Alternative approximations of the bias and MSE of the IV estimator under weak identification with an application to bias correction

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Abstract

We provide analytical formulae for the asymptotic bias (ABIAS) and mean-squared error (AMSE) of the IV estimator, and obtain approximations thereof based on an asymptotic scheme which essentially requires the expectation of the first stage F-statistic to converge to a finite (possibly small) positive limit as the number of instruments approaches infinity. Our analytical formulae can be viewed as generalizing the bias and MSE results of [Richardson and Wu 1971. A note on the comparison of ordinary and two-stage least squares estimators. Econometrica 39, 973-982] to the case with nonnormal errors and stochastic instruments. Our approximations are shown to compare favorably with approximations due to [Morimune 1983. Approximate distributions of k-class estimators when the degree of overidentifiability is large compared with the sample size. Econometrica 51, 821-841] and [Donald and Newey 2001. Choosing the number of instruments. Econometrica 69, 1161-1191], particularly when the instruments are weak. We also construct consistent estimators for the ABIAS and AMSE, and we use these to further construct a number of bias corrected OLS and IV estimators, the properties of which are examined both analytically and via a series of Monte Carlo experiments.

Original languageEnglish (US)
Pages (from-to)515-555
Number of pages41
JournalJournal of Econometrics
Volume137
Issue number2
DOIs
StatePublished - Apr 2007

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Keywords

  • Confluent hypergeometric function
  • Laplace approximation
  • Local-to-zero asymptotics
  • Weak instruments

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