Marginal Analysis of Gross Domestic Product using Best-Fitted Least Square Model - Rahela Abdul Rahim; Fatinah Zainon; Noraziah Man (International Journal of Supply Chain Management, 2019)
Gross Domestic Product (GDP) represents the total monetary value of all goods and services produced over a specific time period. This study models the GDP data of the state of Kedah, Malaysia for year 2005-2016. A mathematical model is developed for the state GDP data using Least Square Methods. The future GDP values are predicted using five empirical models: Linear model, Quadratic model, Cubic model, Exponential model and Polynomial model. The result has shown that Exponential model is the best fitted model for Kedah GDP data. The result of the derivative of the obtained model provide marginal analysis that shows the performance of GDP per year for the state. s document gives formatting instructions for authors preparing papers for publication in the said journal. The authors must follow the instructions given in the document for the papers to be published. You can use this document as both an instruction set and as a template into which you can type your own text.