The causality relationship between income inequality, debt, and economic growth in Sub-Saharan African countries 1

Abstract

AbstractThis study aims to investigate the direction of causality between income inequality and growth, income inequality and debt, and debt and growth for 11 selected countries in SSA countries (Botswana, Ghana, Kenya, Lesotho, Malawi, Nigeria, Rwanda, South Africa, Tanzania, Uganda, and Zambia). The panel bootstrap causality approach is applied to these countries from 1980 to 2018. Inequality is represented using Gini coefficient, Palma ratio, and Theil index. The findings show that there is at least a one-way causal relationship between public debt and inequality in Botswana, Ghana, Kenya, Malawi, Nigeria, Rwanda, South Africa, Tanzania, and Uganda, between inequality and growth in Botswana, Lesotho, Nigeria, and South Africa and between growth and debt in Botswana, Rwanda, South Africa, and Uganda. Empirical results imply that the relations between the relevant variables in the Sub-Saharan African countries may vary according to the specific characteristics of these countries. To the best of our knowledge, this is the first paper to analyse the impact of these three macroeconomic variables together.KEYWORDS: Income inequalitypublic debteconomic growthpanel bootstrap causality approachJel Classifications: C1D3H63010 Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Odusola et al. (Citation2017) states that more than half of the 19 most unequal countries in the world are in Sub-Saharan Africa (hereafter SSA).2 SSA countries refers to countries in Sub Sahara Africa.3 Investing debt in nonproductive activities like war can lead to debt distress whereby there is accumulation of unpaid debts, and the country is unable to fulfill all its obligations including interest rate repayment.4 According to Seery, Okanda, and Lawson (Citation2019) Africa is the second most unequal continent in the world with the five richest men in Africa owning more wealth than the bottom 50% combined.5 The list of SSA countries considered in this study include Botswana, Ghana, Kenya, Lesotho, Malawi, Nigeria, Rwanda, South Africa, Tanzania, Uganda, and Zambia. The selection of the countries is because they are representative of the different income groups in SSA covering countries in the low-income, lower-middle and upper-middle-income country classifications. This ensures that a wide range of economic conditions are represented and allow for easier cross-country comparisons. By studying countries from each income group, we can gain insights into the unique challenges and opportunities each group faces, and how these factors interact with public debt and economic growth.6 Asongu (Citation2013) examines domestic, foreign, private and public investments separately and whether they effect income-inequality through financial intermediary dynamics.7 Due to data availability and verifiability of the macroeconomic variables considered, the period has been limited to 1980-2018 (1990-2018 for Gini). The main databases available containing inequality information including SWIID and WIID, have gaps especially for SSA countries which are the countries under consideration in the study. To allow for comparability, data from the same database available for a consistent time period has been used.8 Palma ratio is calculated by taking the top 10% of population’s share of Gross National Income and dividing it with the bottom 40% of the population’s income.