L1-estimation in linear models with heterogeneous white noise
AbstractNecessary 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 45 (1999)
Issue (Month): 4 (December)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
Other versions of this item:
- Marc Hallin & Faouzi El Bantli, 1999. "L1-estimation in linear models with heterogeneous white noise," ULB Institutional Repository 2013/2083, ULB -- Universite Libre de Bruxelles.
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- Marc Hallin & Ivan Mizera, 2001. "Sample heterogeneity and the asymptotics of M-estimators," ULB Institutional Repository 2013/2103, ULB -- Universite Libre de Bruxelles.
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Marc Hallin & Ivan Mizera, 1997. "Unimodality and the asymptotics of M-estimators," ULB Institutional Repository 2013/2217, ULB -- Universite Libre de Bruxelles.
- Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(02), pages 186-199, June.
- 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.
- 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.
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