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dc.contributor.authorChao, John C.en_US
dc.contributor.authorSwanson, Norman R.en_US
dc.contributor.authorHausman, Jerry A.en_US
dc.contributor.authorNewey, Whitney K.en_US
dc.contributor.authorWoutersen, Tiemenen_US
dc.description.abstractThis paper derives the limiting distributions of alternative jackknife IV (JIV) estimators and gives formulae for accompanying consistent standard errors in the presence of heteroskedasticity and many instruments. The asymptotic framework includes the many instrument sequence of Bekker (1994) and the many weak instrument sequence of Chao and Swanson (2005). We show that JIV estimators are asymptotically normal and that standard errors are consistent provided that √Kn/rn → 0 as n → ∞, where Kn and rn denote, respectively, the number of instruments and the concentration parameter. This is in contrast to the asymptotic behavior of such classical IV estimators as LIML, B2SLS, and 2SLS, all of which are inconsistent in the presence of heteroskedasticity, unless Kn/rn → 0. We also show that the rate of convergence and the form of the asymptotic covariance matrix of the JIV estimators will in general depend on the strength of the instruments as measured by the relative orders of magnitude of rn and Kn.en_US
dc.publisher|aJohns Hopkins Univ., Dep. of Economics |cBaltimore, Md.en_US
dc.relation.ispartofseries|aWorking papers // the Johns Hopkins University, Department of Economics |x567en_US
dc.subject.keywordinstrumental variablesen_US
dc.subject.keywordjackknife estimationen_US
dc.subject.keywordmany instrumentsen_US
dc.subject.keywordweak instrumentsen_US
dc.titleAsymptotic distribution of JIVE in a heteroskedastic IV regression with many instrumentsen_US
dc.typeWorking Paperen_US

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