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Statistical Papers

, Volume 53, Issue 3, pp 739–752 | Cite as

Identifying the determinants of foreign direct investment: a data-specific model selection approach

  • Erhard Reschenhofer
  • Michael Schilde
  • Eva Oberecker
  • Ellen Payr
  • Hasan T. Tandogan
  • Lea M. Wakolbinger
Regular Article

Abstract

In this paper, we examine the potential determinants of foreign direct investment. For this purpose, we apply new exact subset selection procedures, which are based on idealized assumptions, as well as their possibly more plausible empirical counterparts to an international data set to select the optimal set of predictors. Unlike the standard model selection procedures AIC and BIC, which penalize only the number of variables included in a model, and the subset selection procedures RIC and MRIC, which consider also the total number of available candidate variables, our data-specific procedures even take the correlation structure of all candidate variables into account. Our main focus is on a new procedure, which we have designed for situations where some of the potential predictors are certain to be included in the model. For a sample of 73 developing countries, this procedure selects only four variables, namely imports, net income from abroad, gross capital formation, and GDP per capita. An important secondary finding of our study is that the data-specific procedures, which are based on extensive simulations and are therefore very time-consuming, can be approximated reasonably well by the much simpler exact methods.

Keywords

Foreign direct investment Non-nested models Model selection Subset selection Mean squared prediction error Penalty 

Mathematics Subject Classification (2000)

62F07 62J05 62P20 

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Erhard Reschenhofer
    • 1
  • Michael Schilde
    • 2
  • Eva Oberecker
    • 2
  • Ellen Payr
    • 2
  • Hasan T. Tandogan
    • 2
  • Lea M. Wakolbinger
    • 2
  1. 1.Department of Statistics and Operations ResearchUniversity of ViennaViennaAustria
  2. 2.Department of Business AdministrationUniversity of ViennaViennaAustria

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