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Testing overidentifying restrictions with many instruments and heteroskedasticity
| dc.contributor.author | Chao, John C. | |
| dc.contributor.author | Swanson, Norman R. | |
| dc.contributor.author | Woutersen, Tiemen | |
| dc.contributor.author | Hausman, Jerry A | |
| dc.contributor.author | Newey, Whitney K | |
| dc.date.accessioned | 2017-02-06T19:02:53Z | |
| dc.date.available | 2017-02-06T19:02:53Z | |
| dc.date.issued | 2013-09 | |
| dc.identifier.issn | 03044076 | |
| dc.identifier.issn | 0304-4076 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/106873 | |
| dc.description.abstract | This paper gives a test of overidentifying restrictions that is robust to many instruments and heteroskedasticity. It is based on a jackknife version of the overidentifying test statistic. Correct asymptotic critical values are derived for this statistic when the number of instruments grows large, at a rate up to the sample size. It is also shown that the test is valid when the number of instruments is fixed and there is homoskedasticity. This test improves on recently proposed tests by allowing for heteroskedasticity and by avoiding assumptions on the instrument projection matrix. This paper finds in Monte Carlo studies that the test is more accurate and less sensitive to the number of instruments than the Hausman–Sargan or GMM tests of overidentifying restrictions. | en_US |
| dc.description.sponsorship | National Science Foundation (U.S.) | en_US |
| dc.language.iso | en_US | |
| dc.publisher | Elsevier | en_US |
| dc.relation.isversionof | http://dx.doi.org/10.1016/j.jeconom.2013.08.003 | en_US |
| dc.rights | Creative Commons Attribution-NonCommercial-NoDerivs License | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
| dc.source | Other univ. web domain | en_US |
| dc.title | Testing overidentifying restrictions with many instruments and heteroskedasticity | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Chao, John C. et al. “Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity.” Journal of Econometrics 178 (2014): 15–21. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Economics | en_US |
| dc.contributor.mitauthor | Hausman, Jerry A | |
| dc.contributor.mitauthor | Newey, Whitney K | |
| dc.relation.journal | Journal of Econometrics | en_US |
| dc.eprint.version | Original manuscript | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
| dspace.orderedauthors | Chao, John C.; Hausman, Jerry A.; Newey, Whitney K.; Swanson, Norman R.; Woutersen, Tiemen | en_US |
| dspace.embargo.terms | N | en_US |
| dc.identifier.orcid | https://orcid.org/0000-0002-5433-9435 | |
| dc.identifier.orcid | https://orcid.org/0000-0003-2699-4704 | |
| mit.license | PUBLISHER_CC | en_US |
