Salan Md Sifat Ar, Ali Akher, Amin Ruhul, Sultana Afroza, Naznin Mahabuba, Kabir Mohammad Alamgir, Hossain Md Moyazzem
Department of Statistics and Data Science, Jahangirnagar University, Dhaka, Bangladesh.
Department of Statistics, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
ScientificWorldJournal. 2025 Apr 18;2025:4406958. doi: 10.1155/tswj/4406958. eCollection 2025.
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. 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 -squared, the Bayesian information criterion (BIC), and the Akaike information criterion (AIC). 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 ( = 0.987, = 608.03, and = 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. 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.
外国直接投资(FDI)是资本流动的坚定贡献者,在推动经济发展方面发挥着不可或缺的作用,并成为孟加拉国融资增长的关键途径。因此,本研究确定了影响孟加拉国FDI流入的因素。此外,作者通过比较其他模型预测的有效性,探索了更适合预测FDI的模型。本研究基于1973年至2021年期间的二手数据,这些数据从世界银行的公开网站收集。采用广义相加模型(GAM)来描述合适的样条。使用修正平方、贝叶斯信息准则(BIC)和赤池信息准则(AIC)评估模型的性能。研究结果表明,孟加拉国的FDI与关键经济指标之间存在显著的非线性关系,这些指标包括国内生产总值、贸易开放度、外债、总资本形成、国民总收入(GNI)、政府汇率、总储备和总自然资源租金。还观察到,GAM(=0.987,=608.03,且=658.28)在预测FDI方面优于多元线性回归和多项式回归,强调了GAM在捕捉复杂关系和提高预测准确性方面的优越性。在FDI与本研究中考虑的协变量之间观察到非线性关系。作者认为,本研究的结果将有助于采取有效的FDI管理举措和积极的经济指标优化措施,以增强孟加拉国的经济韧性并促进可持续增长。分析表明,FDI及其相关风险因素呈现非线性模式。该研究建议使用GAM回归作为预测孟加拉国FDI的可靠方法。作者建议,这些发现可以指导政策制定者制定战略,以增加FDI流入、刺激经济增长并确保孟加拉国的可持续经济发展。