On B-robust Instrumental Variable Estimation of the Linear Model with Panel Data

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dc.contributor.author WALDMANN, Robert
dc.contributor.author WAGENVOORT, Rien J.L.M.
dc.date.accessioned 2012-09-11T08:20:03Z
dc.date.available 2012-09-11T08:20:03Z
dc.date.issued 2002
dc.identifier.citation Journal of Econometrics, 2002, 106, 2, 297-324 en
dc.identifier.issn 1872-6895
dc.identifier.issn 0304-4076
dc.identifier.uri http://hdl.handle.net/1814/23694
dc.description (Partially based on Chapter 3 of Wagenvoort's EUI PhD thesis, 1998.) en
dc.description.abstract The aim of this paper is to demonstrate how to acquire robust consistent estimates of the linear model when the fundamental orthogonality condition is not fulfilled. With this end in view, we develop two estimation procedures: Two stage generalized M (2SGM) and robust generalized method of moments (RGMM). Both estimators are B-robust, i.e. their associated influence function is bounded, consistent and asymptotic normally distributed. Our simulation results indicate that the relatively efficient RGMM estimator (in regressions with heteroskedastic and/or autocorrelated errors) provides accurate parameter estimates of a panel data model with all variables subject to measurement errors, even if a substantial portion of the data is contaminated with aberrant observations. The traditional estimation techniques such as 2SLS and GMM break down when outliers corrupt the data. en
dc.language.iso en en
dc.relation.ispartof Journal of Econometrics en
dc.title On B-robust Instrumental Variable Estimation of the Linear Model with Panel Data en
dc.type Article en
dc.identifier.doi 10.1016/S0304-4076(01)00102-6
dc.neeo.contributor WALDMANN|Robert|aut|
dc.neeo.contributor WAGENVOORT|Rien J.L.M.|aut|
dc.identifier.volume 106 en
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