GMM estimation for dynamic panels with fixed effects and strong instrument at unity
This paper develops new estimation and inference procedures for dynamic panel data models with fixed effects and incidental trends. A simple consistent GMM estimation method is proposed that avoids the weak moment condition problem that is known to affect conventional GMM estimation when the autoreg...
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sg-smu-ink.soe_research-31252017-12-29T06:54:07Z GMM estimation for dynamic panels with fixed effects and strong instrument at unity HAN, C. PHILLIPS, Peter C. B. This paper develops new estimation and inference procedures for dynamic panel data models with fixed effects and incidental trends. A simple consistent GMM estimation method is proposed that avoids the weak moment condition problem that is known to affect conventional GMM estimation when the autoregressiye coefficient (rho) is near unity. In both panel and time series cases, the estimator has standard Gaussian asymptotics for all values of rho is an element of (-1, 1] irrespective of how the composite cross-section and time series sample sizes pass to infinity. Simulations reveal that the estimator has little bias even in very small samples. The approach is applied to panel unit root testing. 2010-02-01T08:00:00Z text https://ink.library.smu.edu.sg/soe_research/2125 info:doi/10.1017/S026646660909063X Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Econometrics |
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Econometrics HAN, C. PHILLIPS, Peter C. B. GMM estimation for dynamic panels with fixed effects and strong instrument at unity |
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This paper develops new estimation and inference procedures for dynamic panel data models with fixed effects and incidental trends. A simple consistent GMM estimation method is proposed that avoids the weak moment condition problem that is known to affect conventional GMM estimation when the autoregressiye coefficient (rho) is near unity. In both panel and time series cases, the estimator has standard Gaussian asymptotics for all values of rho is an element of (-1, 1] irrespective of how the composite cross-section and time series sample sizes pass to infinity. Simulations reveal that the estimator has little bias even in very small samples. The approach is applied to panel unit root testing. |
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HAN, C. PHILLIPS, Peter C. B. |
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HAN, C. PHILLIPS, Peter C. B. |
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HAN, C. |
title |
GMM estimation for dynamic panels with fixed effects and strong instrument at unity |
title_short |
GMM estimation for dynamic panels with fixed effects and strong instrument at unity |
title_full |
GMM estimation for dynamic panels with fixed effects and strong instrument at unity |
title_fullStr |
GMM estimation for dynamic panels with fixed effects and strong instrument at unity |
title_full_unstemmed |
GMM estimation for dynamic panels with fixed effects and strong instrument at unity |
title_sort |
gmm estimation for dynamic panels with fixed effects and strong instrument at unity |
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Institutional Knowledge at Singapore Management University |
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2010 |
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https://ink.library.smu.edu.sg/soe_research/2125 |
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1770573903870033920 |