Estimation and inference in dynamic unbalanced panel-data models with a small number of individuals

Giovanni S.F. Bruno ()

Stata Journal, 2005, vol. 5, issue 4, pages 473-500

Abstract: This 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.

Keywords: xtlsdvc; bias approximation; unbalanced panels; dynamic panel data; LSDV estimator; Monte Carlo experiment; bootstrap variance-covariance (search for similar items in EconPapers)
Date: 2005
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Working Paper: Estimation and inference in dynamic unbalanced panel data models with a small number of individuals (2005)
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