania, Leopoldo & Luati, Alessandra, 2023. "Semiparametric modeling of multiple quantiles," Journal of Econometrics, Elsevier, vol. 237(2).
    16. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    17. Cai, Yuzhi, 2007. "A quantile approach to US GNP," Economic Modelling, Elsevier, vol. 24(6), pages 969-979, November.
    18. Fitzenberger, Bernd, 1998. "The moving blocks bootstrap and robust inference for linear least squares and quantile regressions," Journal of Econometrics, Elsevier, vol. 82(2), pages 235-287, February.
    19. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2015. "VAR for VaR: Measuring tail dependence using multivariate regression quantiles," Journal of Econometrics, Elsevier, vol. 187(1), pages 169-188.
    20. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2020. "The Efficiency Gap," Papers 2010.14146, arXiv.org, revised Sep 2022.
    21. Zhao Chen & Runze Li & Yaohua Wu, 2012. "Weighted quantile regression for AR model with infinite variance errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 715-731.

    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:bla:jtsera:v:37:y:2016:i:5:p:603-623. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.