Finite sample bias corrected IV estimation for weak and many instruments
Matthew Harding (),
Jerry Hausman () and
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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
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)
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Persistent link: https://EconPapers.repec.org/RePEc:ifs:cemmap:41/15
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