Bootstrap Based Bias Correction for Homogeneous Dynamic²² Panels
The within or least squares dummy variable estimator is severely biased in homogeneous dynamic panel models with moderate T. We present a bias correction for this estimator based on an iterative bootstrap procedure. Monte Carlo simulations show that this procedure is a good alternative for the analytical correction by Kiviet (1995, JE). The bootstrap (i) improves on the analytical correction when the variance of the individual effects increases, (ii) is straightforward to extend to less restrictive settings and (iii) allows for a correction of the longrun coefficient that is independent of the correction of the short-run coefficients.
Bias correction, within estimator, dynamic panel, GMM estimator, Monte Carlo simulation, Bootstrap
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