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dc.contributor.authorArnold, Matthias-
dc.date.accessioned2007-09-05T12:55:54Z-
dc.date.available2007-09-05T12:55:54Z-
dc.date.issued2007-09-05T12:55:54Z-
dc.identifier.urihttp://hdl.handle.net/2003/24712-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-8890-
dc.description.abstractThis paper suggests an improved GMM estimator for the autoregressive parameter of a spatial autoregressive error model by taking into account that unobservable regression disturbances are different from observable regression residuals. Although this difference decreases in large samples, it is important in small samples. Monte Carlo simulations show that the bias can be reduced by 65 − 80% compared to a GMM estimator that neglects the difference between disturbances and residuals. The mean squared error is smaller, too.en
dc.language.isoende
dc.subjectGeneralized method of moments estimatoren
dc.subjectGMM estimationen
dc.subjectRegression residualsen
dc.subjectSpatial autoregressionen
dc.subject.ddc004-
dc.titleGMM estimation of the autoregressive parameter in a spatial autoregressive error model using regression residualsen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 475

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