This visualization investigates South Africa's high income inequality with three angles to help decipher its curious case of recently having recorded one of the highest income inequality in the world.
Most of the Sub-saharan African countries have a very different economic composition than South Africa's. While most SSA countries' Gini correlates with education and agriculture, South Africa has a very high literacy rate and very low agricultural composition. In the first visualization, we see all countries with a recorded Gini coefficient of 70 or higher which happens to consist of eight African countries with South Africa being the most recent to join those ranks. This visualization charts a possible political event that may help explain why that specific country reached a Gini coefficient of 70 or higher during that year. The second and third visualizations look at two countries (Ethiopia and Tanzania) that have been case studies in the recent UNDP report, Income Inequality Trends in sub-Saharan Africa: Divergence, Determinants and Consequences. With the analysis of these two countries, I hope to paint a path of analysis that might help to explain South Africa's high inequality.
This is an investigative visualization using qualitative data for a closer read into the UNDP report, while trying to redirect the qualitative analysis to start a conversation on recommendations for South Africa. It seems that with a drive away from agriculture and towards services (which seems inevitable with higher education rates), inequality rises exponentially, so a close read into South Africa's economy may help prevent high inequality in the development of other SSA countries.
The political information was subjectively extracted from three sources (Wikipedia, Britannica, and Freedom House) that provided non-partisan general information about that year and country. I chose information that I thought was the most significant political event in the given time period.
The qualitiative data parsing from the report was hand-picked according to their relevance to the data points listed in the table and its utility in explaining some of the big topic issues covered throughout the report that I felt might help map South Africa's specific case.
As this is an investigation, I encourage users to read further into the report with my hope being that this visualization inspires one to think about and further investigate the factors involved in South Africa's high income inequality, but also with a lens of the growing development of SSA.
- Hover over each circle to see the Gini coefficient as recorded by the World Income Inequality Database. Text will also appear upon hovering that provides general political context during that year.
- Scroll down to read more about South Africa, Tanzania and Ethiopia as parsed from the report, Income Inequality Trends in sub-Saharan Africa.
- Hover over highlighted text to see the snippet extracted from the report.
- Download the report by clicking on the link in the footer to further investigate in context.
Odusola, Ayodele, Giovanni Cornia, Haroon Bhorat, and Pedro Conceição, eds. Income Inequality Trends in sub-Saharan Africa: Divergence, Determinants and Consequences. Report. Regional Bureau for Africa, United Nations Development Programme. New York, NY: United Nations Development Programme, 2017. September 21, 2017. Accessed November 7, 2017. http://www.africa.undp.org/content/rba/en/home/library/reports/income-inequality-trends-in-sub-saharan-africa--divergence--dete.html.
Gradín, Carlos. World Income Inequality Database. Database. United Nations University World Institute for Development, Economics Research. Helsinki, Finland: United Nations University, January 2017.
United Nations Statistics Division, UN Data: A World of Information, 2017.
Wikipedia contributors, Wikipedia, The Free Encyclopedia.
Encyclopaedia Britannica, 2017.
The World Factbook 2017, Washington, DC: Central Intelligence Agency, 2017.
Freedom in the World 2017, New York: NY: Freedom House, 2017.
Jennifer Widner, "Constitution Writing & Conflict Resolution: Data & Summaries," Princeton University, August 2005.