Lag length selection in panel autoregression
Model selection by BIC is well known to be inconsistent in the presence of incidental parameters. This article shows that, somewhat surprisingly, even without fixed effects in dynamic panels BIC is inconsistent and overestimates the true lag length with considerable probability. The reason for the i...
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| Main Authors: | , , |
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| 格式: | text |
| 語言: | English |
| 出版: |
Institutional Knowledge at Singapore Management University
2017
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| 主題: | |
| 在線閱讀: | https://ink.library.smu.edu.sg/soe_research/1893 https://ink.library.smu.edu.sg/context/soe_research/article/2893/viewcontent/LagLengthSelectionPanelAutoReg_2017_afv.pdf |
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| 總結: | Model selection by BIC is well known to be inconsistent in the presence of incidental parameters. This article shows that, somewhat surprisingly, even without fixed effects in dynamic panels BIC is inconsistent and overestimates the true lag length with considerable probability. The reason for the inconsistency is explained, and the probability of overestimation is found to be 50% asymptotically. Three alternative consistent lag selection methods are considered. Two of these modify BIC, and the third involves sequential testing. Simulations evaluate the performance of these alternative lag selection methods in finite samples. |
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