| dc.description.abstract | The world is facing environmental challenges in particular the surging growth of greenhouse gases emissions. In line with these challenges, the developed world is funding sustainable development in poor countries, assumed to have low willingness to pay for
environmental quality improvements. We are therefore directed to asking the question, “Does financial sustainable development assistance improve environmental air quality in poor countries and if so, by what magnitude?” The study attempts to expose whether
financial development assistance reduces greenhouse gases emissions in Sub-Sahara Africa or not. With regards to value addition to this field, the study attempts to introduce the consumer theory of utility maximization in explaining how financial sustainable
development assistance shifts the country’s optimal consumption levels and it also attempts to introduce the Marshallian productivity theory in its suggested post-cure financial sustainable development assistance model. Empirically, the study makes use of
an econometric programme, STATA 9, to estimate the random effects panel data model in three functional forms, linear, quadratic and cubic forms, linking greenhouse gases emissions to sustainable development assistance, per capita income, energy use and manufacturing share. In addition, it also estimates the dynamic panel data model, linking the current greenhouse gases emissions to previous emissions in SSA countries. The study finds no evidence that financial sustainable development assistance improves
environmental air quality in SSA. The findings provide evidence that the quadratic functional form in terms of the sustainable development assistance variable provides the best fit for SSA data whereas the cubic functional form has the worst fit. While the
explicit link between environmental quality and per capita income professed by various empirical studies is not refuted, this study finds evidence that increases in current per capita incomes increase greenhouse gases emissions in SSA. In addition, energy use and
manufacturing share are found to be significant determinants of variations in greenhouse gases emissions in SSA in both the linear and quadratic functional forms. But in the dynamic random effects estimation, the study finds no evidence of a significant influence
of previous greenhouse gases emissions on current emissions although there is an indication of a positive relationship. | nor |