Discriminating between (in)valid external instruments and (in)valid exclusion restrictions
No 15-04, UvA-Econometrics Working Papers from Universiteit van Amsterdam, Dept. of Econometrics
In models estimated by (generalized) method of moments a test of coefficient restrictions can either be based on a Wald statistic or on the difference between evaluated criterion functions. Their correspondence can be used to demonstrate that a Sargan-Hansen test statistic for overidentification restrictions is equivalent to an omitted variables test statistic for a nonunique group of variables. We prove that this is the case for incremental Sargan-Hansen tests too. However, we also demonstrate that, despite this equivalence, one can nevertheless distinguish between either the (in)validity of some additional instruments or the (un)tenability of particular exclusion restrictions. It all hinges upon the required choice made regarding the initial maintained hypothesis.
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://ase.uva.nl/binaries/content/assets/subsites ... ics/dp-2015/1504.pdf (application/pdf)
Journal Article: Discriminating between (in)valid External Instruments and (in)valid Exclusion Restrictions (2017)
Working Paper: Discriminating between (in)valid external instruments and (in)valid exclusion restrictions (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ame:wpaper:1504
Access Statistics for this paper
More papers in UvA-Econometrics Working Papers from Universiteit van Amsterdam, Dept. of Econometrics Dept. of Econometrics, Universiteit van Amsterdam, Valckenierstraat 65, NL - 1018 XE Amsterdam, The Netherlands. Contact information at EDIRC.
Bibliographic data for series maintained by Noud P.A. van Giersbergen ().