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A Comprehensive Study on the Factors Impacting the GDP (per capita) of Major Economies around the Globe using Regression Analysis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 175 - Number 10 |
| Year of Publication: 2020 |
| Authors: Nimisha Bhide, Saurabh Khanolkar |
10.5120/ijca2020920560
|
Nimisha Bhide, Saurabh Khanolkar . A Comprehensive Study on the Factors Impacting the GDP (per capita) of Major Economies around the Globe using Regression Analysis. International Journal of Computer Applications. 175, 10 ( Aug 2020), 26-30. DOI=10.5120/ijca2020920560
Abstract
Financial Architecture aims at sustainability of an Economy. This is done by ensuring a consistent growth rate. GDP is a strong indicator of the growth of an economy. A Higher GDP of an economy reflects a robust growth. This leads to the definition of GDP (per capita). This study focuses on the GDP (per capita) as an indicator of a nation’s prosperity. The ratio of the GDP of an economy to its population is termed as the GDP (per capita). This study considers GDP (per capita) as a function of 17 factors. Further on, out of these 17 factors, 5 of the most statistically significant factors are identified using the Backward Elimination Algorithm. Thus, a statistically significant regression model is designed and the impact of each of the 5 factors on the GDP (per capita) is gauged. It was found that the combination of the aforementioned 5 statistically significant variables could explain 83% of the variance in the GDP (per capita) of the economies. The F statistic increased from 51.13(before applying Backward Elimination Algorithm); to 168.6 (after the application of the Algorithm) and hence, signifying the increase in the overall significance of the model. The authors firmly believe that that this study will form a foundation to the higher level policy making in the future.
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