Measuring the Impact of Governmental Expenditure and Inflation on Gross Domestic Product Using (Panel Models) during the Period 2014-2020..

(خلال الفترة2014-2020

Abstract

The study investigated the measurement of governmental expenditure and inflation on Gross Domestic Product. The problem was represented in several questions including: To what extent there is a statistically significant relationship between inflation and Gross Domestic Product using (Data Panel Models)? To what extent there is a statistically significant relationship between governmental expenditure and Gross Domestic Product? The study aimed to identify the measurement of the impact of the variables (governmental expenditure and inflation) on Gross Domestic Product during the period 2014-2020. In order to achieve the study objectives, the researcher collected data from the Central Authority of Statistics. The data were analyzed and the hypotheses were verified. The statistical package (E-views) and the (Panel Data Models) models were used through the Pooled Regression Model (PRM), the Fixed Effects Model (FEM) or the Random Effects Model (REM) to estimate the model and select which of the above mentioned models is the best to conduct the analysis. The study concluded several findings the most significant: The study showed that the estimated model is significant and this indicates that inflation and governmental expenditure together affect Gross Domestic Product in Sudan through F-Test. There is an effect of each inflation and governmental expenditure individually on Gross Domestic Product in Sudan because the coefficients values are significant. Inflation affects Gross Domestic Product more than governmental expenditure because the coefficient value in the model was (199.4569). The study recommends the following: Research practical results should be adopted when setting the economic and political plans for decision makers because of the accuracy of the results obtained. Further studies should be conducted on Data Panel Models using other variables in the States because of their role on estimation accuracy and wide contribution to development.