Determinants of Bilateral FDI Positions: Empirical Insights from ECs Using Model Averaging Techniques

ABSTRACT

Although FDI determinants have been broadly studied, there is a lack of consensus on theoretical and empirical analysis from the perspective of emerging countries (ECs) as sources. However, this study aims to address the model uncertainty and non-universality in the empirical findings by performing two model averaging techniques as Bayesian Model Averaging (BMA) and Weighted Average Least Squares (WALS) approach. Using a bilateral FDI position dataset for the period 2009–2016, we investigate the robust FDI determinants of 24 ECs in developed, emerging, and other developing countries both at the source and destination level separately. Our findings reveal that the estimated FDI determinants are remarkably heterogeneous with change in the destination. Accordingly, the policymakers of ECs frame somewhat different strategies to channelize their FDI positions.

KEYWORDS:

• FDI determinants
• emerging countries
• model averaging
• Bayesian analysis

JEL CLASSIFICATIONS:

• C11
• F21
• F23

Supplemetary material

Supplemental data for this article can be accessed on the publisher’s website.

Notes

1. The term “Developing countries”, “Emerging countries”, “South”, “less developed countries”, “new industrialized countries”, and “non-traditional countries” are interchangeably used in the literature.

2. The emerging countries are in a transition phase between developing and developed countries, because of their rapid growth and industrialization (Gaeta 2012).

3. For a detailed description of country classification see section 3.

4. The number of possible models estimated in the BMA framework is equal to N=2k, which is the number of possible combinations of K (K=K1+K2) explanatory variables.