Economic complexity to boost the selected sub-Saharan African economies

Thobeka Ncanywa,Brian S Molele,Thabiso E Letsoalo,Ombeswa Ralarala,Itumeleng P Mongale

doi:10.4102/jef.v14i1.567

Thobeka Ncanywa, Brian S Molele + Show 3 more

Open Access

https://doi.org/10.4102/jef.v14i1.567

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Abstract

Orientation: Economic complexity is a measure of productive capabilities indirectly by looking at the mix of sophisticated products that countries export. The economic complexity index proposed a proxy for diversity and ubiquity of products in the export basket.Research purpose: This study seeks to determine if economic complexity can influence the inequality measured by the Gini index in some selected sub-Saharan African countries.Motivation for the study: The need for the study emanates from the notion that that economic complexity can reduce income inequality hence it is imperative to investigate this relationship in the sub-Saharan African region where most countries produce few sophisticated goods that are also labour-intensive. Inadequate literature within the African continent has also contributed to the formulation of this study.Research approach/design and method: This study employed the autoregressive distribution lag (ARDL) model to analyze a panel data set, which includes eight sub-Saharan African countries for the period 1994–2017.Main findings: We found that economic complexity can reduce income disparities.Practical/managerial implications: Sub-Saharan African countries should shift their productive capabilities and resources from primary to sophisticated products in the manufacturing and services sector to increase economic complexity and reduce inequality.Contribution/value-add: The study makes an important contribution to the debate about the relationship between economic complexity and income inequality in the sub-Saharan African context and it is envisaged that it will inform the actions of the decision-makers to drive future productivity and prosperity in the region.

Highlights

Sub-Saharan Africa (SSA) remained the second most disproportionate continent following Latin America and inequalities have grown over time, as shown by the Gini index (World Bank 2011)
It was found that the three tests (LLC, IPC, FisherADF) show a mixture of levels (I[0]) and first order (I[1]) integration variables in the Gini index models of the selected SSA countries
We note that the Gini coefficient as our dependent variable is integrated of order one and our main independent variable, Economic complexity index (ECI) is integrated at level

Summary

Introduction

Sub-Saharan Africa (SSA) remained the second most disproportionate continent following Latin America and inequalities have grown over time, as shown by the Gini index (World Bank 2011). The Gini index is the measure of inequality and zero indicate complete equality whilst a value of 100 shows complete inequality. Inequalities may be reduced through several policies, such as increasing the minimum wage, progressive taxation and investing heavily on education. Countries that attempt to reduce inequalities through these policies may experience more economic crisis. Increasing the minimum wage may induce employers to retrench workers, creating unemployment which could potentially increase the income gap between the rich and poor (Park 2019). The study investigates economic complexity as a solution to reduce inequalities and boost selected SSA economies

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