A Nonparametric Approach to Estimating Growth Determinants in Sub-Saharan Africa

Abstract

This paper provides a contribution to the growth empirics in sub-Saharan Africa with a focus on identifying the major determinants of long run economic growth among SSA countries. Being aware of the overwhelming dominance of parametric regression methodology in the extant literature and its associated numerous setbacks, we specifically employ the local linear kernel estimator which does not assume any functional form for the underlying growth model. At the end of the study, the findings suggest that there is a positive and nonlinear relationship between economic growth on one hand as well as investment in physical capital, population and democracy on the other hand. Again, while we find that human capital and inflation have no significant effect on economic growth over the study period, foreign aid was found to have negative effect on economic growth in SSA. The findings obtained in the paper have important implications for growth policy in SSA. Growth policies should thus consider population control, expanding and improving the quality of education and enrolment especially at the higher levels and strengthen democratic institutions. For research, the findings imply that researchers should be cautious in specifying the functional form of growth models when investigating the determinants of economic growth.

Keywords: Bandwidth, economic growth, local linear kernel regression, nonparametric, sub-Saharan Africa

DOI: 10.7176/JESD/12-16-02

Publication date:August 31^st 2021