Combining Two Consistent Estimators
This chapter shows how a weighted average of a forward and reverse Jackknife IV estimator (JIVE) yields estimators that are robust against heteroscedasticity and many instruments. These estimators, called HFUL (Heteroscedasticity robust Fuller) and HLIM (Heteroskedasticity robust limited information...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | en_US |
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Emerald (MCB UP)
2013
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| Online Access: | http://hdl.handle.net/1721.1/82655 https://orcid.org/0000-0003-2699-4704 https://orcid.org/0000-0002-5433-9435 |
| _version_ | 1811087591862173696 |
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| author | Chao, John C. Hausman, Jerry A. Newey, Whitney K. Swanson, Norman R. Woutersen, Tiemen |
| author2 | Massachusetts Institute of Technology. Department of Economics |
| author_facet | Massachusetts Institute of Technology. Department of Economics Chao, John C. Hausman, Jerry A. Newey, Whitney K. Swanson, Norman R. Woutersen, Tiemen |
| author_sort | Chao, John C. |
| collection | MIT |
| description | This chapter shows how a weighted average of a forward and reverse Jackknife IV estimator (JIVE) yields estimators that are robust against heteroscedasticity and many instruments. These estimators, called HFUL (Heteroscedasticity robust Fuller) and HLIM (Heteroskedasticity robust limited information maximum likelihood (LIML)) were introduced by Hausman, Newey, Woutersen, Chao, and Swanson (2012), but without derivation. Combining consistent estimators is a theme that is associated with Jerry Hausman and, therefore, we present this derivation in this volume. Additionally, and in order to further understand and interpret HFUL and HLIM in the context of jackknife type variance ratio estimators, we show that a new variant of HLIM, under specific grouped data settings with dummy instruments, simplifies to the Bekker and van der Ploeg (2005) MM (method of moments) estimator. |
| first_indexed | 2024-09-23T13:48:32Z |
| format | Article |
| id | mit-1721.1/82655 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:48:32Z |
| publishDate | 2013 |
| publisher | Emerald (MCB UP) |
| record_format | dspace |
| spelling | mit-1721.1/826552022-10-01T17:16:43Z Combining Two Consistent Estimators Chao, John C. Hausman, Jerry A. Newey, Whitney K. Swanson, Norman R. Woutersen, Tiemen Massachusetts Institute of Technology. Department of Economics Hausman, Jerry A. Newey, Whitney K. This chapter shows how a weighted average of a forward and reverse Jackknife IV estimator (JIVE) yields estimators that are robust against heteroscedasticity and many instruments. These estimators, called HFUL (Heteroscedasticity robust Fuller) and HLIM (Heteroskedasticity robust limited information maximum likelihood (LIML)) were introduced by Hausman, Newey, Woutersen, Chao, and Swanson (2012), but without derivation. Combining consistent estimators is a theme that is associated with Jerry Hausman and, therefore, we present this derivation in this volume. Additionally, and in order to further understand and interpret HFUL and HLIM in the context of jackknife type variance ratio estimators, we show that a new variant of HLIM, under specific grouped data settings with dummy instruments, simplifies to the Bekker and van der Ploeg (2005) MM (method of moments) estimator. 2013-12-06T14:07:57Z 2013-12-06T14:07:57Z 2012 Article http://purl.org/eprint/type/JournalArticle 978-1-78190-307-0 0731-9053 http://hdl.handle.net/1721.1/82655 Chao, John C., Jerry A. Hausman, Whitney K. Newey, Norman R. Swanson, and Tiemen Woutersen. Combining Two Consistent Estimators. Emerald (MCB UP), 2012. https://orcid.org/0000-0003-2699-4704 https://orcid.org/0000-0002-5433-9435 en_US http://dx.doi.org/10.1108/S0731-9053(2012)0000029007 Essays in Honor of Jerry Hausman (Advances in Econometrics) Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Emerald (MCB UP) SSRN |
| spellingShingle | Chao, John C. Hausman, Jerry A. Newey, Whitney K. Swanson, Norman R. Woutersen, Tiemen Combining Two Consistent Estimators |
| title | Combining Two Consistent Estimators |
| title_full | Combining Two Consistent Estimators |
| title_fullStr | Combining Two Consistent Estimators |
| title_full_unstemmed | Combining Two Consistent Estimators |
| title_short | Combining Two Consistent Estimators |
| title_sort | combining two consistent estimators |
| url | http://hdl.handle.net/1721.1/82655 https://orcid.org/0000-0003-2699-4704 https://orcid.org/0000-0002-5433-9435 |
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