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

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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

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Fig. 8.9
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Notes

  1. 1.

    SALDRU is the Southern Africa Labour Development Research Unit, based at the University of Cape Town, South Africa.

  2. 2.

    This was formerly the October Household Survey (OHS) and more recently the Labour Force Survey (LFS).

  3. 3.

    These are eradicate extreme poverty and hunger, achieve universal primary education, promote gender equality and empower women, reduce child mortality, improve maternal health, combat HIV/AIDS, malaria and other diseases, ensure environmental sustainability, and develop a global partnership for development (UNDP 2015).

  4. 4.

    This chapter works with the 2011 municipal boundaries. The municipal boundaries were changed after the manuscript had been completed.

  5. 5.

    The National Income Dynamics Study (NIDS) is being executed by SALDRU, which is based at the University of Cape Town, South Africa.

  6. 6.

    Statistics South Africa (StatsSA) presents income data in 12 income bands or groups. The calculated median household income excluded the no-income group, a group StatsSA (2015) speculates, are either households who did not want to divulge their income information or poor households with no, or irregular income. The authors had no way validate StatsSA’s (2015) assertion.

  7. 7.

    Estimation results showed that there was residual heteroscedasticity from spatial models. Attempts to solve the residual heteroscedasticity problem using various transformations and specifications of the estimation equation were fruitless. The residual heteroscedasticity could be explained by data belonging to irregular spatial units, the existence of systematic regional differences in the data, and the presence of continuous spatial drift of parameters in the model (Matthews 2006). Nonetheless, this is not a serious issue since estimated coefficients are still unbiased.

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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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Cheruiyot, K., Mushongera, D. (2018). Testing Economic Growth Convergence and Its Policy Implications in the Gauteng City-Region. In: Cheruiyot, K. (eds) The Changing Space Economy of City-Regions. GeoJournal Library(). Springer, Cham. https://doi.org/10.1007/978-3-319-67483-4_8

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