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)

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... 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. JEL: C31, C13, C15 Keywords: instrumental variables, weak and many instruments, finite sample, k-class estimators * We are grateful to Tim Armstrong for providing excellent research assistance. Thanks to Plamen Koev for sharing his code for the computation of hypergeometric functions.