JEFAS Vol. 29 Nº 57 (2024)

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12640/4145

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    Do credit risks deter FDI? Empirical evidence from the SAARC countries
    (Universidad ESAN. ESAN Ediciones, 2024-03-30) Alam, Md Badrul; Tahir, Muhammad; Ali, Norulazidah Omar
    Purpose: This paper makes a novel attempt to estimate the potential impact of credit risk on foreign direct investment (FDI hereafter), thereby focusing on a completely unexplored area in the existing empirical literature. Design/methodology/approach. To provide a comprehensive understanding of the relationship between credit risk and FDI inflows, the study incorporates all the eight-member economies of the South Asian Association of Regional Cooperation (SAARC hereafter) and analyzes a panel data set, over the period 2011 to 2019, extracted from the World Development Indicators, using the suitable econometric techniques for the efficient estimations of the specified models. Findings: The results indicate a negative and statistically significant relationship between the credit risk of the banking sectors and FDI inflows. Similarly, market size and inflation rate appear to be the two other main factors behind the increasing FDI inflows in the SAARC member economies. Interestingly, the size of the market became irrelevant in attracting FDI inflows when the Indian economy is excluded from the sample due to its higher economic weight. On the other hand, FDI inflows are not dependent on the level of trade openness, with most of the specifications showing either an insignificant or negative coefficient of the variable. Practical implications: The obtained results are unique and robust to alternative methodologies, and hence, the SAARC economies could consider them as the critical inputs in formulating the appropriate policies on FDI inflows. Originality/value: The findings are unique and original. The authors have established a relationship between credit risk and FDI for the first time in the SAARC context.
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    Foreign direct investment and local interpretable model-agnostic explanations: a rational framework for FDI decision making
    (Universidad ESAN. ESAN Ediciones, 2024-03-30) Singh, Devesh
    Purpose: This study aims to examine foreign direct investment (FDI) factors and develops a rational framework for FDI inflow in Western European countries such as France, Germany, the Netherlands, Switzerland, Belgium and Austria. Design/methodology/approach: Data for this study were collected from the World development indicators (WDI) database from 1995 to 2018. Factors such as economic growth, pollution, trade, domestic capital investment, gross value-added and the financial stability of the country that influence FDI decisions were selected through empirical literature. A framework was developed using interpretable machine learning (IML), decision trees and three-stage least squares simultaneous equation methods for FDI inflow in Western Europe. Findings: The findings of this study show that there is a difference between the most important and trusted factors for FDI inflow. Additionally, this study shows that machine learning (ML) models can perform better than conventional linear regression models. Research limitations/implications: This research has several limitations. Ideally, classification accuracies should be higher, and the current scope of this research is limited to examining the performance of FDI determinants within Western Europe. Practical implications: Through this framework, the national government can understand how investors make their capital allocation decisions in their country. The framework developed in this study can help policymakers better understand the rationality of FDI inflows. Originality/value: An IML framework has not been developed in prior studies to analyze FDI inflows. Additionally, the author demonstrates the applicability of the IML framework for estimating FDI inflows in Western Europe.