Modeling External Capital Inflows and Economic Growth in Africa Utilizing Ordinal Logistic Regression

There has been a lack of unanimity among researchers about the causality of economic growth that has led to calls for pragmatic models. Consequently, the purpose of this study was to examine the feasibility of the ordinal logistic regression model (OLRM) for an empirical economic growth study based on the Cobb-Douglas production function. The OLRM has been used in the biomedical sciences but hardly encountered in economic growth studies. The research question examined the feasibility of OLRM to determine the cumulative probabilities of African countries moving into higher income classifications on the basis of the combined effects of external capital inflows from 2003 to 2011. The findings were (a) a model fit of the OLRM based on 354 cases representing 44 African countries compiled from the World Bank's world development indicators; (b) cumulative probabilities of 67% and 23% of African countries moving to lower-middle-income, and then to upper-middle-income classifications respectively; and (c) a Nagelkerke pseudo R2 of 33%, which measured the proportion of Africa's economic growth that was explained by the aggregate external capital inflows. Compared to a Pierson R2 of 13%, the OLRM was impactful. Additionally, the cumulative odds ratio of 6.6 implied that African countries would need at least 6 times their current levels of development financing to move up the ladders of economic growth. The demonstrated feasibility of OLRM and its accompanying pragmatic conclusions have the social impact of OLRM being employed by policymakers and researchers in the examination of further questions of economic growth to guide economic development initiatives in Africa and other developing regions without the current state of conflicting inferences.