Initial-condition free estimation of fixed effects dynamic panel data models
It is well known that (quasi) MLE of dynamic panel data (DPD) models with short panels depends on the assumptions on the initial values; ignoring them or a wrong treatment of them will result in inconsistency or serious bias. This paper introduces a initial-condition free method for estimating the f...
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sg-smu-ink.soe_research-25992020-04-02T07:01:00Z Initial-condition free estimation of fixed effects dynamic panel data models YANG, Zhenlin It is well known that (quasi) MLE of dynamic panel data (DPD) models with short panels depends on the assumptions on the initial values; ignoring them or a wrong treatment of them will result in inconsistency or serious bias. This paper introduces a initial-condition free method for estimating the fixed-effects DPD models, through as simple modification of the quasi-score. An outer-product-of-gradients (OPG) method is also proposed for robust inference. The MLE of Hsiao, Pesaran and Tahmiscioglu (2002, Journal of Econometrics), where the initial observations are modeled, is extended to quasi MLE and an OPG method is proposed for robust inference. Consistency and asymptotic normality for both estimation strategies are established, and the two methods are compared through Monte Carlo simulations. The proposed method performs well in general, whether the panel is short or not. The quasi MLE performs comparably, except when model does not contain time-varying regressor, or the panel is not short and the dynamic parameter is small. The proposed method is much simpler and easier to apply. 2014-09-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1600 https://ink.library.smu.edu.sg/context/soe_research/article/2599/viewcontent/16_2014.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Bias reduction Consistency Asymptotic normality Dynamic panel Fixed effects Modified quasi-score Robust standard error Short panel Econometrics |
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Bias reduction Consistency Asymptotic normality Dynamic panel Fixed effects Modified quasi-score Robust standard error Short panel Econometrics YANG, Zhenlin Initial-condition free estimation of fixed effects dynamic panel data models |
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It is well known that (quasi) MLE of dynamic panel data (DPD) models with short panels depends on the assumptions on the initial values; ignoring them or a wrong treatment of them will result in inconsistency or serious bias. This paper introduces a initial-condition free method for estimating the fixed-effects DPD models, through as simple modification of the quasi-score. An outer-product-of-gradients (OPG) method is also proposed for robust inference. The MLE of Hsiao, Pesaran and Tahmiscioglu (2002, Journal of Econometrics), where the initial observations are modeled, is extended to quasi MLE and an OPG method is proposed for robust inference. Consistency and asymptotic normality for both estimation strategies are established, and the two methods are compared through Monte Carlo simulations. The proposed method performs well in general, whether the panel is short or not. The quasi MLE performs comparably, except when model does not contain time-varying regressor, or the panel is not short and the dynamic parameter is small. The proposed method is much simpler and easier to apply. |
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YANG, Zhenlin |
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YANG, Zhenlin |
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YANG, Zhenlin |
title |
Initial-condition free estimation of fixed effects dynamic panel data models |
title_short |
Initial-condition free estimation of fixed effects dynamic panel data models |
title_full |
Initial-condition free estimation of fixed effects dynamic panel data models |
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Initial-condition free estimation of fixed effects dynamic panel data models |
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Initial-condition free estimation of fixed effects dynamic panel data models |
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initial-condition free estimation of fixed effects dynamic panel data models |
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Institutional Knowledge at Singapore Management University |
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2014 |
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https://ink.library.smu.edu.sg/soe_research/1600 https://ink.library.smu.edu.sg/context/soe_research/article/2599/viewcontent/16_2014.pdf |
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