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The Bias-Corrected First-Difference Estimator in
Dynamic Panel Data Models with Cross Section Dependence and Heteroscedasticity
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In this paper, we show that the bias-corrected first-difference (BCFD) estimator suggested by Chowdhury (1987) can be applied to the case where the error terms are cross-sectionally dependent and heteroscedastic. By deriving the finite sample bias of the BCFD estimator, we find that the BCFD estimator has small bias when T, the dimension of the time series, is not very large and ρ, the autoregressive parameter, is close to one. Simulation results show that the BCFD estimator performs better than existing estimators, especially when T is not very large. |
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| Copyright (C) 2003-2007 by Institute of Economic
Research.All rights reserved. |
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