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Bootstrap-based bias correction and inference for dynamic panels with fixed effects

Ignace De Vos, Gerdie Everaert and Ilse Ruyssen

Stata Journal, 2015, vol. 15, issue 4, 986-1018

Abstract: In this article, we describe a new command, xtbcfe, that performs the iterative bootstrap-based bias correction for the fixed-effects estimator in dynamic panels proposed by Everaert and Pozzi (2007, Journal of Economic Dynamics and Control 31: 1160–1184). We first simplify the core of their algorithm by using the invariance principle and subsequently extend it to allow for unbalanced and higher-order dynamic panels. We implement various bootstrap error resampling schemes to account for general heteroskedasticity and contemporaneous cross-sectional dependence. Inference can be performed using a bootstrapped variance–covariance matrix or percentile intervals. Monte Carlo simulations show that the simplification of the original algorithm results in a further bias reduction for very small T. The Monte Carlo results also support the bootstrap-based bias correction in higher-order dynamic panels and panels with cross-sectional dependence. We illustrate the command with an empirical example estimating a dynamic labor–demand function. Copyright 2015 by StataCorp LP.

Keywords: xtbcfe; bootstrap-based bias correction; dynamic panel data; unbalanced; higher order; heteroskedasticity; cross-sectional dependence; Monte Carlo; labor demand; bootstrap (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (66)

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Working Paper: BOOTSTRAP-BASED BIAS CORRECTION AND INFERENCE FOR DYNAMIC PANELS WITH FIXED EFFECTS (2015) Downloads
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