Testing Economic Growth Convergence and Its Policy Implications in the Gauteng City-Region

Chapter
Part of the GeoJournal Library book series (GEJL)

Abstract

Reducing income inequalities remains one of the key challenges facing South Africa twenty years after democracy. While these inequalities are very clear along racial lines, they are also very stark spatially. For example, research in 2000 showed that 82% of South Africa’s gross domestic product (GDP) was concentrated in 20% of the country’s major urban areas and 20% of urban areas had an average per capita income of R25,277, compared with an average per capita income of R5,452 for the poorest 20% of places. In Gauteng, over 80% of regional GDP is generated in the three metro areas of Johannesburg, Tshwane, and Ekurhuleni. However, neoclassical growth theory predicts that poor localities, or regions, will grow faster than rich ones, leading to economic convergence over time. Using ward-level median household income calculated from census data for 2001 and 2011, this chapter tests this assertion in the ten-year period between the censuses. The chapter employs spatial econometric techniques to generate exploratory spatial data analysis and measure unconditional (or beta) convergence parameters. While exploratory spatial analysis did not clearly indicate either unconditional convergence or divergence, spatial models suggested a divergence rate of 0.7% between the two censuses. The growth rate of divergence is significantly clustered, with the north-west and south-west of Gauteng having experienced clusters of higher growth rates of ward-level median household income. There are also pockets of high growth rates of median household income in central Tshwane, Midvaal, and Merafong City. Clusters of high growth rates are also visible in the suburbs around Sandton, Midrand, Bryanston, and Fourways. Pockets of low growth rates of median household income are visible in the areas around Ennerdale and Poortje in the south of Johannesburg. Implications for policy are suggested regarding spatial targeting efforts by government.

Keywords

Inequality Economic convergence Spatial analyses Gauteng City-Region 

Notes

Acknowledgments

Christian Hamann is thanked for median household income calculations and preparation of the accompanying maps/figures. The useful comments of the two reviewers who read an earlier version of this chapter are acknowledged.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.University of the Witwatersrand, Gauteng City-Region Observatory (GCRO), a partnership between the University of Johannesburg, the University of the Witwatersrand, Johannesburg, the Gauteng Provincial Government and organized local governmentJohannesburgSouth Africa

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