期刊
EMERGING MARKETS FINANCE AND TRADE
卷 58, 期 3, 页码 710-726出版社
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/1540496X.2020.1837107
关键词
FDI determinants; emerging countries; model averaging; Bayesian analysis
Although FDI determinants have been extensively studied, there is a lack of consensus on the theoretical and empirical analysis from the perspective of emerging countries (ECs) as sources. This study addresses the lack of universality in empirical findings by using two model averaging techniques - Bayesian Model Averaging (BMA) and Weighted Average Least Squares (WALS). The results reveal that the determinants of FDI vary significantly depending on the destination, suggesting that policymakers in ECs need to formulate different strategies to attract FDI.
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.
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