Abstract
AbstractIn developing economies, stable foreign direct investment inflow is used as a means of realization of private sector growth and sustainable development goals. However, there is variability in inflows to African region in general and its economic bloc groupings in particular overtime across countries. In this regard, numerous empirical studies have been carried out on the determinants of investment inflow variability using different datasets on developing countries despite the studies have produced paradoxical findings. The aim of this study is, therefore, to empirically identify factors that determine variability of foreign direct investment inflows to COMESA member countries using panel data estimators. The study used explanatory research design with arrangement of secondary data, ex post control over variables, unbalanced short panel inclined with quantitative approach. The data were acquired from world development and governance indicators of World Bank for a period of 15 years ranging from 2002 to 2016 for 17 countries. Econometric model estimation procedures and diagnostic tests for classical linear regression model assumptions were carried out before making valid analysis. Accordingly, empirical evidence of the study revealed that infrastructure, government effectiveness, economic growth, control over corruption, trade openness, political stability, human capital and financial development have statistically positive effect on the inflow. However, external debt, inflation and regulatory quality failed to show significant effect. Therefore, member countries should take measures to narrow-up bottlenecks of financial development, improve infrastructure, scale-up trade integration, improve human capital quality, work to bring better political stability and to control corruption in order to boost-up stable inflows.
Publisher
Springer Science and Business Media LLC
Subject
Management of Technology and Innovation,Economics and Econometrics,Sociology and Political Science,Information Systems,Management Information Systems
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