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Bias Correction and Bootstrapping of Error Component Models for Panel Data: Theory and Applications

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  • Bellmann, L
  • Breitung, J
  • Wagner, Joachim

Abstract

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.

Suggested Citation

  • Bellmann, L & Breitung, J & Wagner, Joachim, 1989. "Bias Correction and Bootstrapping of Error Component Models for Panel Data: Theory and Applications," Empirical Economics, Springer, vol. 14(4), pages 329-342.
    • Handle: RePEc:spr:empeco:v:14:y:1989:i:4:p:329-42
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    Cited by:

    1. Ricardo De Bonis & Giuseppe Bruno, 2000. "A Comparative Study Of Alternative Econometric Packages: An Application To Italian Deposit Interest Rates," Computing in Economics and Finance 2000 160, Society for Computational Economics.
    2. Michael K. Andersson & Sune Karlsson, 2001. "Bootstrapping Error Component Models," Computational Statistics, Springer, vol. 16(2), pages 221-231, July.
    3. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2022. "Robust Dynamic Space-Time Panel Data Models Using ε-contamination: An Application to Crop Yields and Climate Change," Center for Policy Research Working Papers 254, Center for Policy Research, Maxwell School, Syracuse University.
    4. Baltagi, Badi H. & Bresson, Georges & Chaturvedi, Anoop & Lacroix, Guy, 2018. "Robust linear static panel data models using ε-contamination," Journal of Econometrics, Elsevier, vol. 202(1), pages 108-123.

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