October 3, 2025 Thesis Open Access

KALKIDAN SAMUEL

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        <foaf:name>KALKIDAN SAMUEL</foaf:name>
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    <dct:title>STRUCTURAL CHANGE AND ECONOMIC GROWTH IN AFRICA</dct:title>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2025</dct:issued>
    <dcat:keyword>Africa, Economic growth, structural change, Industry Value added, Per capita GDP growth, Panel Data.</dcat:keyword>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2025-10-03</dct:issued>
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    <dct:description>&lt;p&gt;Since the late 1950s and mid 1960s which is known to be the period of African independence,&lt;br&gt; Africa&amp;rsquo;s growth performance and structural change, as indicated by the growth of the secondary&lt;br&gt; sector, have shown a fluctuating pattern. The period between the 1950s and the mid-1970s was&lt;br&gt; relatively of good economic performance and expansion of the manufacturing sector while the&lt;br&gt; period after the mid-1970s to the mid-1990s is characterized by poor economic performance and&lt;br&gt; contraction of the secondary sector. The period since the late 1990s is a period of rapid&lt;br&gt; economic growth but declining share of the secondary sector which implies negative structural&lt;br&gt; change in the context of this study. Given this pattern of economic growth and structural change,&lt;br&gt; previous studies focus on the effect of structural change on economic growth of Africa.&lt;br&gt; Accordingly, this study aims at analyzing the effect of economic growth on structural change in&lt;br&gt; Africa.Other drivers of structural change in Africa are also studied by considering the Natural&lt;br&gt; resource endowment hypothesis, Geography hypothesis, exchange rate policy hypothesis and&lt;br&gt; human capital hypothesis. The effect of openness on structural change is also analyzed by&lt;br&gt; considering the effect of trade on sectorial value added share.Secondary data for a set of 43&lt;br&gt; African countries for the period between 1980 to 2020 is collected from the World Bank&amp;rsquo;s World&lt;br&gt; Development Indicators Database. The countries and years of study are selected based on the&lt;br&gt; availability of data. The fixed Generalized Least Squares (FGLS) estimation is employed to&lt;br&gt; estimate the parameters as it addresses the problems of heterosckedasticity, autocorrelation and&lt;br&gt; Cross-sectional dependence existing within the data. The Durbin-Hausman-Wu endogenity test&lt;br&gt; is applied and the variables are found to be strictly exogenous. The result of the study shows that&lt;br&gt; Economic growth has a significant negative effect on Structural change. This is consistent with&lt;br&gt; the reality faced by African economies in the past decades for which economic growth and&lt;br&gt; structural change move in opposite directions to each other. Particularly after the mid-1990s,&lt;br&gt; the economy is growing faster but the industry sector&amp;rsquo;s share in output which represents&lt;br&gt; structural change, is declining. Exchange rate depreciation has also a negative effect on&lt;br&gt; structural change in Africa for the last four decades. On the other hand, Human Capital and&lt;br&gt; Openness has a positive effect on structural change that more improved human capital and more&lt;br&gt; open economy results in an increasing share of Industry Value Added thereby facilitating&lt;br&gt; structural change. Natural resource endowment and Geography are found to be insignificant&lt;br&gt; variables in the model estimation. Based on the result, the study recommends those policy&lt;br&gt; designs focused on: driving the fruits of economic growth towards the expansion of the industry&lt;br&gt; sector,increasing investment in human capital, following more liberal trade policies and well&lt;br&gt; managed exchange rate system.&lt;/p&gt;</dct:description>
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