Finite Sample BIAS Corrected IV Estimation for Weak and Many Instruments

aSanford School of Public Policy and Department of Economics, Duke University, Durham, NC, USA
bDepartment of Economics, Massachusetts Institute of Technology, Cambridge, MA, USA
cHaas School of Business, University of California at Berkeley, Berkeley, CA, USA

Essays in Honor of Aman Ullah

ISBN: 978-1-78560-787-5, eISBN: 978-1-78560-786-8

ISSN: 0731-9053

Publication date: 23 June 2016


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 outperform Fuller (1977) estimators in terms of mean bias and MSE.



Harding, M., Hausman, J. and Palmer, C. (2016), "Finite Sample BIAS Corrected IV Estimation for Weak and Many Instruments", Essays in Honor of Aman Ullah (Advances in Econometrics, Vol. 36), Emerald Group Publishing Limited, pp. 245-273.

Download as .RIS



Emerald Group Publishing Limited

Copyright © 2016 Emerald Group Publishing Limited

Please note you might not have access to this content

You may be able to access this content by login via Shibboleth, Open Athens or with your Emerald account.
If you would like to contact us about accessing this content, click the button and fill out the form.