Asymptotic Distribution of JIVE in a Heteroskedastic IV Regression with Many Instruments
Norman Swanson (),
John Chao (),
Whitney Newey and
Tiemen Woutersen ()
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Tiemen Woutersen: Johns Hopkins University
Departmental Working Papers from Rutgers University, Department of Economics
This 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 J IV 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 rate of growth of 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 strength of the instruments as measured by the relative orders of magnitude of rn and Kn.
Keywords: heteroskedasticity; instrumental variables; jackknife estimation; many instruments; weak instruments (search for similar items in EconPapers)
JEL-codes: C13 C31 (search for similar items in EconPapers)
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Journal Article: ASYMPTOTIC DISTRIBUTION OF JIVE IN A HETEROSKEDASTIC IV REGRESSION WITH MANY INSTRUMENTS (2012)
Working Paper: Asymptotic Distribution of JIVE in a Heteroskedastic IV Regression with Many Instruments (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:rut:rutres:201110
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