Removing structural changes from the GDP regression model on (foreign investment, unemployment, and inflation) using multinomial regression analysis

Abstract

This paper examines the impact of foreign direct investment (FDI), inflation (Inf), and unemployment (Ump) on gross domestic product (GDP) using a multinomial regression model while maintaining the direction and characteristics of each variable under structural changes. It concludes that the quadratic model for FDI is more explanatory than the simple linear model for changes in GDP, with GDP growing by approximately 3.423% when FDI increases by 7.61%. Similarly, the quadratic model for inflation (Inf) is more explanatory than the simple linear model for changes in GDP, and GDP stabilizes at 17.035% when Inf is at or above 5.99%. For unemployment (Ump), the simple linear regression model is the best model for explaining changes in GDP.