Bootstrap tests for unit roots based on lad estimation

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dc.contributor.author Moreno, Marta
dc.contributor.author Romo, Juan
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2009-12-22T14:41:38Z
dc.date.available 2009-12-22T14:41:38Z
dc.date.issued 1997-05
dc.identifier.uri http://hdl.handle.net/10016/6210
dc.description.abstract In this paper we propose a new bootstrap test for unit roots in first order autoregressive models based on least absolute deviation (LAD) estimators. It is known that the behaviour of this estimator when the distribution is heavy tailed is very good compared with least squares estimation. The innovations distribution dependence of the LAD asymptotic law is overcome using bootstrap, which automatically approaches the target distribution. We provide the bootstrap functional limit theory necessary to prove the asymptotic validity of the procedure. Our strategy avoids the usual problem of estimating the variance matrix and the density in zero, and the construction of distribution free statistics through linear combinations with the least squares estimator. Moreover, a large simulation study shows that our test has very good power behaviour compared with others proposed in the literature.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers Statistic and Econometrics
dc.relation.ispartofseries 97-33-16
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Autoregrerrive process
dc.subject.other bootstrap
dc.subject.other least absolute deviation
dc.subject.other unit root
dc.title Bootstrap tests for unit roots based on lad estimation
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
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