Recursive estimation in large panel data models: Theory and practice
Bai (2009) proposes recursive estimation for panel data models with interactive effects. We study the behaviours of this recursive estimator. The recursive formula is established that shows the behaviours of recursive estimators depend on the initial estimator, the population structure and the itera...
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| Vydáno v: | Journal of econometrics Ročník 224; číslo 2; s. 439 - 465 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Amsterdam
Elsevier B.V
01.10.2021
Elsevier Sequoia S.A |
| Témata: | |
| ISSN: | 0304-4076, 1872-6895 |
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| Abstract | Bai (2009) proposes recursive estimation for panel data models with interactive effects. We study the behaviours of this recursive estimator. The recursive formula is established that shows the behaviours of recursive estimators depend on the initial estimator, the population structure and the iterative steps. Under some general scenarios, we find that the recursive estimator becomes consistent after the first iteration from any initials. We also obtain the optimal number of iterative steps under some prescribed conditions. The central limit theorem of the recursive estimator is established when the initial estimator is OLS. Various simulations are conducted to support our theoretical findings. |
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| AbstractList | Bai (2009) proposes recursive estimation for panel data models with interactive effects. We study the behaviours of this recursive estimator. The recursive formula is established that shows the behaviours of recursive estimators depend on the initial estimator, the population structure and the iterative steps. Under some general scenarios, we find that the recursive estimator becomes consistent after the first iteration from any initials. We also obtain the optimal number of iterative steps under some prescribed conditions. The central limit theorem of the recursive estimator is established when the initial estimator is OLS. Various simulations are conducted to support our theoretical findings. |
| Author | Hsiao, Cheng Jiang, Bin Yang, Yanrong Gao, Jiti |
| Author_xml | – sequence: 1 givenname: Bin surname: Jiang fullname: Jiang, Bin organization: Monash University, Australia – sequence: 2 givenname: Yanrong surname: Yang fullname: Yang, Yanrong organization: The Australian National University, Australia – sequence: 3 givenname: Jiti surname: Gao fullname: Gao, Jiti organization: Monash University, Australia – sequence: 4 givenname: Cheng surname: Hsiao fullname: Hsiao, Cheng email: chsiao@usc.edu organization: University of Southern California, USA |
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| Cites_doi | 10.1214/13-AOS1183 10.1016/j.jeconom.2009.10.025 10.1111/j.1468-0262.2006.00692.x 10.1111/j.1368-423X.2010.00330.x 10.1080/07474938.2013.740998 10.1016/j.econlet.2011.02.001 10.3982/ECTA6135 10.1016/j.jeconom.2006.09.004 10.1093/biomet/asr048 10.1017/S0266466618000063 10.1016/j.jeconom.2015.06.001 10.1016/j.jeconom.2010.10.001 10.1016/j.jeconom.2014.06.018 10.1198/073500103288619124 10.1198/016214505000000204 10.1017/S0266466605050425 10.1016/j.jeconom.2010.12.003 10.1016/j.jeconom.2012.01.006 10.1111/rssb.12016 10.1016/j.jeconom.2012.07.001 10.3982/ECTA9382 |
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| Title | Recursive estimation in large panel data models: Theory and practice |
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