Appraisal of Trade Potency on Economic Growth in Sudan: New Empirical and Policy Analysis

Abstract

Article History JEL Classification F1, F10, F14 This paper investigates the relationship between domestic investment, exports, imports, and economic growth in Sudan. In order to achieve this purpose, annual data were collected from the reports of World Bank for the periods between 1976 and 2015, was tested by using Augmented Dickey-Fuller (ADF) and Phillip-Perron (PP) stationary test, co integration analysis of Vector Error Correction Model and the Granger-Causality tests. According to the result of the analysis, unit root tests show that economic growth, domestic investment, exports and imports series become stationary when first difference is considered. Also, it was determined by using co integration analysis that there is relationship between the four variables in Sudan. Also, and according to the Vector Error Correction Model, there is no relationship between variables in the long run term. On the other hand, and according to the GrangerCausality tests, we defined that in the short run term, only economic growth cause domestic investment. These results provide evidence that Reforms and measures in economic strategies are still insufficient to make trade and domestic investment able to boost the Sudan's economy. Contribution/ Originality:

The Impact of Olive Oil Exports on Economic Growth: Empirical Analysis from Tunisia

“…Results provide evidence that domestic investment, exports and labors are seen as a source of economic growth in Malaysia. Bakari (2017b) investigated the nexus between trade, domestic investment and economic growth for the period 1976 -2015. To attempt this objective, the author employed in his analyses cointegration analysis of Vector Error Correction Model and the Granger Causality Tests.…”

Does Trade Openness Promote Economic Growth? The Case of Sudan

“…The ARDL model is further evaluated by diagnostic test such as serial correlation. The table (5) and table (6) illustrate the findings of the test for model ( 1) and ( 2) respectively. It is clear that the models are stable since we cannot reject the null hypothesis of no serial correlation.…”

“…In addition, the stability of ARDL model was assessed using the CUSUM and CUSUMSQ test as suggested by Pesaran. 5 Figure ( 4) and ( 5) present the findings of CUSUM and CUSUMSQ for model (1) and model ( 2) respectively. The models have passed the test indicating the stability of the estimated parameters except model ( 1) the bivariate has fail to pass the CUSUM test.…”

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Untitled

“…This study contributes to the body of knowledge in a number of ways. Firstly, while the literature examining the link between macroeconomic factors and carbon emissions have been fairly vast (Lee and Chang, 2008;Narayan and Narayan, 2010;Sharma, 2011;Iwata et al, 2012;Ozturk and Acaravci, 2013;Adebambo et al, 2014;Henry, 2014;Rasiah et al, 2015;Zomorrodi and Zhou, 2016;Alkali and Imam, 2016;Zambrano-Monserrate et al, 2016;Zomorrodi and Zhou, 2017;Kahouli, 2017;Khan et al, 2017;Bakari, 2017), the impact of financial development on carbon emissions has, however, been rather neglected (neglect spotting gap). The second contribution comes from the fact that although many studies have been carried out on the various macroeconomic antecedents of carbon emissions, there exists ambiguity in the findings (confusion spotting).…”