Bias Correction and Bootstrapping of Error Component Models for Panel Data: Theory and Applications
The wellknown Wallace-Hussain estimator is applied in pooled models with random individual effects, and the magnitude of the bias caused by the estimator is estimated by bootstrap methods. Furthermore, the significance of the bias is tested using an asymptotic test based on the bootstrap results.
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