Abstract:
This research investigates the impact of water scarcity on sustainable development in Sub-Saharan countries by using the data of some selected countries over the period 2000-2010. Nowadays, the world is experiencing a worldwide water crisis that is regarded as something
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that might ruin our planet's natural sustainability. Water shortage is growing, and the fact is that humanity's demand diminishes natural resources more quickly than nature can replenish itself. Water scarcity inevitably increases and becomes a major cause for conflict between various nations of the world if human habits and unsustainable utilization of water resources are not changed. The variables used to measure the factors are population growth, Maternal Mortality Rate, Health Care Spending, Co2 emissions, and Percentage of Population with improved water sources and test their effect on sustainable development which is measured by the environmental performance index. Additionally, the methodology used to test for the relationships between the variables is panel least square, and ARDL models using the E-views 10 program. The result of this project showed in the short run, the LOG POPULATION seemed to be significant at a 10% significance level and its coefficient has a positive sign, indicating co-integration. However, HEALTHCARE was not significant in the short term, and HEALTHCARE appears to have a positive sign and significance at 1%, which explains the positive association between the dependent variable and HEALTHCARE. The MMR had a 1% significance level and a positive connection with the EPI. However, in the long run, the LOG POPULATION coefficient revealed a negative sign with EPI and a significance level of 5 percent which is a convincing conclusion. As for HEALTHCARE and MMR, the results both indicated a positive indication, however, healthcare was statistically significant only by 1%, while MMR showed no statistical significance at all. Keywords: Sustainability, Sub-Saharan, Water Scarcity, Population Growth, Health, Socio-Economic, Panel Data Analysis