Robust FDI determinants: Bayesian Model Averaging in the presence of selection bias

Theo Eicher, Lindy Helfman and Alex Lenkoski

Journal of Macroeconomics, 2012, vol. 34, issue 3, 637-651

Abstract: The literature on Foreign Direct Investment (FDI) determinants is remarkably diverse in terms of competing theories and empirical results. We utilize Bayesian Model Averaging (BMA) to resolve the model uncertainty that surrounds the validity of the competing FDI theories. Since the structure of existing FDI data is well known to induce selection bias, we extend BMA theory to HeckitBMA in order to address model uncertainty in the presence of selection bias. We show that more than half of the previously suggested FDI determinants are not robust and highlight theories that do receive robust support from the data. Our selection approach allows us to identify the determinants of the margins of FDI (intensive and extensive), which are shown to differ profoundly. Our results suggest a new emphasis in FDI theories that explicitly identify the dynamics of the intensive and extensive FDI margins.

Keywords: FDI determinants; Bayesian Model Averaging (BMA); Selection bias (search for similar items in EconPapers)
JEL-codes: C52 F21 F23 (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (74)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmacro:v:34:y:2012:i:3:p:637-651

DOI: 10.1016/j.jmacro.2012.01.010

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