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. 2025 Apr 18:2025:4406958.
doi: 10.1155/tswj/4406958. eCollection 2025.

Evaluation of the Impact of Selected Financial Indicators on Foreign Direct Investment in Bangladesh: A Nonlinear Modeling Approach

Md Sifat Ar Salan  1 , Akher Ali  1 , Ruhul Amin  1 , Afroza Sultana  1 , Mahabuba Naznin  2 , Mohammad Alamgir Kabir  1 , Md Moyazzem Hossain  1
Affiliations

Evaluation of the Impact of Selected Financial Indicators on Foreign Direct Investment in Bangladesh: A Nonlinear Modeling Approach

Md Sifat Ar Salan et al. ScientificWorldJournal. .

Abstract

Background: Foreign direct investment (FDI) is a steadfast contributor to capital flows and plays an indispensable role in driving economic advancement and emerging as a pivotal avenue for financing growth in Bangladesh. Therefore, this study identifies the factors that influence FDI inflows in Bangladesh. Moreover, the authors explored the more appropriate model for predicting FDI by comparing the efficacy of other models' predictions. Methods: This study is based on secondary data over the period 1973 to 2021 and collected from the publicly accessible website of the World Bank. A generalized additive model (GAM) was implemented for describing the proper splines. The model's performance was assessed using the modified R-squared, the Bayesian information criterion (BIC), and the Akaike information criterion (AIC). Results: Findings depict a significant nonlinear relationship between Bangladesh's FDI and key economic indicators, including GDP, trade openness, external debt, gross capital formation, gross national income (GNI) and government rates of exchange, total reserves, and total natural resource rent. It is also observed that the GAM (R 2 = 0.987, AIC = 608.03, and BIC = 658.28) outperforms multiple linear regressions and polynomial regression in predicting FDI, emphasizing the superiority of GAM in capturing complex relationships and improving predictive accuracy. Conclusion: A nonlinear relationship is observed between FDI along with the covariates considered in this study. The authors believed that this study's findings would assist in taking efficient initiatives for FDI management and proactive economic indicator optimization to empower Bangladesh's economic resilience and foster sustainable growth. The analysis revealed that FDI and its related risk factors follow a nonlinear pattern. The study recommends using the GAM regression as a reliable method for predicting FDI in Bangladesh. The authors suggest that the findings can guide policymakers in developing strategies to increase FDI inflows, stimulate economic growth, and ensure sustainable economic development in Bangladesh.

Keywords: financial modeling; foreign direct investment (FDI); generalized additive model (GAM); nonlinear modeling.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Framework of this study.
Figure 2
Figure 2
Time series plot of foreign direct investment (FDI).
Figure 3
Figure 3
Correlation matrix plot.
Figure 4
Figure 4
Plots of the results of VIF of the selected variables.
Figure 5
Figure 5
Linear and nonlinear plots of FDI against selective covariates.
Figure 6
Figure 6
Visualization depicting diagnostic checks for the fitted GAM.
Figure 7
Figure 7
Prediction with 95% confidence intervals of FDI in Bangladesh by GAM.
See this image and copyright information in PMC

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