IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v45y1999i4p305-315.html
   My bibliography  Save this article

L1-estimation in linear models with heterogeneous white noise

Author

Listed:
  • Bantli, Faouzi El
  • Hallin, Marc

Abstract

Necessary and sufficient conditions are given for the consistency of the L1-estimator of the regression parameter [beta] in linear models with independent but possibly nonidentically distributed errors. The heteroscedastic case is treated as a particular case. The asymptotic normality of is also established, under assumptions which are weaker than in related results on the asymptotics of the sample median in heteroscedastic location models.

Suggested Citation

  • Bantli, Faouzi El & Hallin, Marc, 1999. "L1-estimation in linear models with heterogeneous white noise," Statistics & Probability Letters, Elsevier, vol. 45(4), pages 305-315, December.
  • Handle: RePEc:eee:stapro:v:45:y:1999:i:4:p:305-315
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(99)00072-3
    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 below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Marc Hallin & Ivan Mizera, 1997. "Unimodality and the asymptotics of M-estimators," ULB Institutional Repository 2013/2217, ULB -- Universite Libre de Bruxelles.
    2. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    3. Liese, F. & Vajda, I., 1994. "Consistency of M-Estimates in General Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 50(1), pages 93-114, July.
    4. Marc Hallin & Ivan Mizera, 2001. "Sample heterogeneity and the asymptotics of M-estimators," ULB Institutional Repository 2013/2103, ULB -- Universite Libre de Bruxelles.
    5. Roger W. Koenker & Vasco D'Orey, 1987. "Computing Regression Quantiles," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(3), pages 383-393, November.
    6. Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(2), pages 186-199, June.
    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. Élise, COUDIN & Jean-Marie DUFOUR, 2017. "Finite-Sample Generalized Confidence Distributions and Sign-Based Robust Estimators in Median Regressions with Heterogeneous Dependent Errors," Cahiers de recherche 01-2017, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    2. Hallin, Marc & Swan, Yvik & Verdebout, Thomas & Veredas, David, 2013. "One-step R-estimation in linear models with stable errors," Journal of Econometrics, Elsevier, vol. 172(2), pages 195-204.
    3. Qifa Xu & Chao Cai & Cuixia Jiang & Fang Sun & Xue Huang, 2020. "Block average quantile regression for massive dataset," Statistical Papers, Springer, vol. 61(1), pages 141-165, 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. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    2. Guili Liao & Qimeng Liu & Rongmao Zhang & Shifang Zhang, 2022. "Rank test of unit‐root hypothesis with AR‐GARCH errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 695-719, September.
    3. Jurecková, Jana & Klebanov, Lev B., 1999. "Trimmed, Bayesian and admissible estimators," Statistics & Probability Letters, Elsevier, vol. 42(1), pages 47-51, March.
    4. Andrew Chesher, 2005. "Nonparametric Identification under Discrete Variation," Econometrica, Econometric Society, vol. 73(5), pages 1525-1550, September.
    5. Song, Song & Ritov, Ya’acov & Härdle, Wolfgang K., 2012. "Bootstrap confidence bands and partial linear quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 244-262.
    6. Dima, Bogdan & Dincă, Marius Sorin & Spulbăr, Cristi, 2014. "Financial nexus: Efficiency and soundness in banking and capital markets," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 100-124.
    7. González-Rivera, Gloria & Maldonado, Javier & Ruiz, Esther, 2019. "Growth in stress," International Journal of Forecasting, Elsevier, vol. 35(3), pages 948-966.
    8. Andrew Chesher, 2003. "Nonparametric identification with discrete endogenous variables," CeMMAP working papers 06/03, Institute for Fiscal Studies.
    9. Chaohua Dong & Jiti Gao & Yundong Tu & Bin Peng, 2023. "Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models," Papers 2301.06631, arXiv.org.
    10. Nader Naifar & Shawkat Hammoudeh & Aviral Kumar Tiwari, 2019. "Do Energy and Banking CDS Sector Spreads Reflect Financial Risks and Economic Policy Uncertainty? A Time-Scale Decomposition Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 507-534, August.
    11. Lee, Ji Hyung, 2016. "Predictive quantile regression with persistent covariates: IVX-QR approach," Journal of Econometrics, Elsevier, vol. 192(1), pages 105-118.
    12. Sun, Yiguo, 2006. "A Consistent Nonparametric Equality Test Of Conditional Quantile Functions," Econometric Theory, Cambridge University Press, vol. 22(4), pages 614-632, August.
    13. Jurecková, Jana & Picek, Jan & Saleh, A.K.Md. Ehsanes, 2010. "Rank tests and regression rank score tests in measurement error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3108-3120, December.
    14. Koenker, Roger & Park, Beum J., 1996. "An interior point algorithm for nonlinear quantile regression," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 265-283.
    15. Alexander Aue & Rex C. Y. Cheung & Thomas C. M. Lee & Ming Zhong, 2014. "Segmented Model Selection in Quantile Regression Using the Minimum Description Length Principle," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1241-1256, September.
    16. Qadan, Mahmoud & Jacob, Maram, 2022. "The value premium and investors' appetite for risk," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 194-219.
    17. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Monash Econometrics and Business Statistics Working Papers 18/21, Monash University, Department of Econometrics and Business Statistics.
    18. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
    19. Qadan, Mahmoud, 2019. "Risk appetite, idiosyncratic volatility and expected returns," International Review of Financial Analysis, Elsevier, vol. 65(C).
    20. Holger Dette & Marc Hallin & Tobias Kley & Stanislav Volgushev, 2011. "Of Copulas, Quantiles, Ranks and Spectra - An L1-Approach to Spectral Analysis," Working Papers ECARES ECARES 2011-038, ULB -- Universite Libre de Bruxelles.

    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:eee:stapro:v:45:y:1999:i:4:p:305-315. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.