Spatial inequality in sub-Saharan Africa

ABSTRACT

We examine spatial and national inequality in Sub-Saharan African (SSA) countries using comparable Demographic and Health Surveys (DHS) data. Using living standard measures to calculate asset indices, we find that SSA has considerable within-country spatial and national contemporary asset inequalities, with large cross-country variations. We also use data from 27 SSA countries with comparable data from 1995 to 2018 to compare inequalities in access to basic services. In most countries, regional and national inequities in access to basic services have decreased over time. Our findings show that regional inequality is a significant component of national inequality, which has policy implications.

KEYWORDS:

• Spatial inequality
• asset inequality
• basic services
• Africa

Acknowledgments

The authors gratefully acknowledge the funding for this research from the Agence Française de Développement via the EU-AFD Research Facility in Inequalities, as well as funding from the African Research Universities Alliance (ARUA). Murray Leibbrandt acknowledges the Department of Science and Innovation’s Research Chairs Initiative and the National Research Foundation for funding his work as the South African Research Chair in Poverty and Inequality.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Notes

1. Some empirical works have found a relationship between societal divides such as ethnicity and religion and access to publicly provided goods and services in SSA (see e.g., Brockerhoff & Hewett, 2000; Jackson, 2013; Kimenyi, 2006). See, for example, Østby et al. (2009) and Fjelde and Østby (2012) on the relationship between spatial inequality and ethnic conflict.

2. Harttgen et al. (2013) give four reasons why assets aren’t a good proxy for estimating household consumption: Changes in relative prices can lead to a demand shift favoring some assets at the expense of other household expenditures, assets are stocks while consumption is a flow, preferences for certain assets (e.g., televisions and telephones) may increase over time, and states heavily subsidize access to certain assets (e.g., electricity and water) (Harttgen et al., 2013: p. 41). Furthermore, in the absence of data on asset age and depreciation, asset values and predicted consumption may be overestimated.

3. The data are available from the DHS website(https://dhsprogram.com/Methodology/Survey-Types/DHS.cfm).

4. These asset indices are often called wealth indices too.

5. Price data is hardly available, and it is difficult to justify the use of equal weighs.

Additional information

Funding

This work was supported by the African Research Universities Alliance (ARUA). Agence Française de Développement

Notes on contributors

Muna Shifa

Muna Shifa is a senior research officer in SALDRU. She holds MCom and Ph.D. degrees in economics from the University of Cape Town and a BSc degree in statistics from Addis Ababa University. Her research focuses on land tenure systems and rural livelihoods, urbanization and development, social cohesion and inequality, and the analysis of poverty and inequality. She teaches postgraduate-level courses on complex surveys and measuring poverty and inequality in the School of Economics at the University of Cape Town.

Murray Leibbrandt

Murray Leibbrandt holds the National Research Foundation Chair in Poverty and Inequality Research in the School of Economics at the University of Cape Town. He is the Director of the Southern Africa Labour and Development Research Unit and the African Centre of Excellence for Inequality Research within the African Research Univerisities Alliance. He is on the Executive Committee of the International Economic Association and is a Senior Research Fellow of UNU-WIDER. He has published widely in development economics using survey data and especially panel data to analyze South Africa’s poverty, inequality and labor market dynamics.