Improved Jive estimators for overidentified linear models with and without heteroskedasticity
|Title:||Improved Jive estimators for overidentified linear models with and without heteroskedasticity||Authors:||Devereux, Paul J.
Ackerberg, Daniel A.
|Permanent link:||http://hdl.handle.net/10197/749||Date:||Aug-2008||Abstract:||We introduce two simple new variants of the Jackknife Instrumental Variables (JIVE) estimator for overidentified linear models and show that they are superior to the existing JIVE estimator, significantly improving on its small sample bias properties. We also compare our new estimators to existing Nagar (1959) type estimators. We show that, in models with heteroskedasticity, our estimators have superior properties to both the Nagar estimator and the related B2SLS estimator suggested in Donald and Newey (2001). These theoretical results are verified in a set of Monte-Carlo experiments and then applied to estimating the returns to schooling using actual data.||Type of material:||Working Paper||Publisher:||University College Dublin. School of Economics||Copyright (published version):||UCD School of Economics 2008||Subject LCSH:||Jackknife (Statistics)
Linear models (Statistics)
Human capital--Mathematical models
|Language:||en||Status of Item:||Not peer reviewed|
|Appears in Collections:||Economics Working Papers & Policy Papers|
Show full item record
This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.