Finite sample bias corrected IV estimation for weak and many instruments

Matthew Harding (), Jerry Hausman () and Christopher Palmer
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Jerry Hausman: Institute for Fiscal Studies and MIT
Christopher Palmer: Institute for Fiscal Studies

No CWP41/15, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: This paper considers the finite sample distribution of the 2SLS estimator and derives bounds on its exact bias in the presence of weak and/or many instruments. We then contrast the behavior of the exact bias expressions and the asymptotic expansions currently popular in the literature, including a consideration of the no-moment problem exhibited by many Nagar-type estimators. After deriving a finite sample unbiased k-class estimator, we introduce a double k-class estimator based on Nagar (1962) that dominates k-class estimators (including 2SLS), especially in the cases of weak and/or many instruments. We demonstrate these properties in Monte Carlo simulations showing that our preferred estimators outperforms Fuller (1977) estimators in terms of mean bias and MSE.

Keywords: Instrumental variables; weak and many instruments; finite sample; k-class estimators (search for similar items in EconPapers)
JEL-codes: C13 C15 C31 (search for similar items in EconPapers)
Date: 2015-07-21
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (2)

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