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Analysis of macroeconomic predictive variables on gross domestic product using stepwise regression model

International Journal of Applied Research · 2020 · Vol. 6(9) · pp. 430–437
Onwubuya MNG Orighoyegha

Abstract

Over the years, interest has been on estimating best regression models that minimizes error when several estimated models contain irrelevant independent variables. This study deals with analysis of macroeconomic predictive variables of gross domestic product. The data used for this study were obtained from a secondary source. A multiple regression model containing six independent variables of economic data were fitted. The variables included in the model are external debt, exchange rate, foreign direct investment, net export, consumption and debt payment. The data were analyzed through the use of stepwise regression with the help of statistical software (SPSS). The best model excluded both the debt service payment and the external for the single variable model and excludes only the debt service payment for the two variable models. Based on the analysis, consumption index and exchange rate influences the gross domestic product better; therefore, the use of stepwise regression is really essential in determining the predictive power of a regression model.

Advanced Statistical Methods and ModelsGross domestic productStepwise regressionRegression analysisEconometricsRegressionStatisticsVariablesEconomicsLinear regressionConsumption (sociology)
Citations
0
FWCI
0.00
field-weighted impact
References
10
Percentile
20%
vs. same field & year
References
Discovering Statistics Using SPSS
Medical Entomology and Zoology · 2000 · 27,794 citations
Model selection in ecology and evolution
Trends in Ecology & Evolution · 2003 · 3,816 citations
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