This study describes a new Stata routine that computes bias-corrected LSDV estimators and thier bootstrap variance-covariance matrix for dynamic (possibly) unbalanced panel data models. A Monte Carlo analysis is carried out to evaluate the finite-sample performance of the bias corrected LSDV estimators in comparison to the original LSDV estimators and three popular N-consistent estimators: Arellano-Bond, Anderson-Hsiao and Blundell-Bond. Results strongly support the bias-corrected LSDV estimators according to bias and root mean squared error criteria when the number of individuals is small.
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Paper provided by CESPRI, Centre for Research on Innovation and Internationalisation, Universita' Bocconi, Milano, Italy in its series CESPRI Working Papers with number
165.
Length: 28 pages Date of creation: Jun 2005 Date of revision:
Jun 2005 Handle: RePEc:cri:cespri:wp165
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Find related papers by JEL classification: C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
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