Robust confidence sets in the presence of weak instruments
This paper considers instrumental variable regression with a single endogenous variable and the potential presence of weak instruments. I construct confidence sets for the coefficient on the single endogenous regressor by inverting tests robust to weak instruments. I suggest a numerically simple alg...
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| Format: | Article |
| Language: | en_US |
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Elsevier
2011
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| Online Access: | http://hdl.handle.net/1721.1/61662 https://orcid.org/0000-0002-0724-5428 |
| _version_ | 1826201412231495680 |
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| author | Mikusheva, Anna |
| author2 | Massachusetts Institute of Technology. Department of Economics |
| author_facet | Massachusetts Institute of Technology. Department of Economics Mikusheva, Anna |
| author_sort | Mikusheva, Anna |
| collection | MIT |
| description | This paper considers instrumental variable regression with a single endogenous variable and the potential presence of weak instruments. I construct confidence sets for the coefficient on the single endogenous regressor by inverting tests robust to weak instruments. I suggest a numerically simple algorithm for finding the Conditional Likelihood Ratio (CLR) confidence sets. Full descriptions of possible forms of the CLR, Anderson–Rubin (AR) and Lagrange Multiplier (LM) confidence sets are given. I show that the CLR confidence sets have nearly the shortest expected arc length among similar symmetric invariant confidence sets in a circular model. I also prove that the CLR confidence set is asymptotically valid in a model with non-normal errors. |
| first_indexed | 2024-09-23T11:51:31Z |
| format | Article |
| id | mit-1721.1/61662 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:51:31Z |
| publishDate | 2011 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | mit-1721.1/616622022-10-01T06:28:33Z Robust confidence sets in the presence of weak instruments Mikusheva, Anna Massachusetts Institute of Technology. Department of Economics Mikusheva, Anna Mikusheva, Anna This paper considers instrumental variable regression with a single endogenous variable and the potential presence of weak instruments. I construct confidence sets for the coefficient on the single endogenous regressor by inverting tests robust to weak instruments. I suggest a numerically simple algorithm for finding the Conditional Likelihood Ratio (CLR) confidence sets. Full descriptions of possible forms of the CLR, Anderson–Rubin (AR) and Lagrange Multiplier (LM) confidence sets are given. I show that the CLR confidence sets have nearly the shortest expected arc length among similar symmetric invariant confidence sets in a circular model. I also prove that the CLR confidence set is asymptotically valid in a model with non-normal errors. 2011-03-11T14:32:17Z 2011-03-11T14:32:17Z 2010-01 2009-12 Article http://purl.org/eprint/type/JournalArticle 0304-4076 http://hdl.handle.net/1721.1/61662 Mikusheva, Anna. “Robust confidence sets in the presence of weak instruments.” Journal of Econometrics 157.2 (2010): 236-247. https://orcid.org/0000-0002-0724-5428 en_US http://dx.doi.org/10.1016/j.jeconom.2009.12.003 Journal of Econometrics Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Elsevier MIT web domain |
| spellingShingle | Mikusheva, Anna Robust confidence sets in the presence of weak instruments |
| title | Robust confidence sets in the presence of weak instruments |
| title_full | Robust confidence sets in the presence of weak instruments |
| title_fullStr | Robust confidence sets in the presence of weak instruments |
| title_full_unstemmed | Robust confidence sets in the presence of weak instruments |
| title_short | Robust confidence sets in the presence of weak instruments |
| title_sort | robust confidence sets in the presence of weak instruments |
| url | http://hdl.handle.net/1721.1/61662 https://orcid.org/0000-0002-0724-5428 |
| work_keys_str_mv | AT mikushevaanna robustconfidencesetsinthepresenceofweakinstruments |