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Finite sample evidence of IV estimators under weak instruments
Author(s) -
FloresLagunes Alfonso
Publication year - 2007
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.916
Subject(s) - estimator , econometrics , sample (material) , mathematics , statistics , point (geometry) , sample size determination , point estimation , physics , geometry , thermodynamics
We present finite sample evidence on different IV estimators available for linear models under weak instruments; explore the application of the bootstrap as a bias reduction technique to attenuate their finite sample bias; and employ three empirical applications to illustrate and provide insights into the relative performance of the estimators in practice. Our evidence indicates that the random‐effects quasi‐maximum likelihood estimator outperforms alternative estimators in terms of median point estimates and coverage rates, followed by the bootstrap bias‐corrected version of LIML and LIML. However, our results also confirm the difficulty of obtaining reliable point estimates in models with weak identification and moderate‐size samples. Copyright © 2007 John Wiley & Sons, Ltd.