✦ LIBER ✦

The case against JIVE

✍ Scribed by Russell Davidson; James G. MacKinnon

Publisher: John Wiley and Sons
Year: 2006
Tongue: English
Weight: 135 KB
Volume: 21
Category: Article
ISSN: 0883-7252
DOI: 10.1002/jae.873

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

We perform an extensive series of Monte Carlo experiments to compare the performance of two variants of the ‘jackknife instrumental variables estimator’, or JIVE, with that of the more familiar 2SLS and LIML estimators. We find no evidence to suggest that JIVE should ever be used. It is always more dispersed than 2SLS, often very much so, and it is almost always inferior to LIML in all respects. Interestingly, JIVE seems to perform particularly badly when the instruments are weak. Copyright © 2006 John Wiley & Sons, Ltd.

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While Davidson and MacKinnon (2006) (DM) present an interesting analysis of recently advocated estimators for overidentified instrumental variables models, we disagree with their conclusion that the LIML estimator should almost always be prefered to the JIVE estimators of Phillips and Hale (1977) (P

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In a 1999 issue of the Journal of Applied Econometrics, two papers appeared examining the small sample properties of LIML and some jackknife IV estimators (JIVE). These two papers come to somewhat different conclusions regarding the appropriateness of using the jackknife IV estimators in applied wor

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We welcome the comments on our paper by Ackerberg and Devereux (AD) and Blomquist and Dahlberg (BD), and we are happy to take this opportunity to respond briefly to them. We agree wholeheartedly with both AD and BD that is it unprofitable to try to obtain meaningful empirical results when all avail

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