Consistent Estimation with a Large Number of Weak Instruments
John Chao () and
Norman Swanson ()
Departmental Working Papers from Rutgers University, Department of Economics
This paper analyzes the conditions under which consistent estimation can be achieved in instrumental Variables (IV) regression when the available instruments are weak, in the local-to-zero sense of Staiger and Stock (1997) and using the many-instrument framework of Morimune (1983) and Bekker (1994). Our analysis of an extended k-class of estimators that includes Jackknife IV (JIVE) establishes that consistent estimation depends importantly on the relative magnitudes of rn, the growth rate of the concentration parameter, and Kn, the number of instruments: In particular, LIML and JIVE are consistent when (Kn)^.5 /rn goes to zero, while two-stage least squares is consistent only if (Kn)^.5 /rn goes to zero, as n goes to infinity. We argue that the use of many instruments may be bene¯cial for estimation, as the resulting concentration parameter growth may allow consistent estimation, in certain cases.
Keywords: instrumental variables; k-class estimators; local to zero framework; pathwise asymptotics; weak instruments (search for similar items in EconPapers)
JEL-codes: C13 C31 (search for similar items in EconPapers)
Pages: 20 pages
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Journal Article: Consistent Estimation with a Large Number of Weak Instruments (2005)
Working Paper: Consistent Estimation with a Large Number of Weak Instruments (2004)
Working Paper: Consistent Estimation with a Large Number of Weak Instruments (2003)
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Persistent link: https://EconPapers.repec.org/RePEc:rut:rutres:200421
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