Macroeconomic Determinants of Unemployment in Africa: A Panel Data Analysis Approach
Keywords:
Unemployment; Africa; Determinants; Panel DataAbstract
The study explored the macroeconomic determinants of unemployment in Africa using
panel data analysis (fixed effects, random effects, pooled ordinary least squares, dynamic generalized
methods of moments), with data spanning from 2001 to 2015. Several empirical studies on the
determinants of unemployment have been done, results of which are convergent, divergent and quite
mixed. What is clearly coming out of this empirical research is that there is no universal agreed list of
the determinants of unemployment. Across all the four econometric estimation methods used, the
variables which were found not to be significant determinants of unemployment include information
and communication technology, human capital development and infrastructural development. The
dynamic GMM method observed that the lag of unemployment exacerbated unemployment in Africa.
All the four econometric approaches used produced results which show that FDI increased
unemployment in the African continent. African authorities are therefore urged to ensure that they
implement policies which ensures that the inflow of foreign direct investment (FDI) translates into
easing unemployment woos in the continent. The random effects and pooled OLS noted that financial
development had a significant positive effect on unemployment in the case of Africa. The relevant
African authorities should therefore implement programmes and policies that enhances the poor
people’s financial inclusion so that they can benefit from developed financial markets. As expected
and justified by literature, the pooled OLS shows that trade openness and population growth had a
significant positive impact on unemployment in Africa. However, the interaction between information
and communication technology (ICT) and human capital development was found to have had a
significant negative influence on unemployment across all the four econometric estimation
approaches. Africa is therefore urged to enhance human capital development if they intend to
economically benefit from new technologies especially during the present day 4th industrial revolution
otherwise their people becomes redundant. As expected, fixed effects and pooled OLS methods
shows that economic growth had a significant negative influence on unemployment in Africa. It is
against this backdrop that the study urges African authorities to implement growth-oriented policies if
they intend to reduce unemployment in the region.
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