Estimation and inference in dynamic unbalanced panel-data models with a small number of individuals
AbstractThis article describes a new Stata routine, xtlsdvc, that computes bias-corrected least-squares dummy variable (LSDV) estimators and their boot- strap variance-covariance matrix for dynamic (possibly) unbalanced panel-data models with strictly exogenous regressors. 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 estimator and three popular N-consistent estimators: Arellano-Bond, Anderson-Hsiao and Blundell-Bond. Results strongly sup- port the bias-corrected LSDV estimators according to bias and root mean squared error criteria when the number of individuals is small. Copyright 2005 by StataCorp LP.
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Bibliographic InfoArticle provided by StataCorp LP in its journal Stata Journal.
Volume (Year): 5 (2005)
Issue (Month): 4 (December)
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Web page: http://www.stata-journal.com/
Other versions of this item:
- Giovanni S.F. Bruno, 2005. "Estimation and inference in dynamic unbalanced panel data models with a small number of individuals," KITeS Working Papers 165, KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy, revised Jun 2005.
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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