Drivers of Structural Transformation: The Case of the Manufacturing Sector in Africa

Abstract

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Governance, capital flight and industrialisation in Africa

“…It is important to note that whereas the sample consists of 36 African countries, 35 countries may appear in the regression output because of issues in degrees of freedom associated with some variables used in the conditioning information set. na: not applicable because at least one estimated coefficient needed for the computation of net effects is not significant First, on the one hand, the relevance of good governance in the promotion of industrialisation is consistent with a broad stream of macroeconomic-and industry-specific literature on the improvement of structural transformation in the manufacturing sector (Mijiyawa 2017); foreign direct investment (Rodriguez-Pose and Cols 2017) and technology-driven exports (Asongu and Asongu 2019), inter alia. On the other hand, the established unfavourable effect of capital flight on African industrialisation is broadly in line with a recent steam of literature on the relevance of capital flight in Africa's development (Ndiaye and Siri 2016;Mpenya et al 2016;Gankou et al 2016).…”

Sinking in Premature Deindustrialisation or Revitalising Industrialisation? Nepal’s Prospective

“…Rodrik's study documented an inverted-U relationship between share of manufacturing in GDP and per capita income. Mijiyawa (2017) analysed the driving factors of manufacturing development in Africa using the system-GMM technique with average panel data of the period 1995-2014 covering 53 African countries. Among other things the study documented a U-shaped relationship between the manufacturing share of GDP and per capita GDP.…”

The Effects of the Catch-Up Mechanism on the Structural Transformation of Sub-Saharan Africa

“…The structural change term from Equation 1is substituted by other variables that reflect structural transformation, namely, agriculture as percent of GDP, manufacturing as percent of GDP, and services as percent of GDP. Both Mijiyawa (2017) and Rodrik (2016b) use manufacturing share of GDP as the dependent variable. Second, we apply the theory of catch-up growth to examine the determinants of the patterns of structural change unfolding in SSA.…”

“…Given that most SSA nations are still low income, a U-shaped relationship between squared income per capita and both manufacturing and services shares of GDP suggests three things: one, there is a lot of labor force currently not absorbed into the modern formal sectors. Two, due to low manufacturing competitiveness, an increase in income per capita is accompanied by a reduction in the manufacturing share of GDP until a certain level of income from which both income and domestic manufacturing would increase (Mijiyawa 2017). When income per capita is low, an increase in incomes creates a sudden increase in demand for consumer manufactured goods which is met by increased imports instead of domestic production.…”