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

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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.

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Authors and Affiliations

  1. Department of Economics, Texas A&M University, College Station , TX, 77843–4228, USA

    Badi H. Baltagi

  2. ERMES (CNRS) , Université Paris II , 12 Place du Panthéon , 75230 , Paris Cedex 05 , France

    Georges Bresson

  3. ERMES (CNRS) , Université de Valenciennes ,“Les Tertiales” rue des cent têtes, Université Paris II, 59313 , Valenciennes Cedex 9 , France

    Alain Pirotte

Authors
  1. Badi H. Baltagi
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  2. Georges Bresson
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  3. Alain Pirotte
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Corresponding author

Correspondence to Badi H. Baltagi.

Additional information

We are very grateful to Cheng Hsiao and A. Kamil Tahmiscioglu for providing us with the data set and computer code for the Hierarchical Bayes estimator as well as useful suggestions and comments.

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Baltagi, B., Bresson, G. & Pirotte, A. Tobin q: Forecast performance for hierarchical Bayes, shrinkage, heterogeneous and homogeneous panel data estimators. Empirical Economics 29, 107–113 (2004). https://doi.org/10.1007/s00181-003-0195-z

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  • DOI: https://doi.org/10.1007/s00181-003-0195-z

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