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Tobin q : Forecast performance for hierarchical Bayes, shrinkage, heterogeneous and homogeneous panel data estimators

Author

Listed:
  • Badi H. Baltagi
  • Georges Bresson

    (TEPP - Travail, Emploi et Politiques Publiques - UPEM - Université Paris-Est Marne-la-Vallée - CNRS - Centre National de la Recherche Scientifique, ERMES - Equipe de recherche sur les marches, l'emploi et la simulation - UP2 - Université Panthéon-Assas - CNRS - Centre National de la Recherche Scientifique)

  • Alain Pirotte

    (IFSTTAR/DEST - Département Économie et Sociologie des Transports - IFSTTAR - Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux - PRES Université Paris-Est)

Abstract

This paper reconsiders the Tobin q investment model studied by Hsiao et al. (1999) using a panel of 337 U.S. firms over the period 1982–1998. It contrasts the out-of-sample forecasts performance of hierarchical Bayes, shrinkage, as well as heterogeneous and homogeneous panel data estimators. Copyright Springer-Verlag 2004
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Badi H. Baltagi & Georges Bresson & Alain Pirotte, 2004. "Tobin q : Forecast performance for hierarchical Bayes, shrinkage, heterogeneous and homogeneous panel data estimators," Post-Print hal-04103132, HAL.
    • Handle: RePEc:hal:journl:hal-04103132
    DOI: 10.1007/s00181-003-0195-z
    as

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