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

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The Changing Space Economy of City-Regions

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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.

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Notes

  1. 1.

    This section relies primarily on Kim (2008) who provides a good summary of theories of spatial inequality.

  2. 2.

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

  3. 3.

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

  4. 4.

    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).

  5. 5.

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

  6. 6.

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

  7. 7.

    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.

  8. 8.

    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.

References

  • ANC (African National Congress). (1994). Reconstruction and development programme: A policy framework. Johannesburg: Umanyano.

    Google Scholar 

  • Anselin, L. (2005). Exploring spatial data with GeoDaTM: A workbook. Urbana: Center for Spatially Integrated Social Science.

    Google Scholar 

  • Anselin, L., Syabri, I., & Kho, Y. (2006). GeoDa: An introduction to spatial data analysis. Geographical Analysis, 38(1), 5–22.

    Article  Google Scholar 

  • Banerjee, A. V., & Iyer, L. (2005). History, institutions and economic performance: The legacy of colonial land tenure systems in India. American Economic Review, 95, 1190–1213.

    Article  Google Scholar 

  • Barro, R. et.al (1991). Economic growth in a cross-section of countries. Quarterly Journal of Economics, 106, 407–443.

    Article  Google Scholar 

  • Barro, R. J., & Sala-i-Martin, X. (1992). Convergence. Journal of Political Economy, 100(2), 223–251.

    Article  Google Scholar 

  • Barro, R. J., & Sala-i-Martin, X. (1995). Economic growth. New York: McGraw-Hill.

    Google Scholar 

  • Barro, R. J., Sala-i-Martin, X., Blanchard, O. J., & Hall, R. E. (1991). Convergence across states and regions. Brooking Institution Papers on Economic Activity, 1, 107–182.

    Article  Google Scholar 

  • Bernat, G. A. (2001). Convergence in state per capita personal income, 1950–99. Survey of Current Business, 81(6), 36–48.

    Google Scholar 

  • Bernstein, A. (Ed.). (2010). Poverty and inequality: Facts, trends, and hard choices. Edited proceedings of Round Table No. 15. Johannesburg: Centre for Development and Enterprise (CDE).

    Google Scholar 

  • Bhorat, H., & Kanbur, R. (2006). Poverty and policy in post-apartheid South Africa. Pretoria: HSRC Press.

    Google Scholar 

  • Bhorat, H., & Van der Westhuizen, C. (2008). Economic growth, poverty and inequality in South Africa: The first decade of democracy. Paper commissioned by The Presidency for the 15 year review process. Cape Town: University of Cape Town (Development Policy Research Unit).

    Google Scholar 

  • Bosch, A., Rossouw, J., Claassens, T., & Du Plessis, B. (2010). A second look at measuring inequality in South Africa: A modified Gini coefficient. Working Paper No. 58. Durban: University of KwaZulu-Natal (School of Development Studies).

    Google Scholar 

  • Bourguignon, F. (2004). The poverty-growth-inequality triangle. Washington, D.C.: World Bank.

    Google Scholar 

  • Brand, D., & Heyns, C. (Eds.). (2005). Socio-economic rights in South Africa. Pretoria: University of Pretoria Law Press.

    Google Scholar 

  • Bruhn, M. (2008). Good, bad, and ugly colonial activities: Studying development across the Americas (Vol. 334). Washington, D.C.: World Bank.

    Book  Google Scholar 

  • Canaleta, C. G., Arzoz, P. P., & Garate, R. M. (2002). Structural change, infrastructure and convergence in the region of the European Union. European Urban and Regional Studies, 9(2), 115–135.

    Article  Google Scholar 

  • Deaton, A. (1997). The analysis of household surveys: A micro-econometric approach to development policy. Washington, D.C.: World Bank.

    Book  Google Scholar 

  • Durlauf, S., & Quah, D. T. (1999). The new empirics of economic growth. In J. Taylor & M. Woodford (Eds.), Handbook of macroeconomics (Part A) (pp. 235–308). North Holland: Elsevier.

    Google Scholar 

  • Everatt, D. (2003). The politics of poverty. Bangladesh e-Journal of Sociology, 2(1), 16–31.

    Google Scholar 

  • Gumede, V. (2011). Social and economic inclusion in post-apartheid South Africa. In J. Hofmeyr (Ed.), From inequality to inclusive growth: 2011 transformation audit (pp. 88–94). Cape Town: Institute for Justice and Reconciliation.

    Google Scholar 

  • Henderson, J. V. (2002). Urbanization in developing countries. World Bank Research Observer, 17(1), 89–112.

    Article  Google Scholar 

  • Jenkins, S. P., & Micklewright, J. (2007). New directions in the analysis of inequality and poverty. ISER Working Paper 2007–11. Colchester: University of Essex.

    Google Scholar 

  • Kanbur, R., & Venables, A. J. (2005). Spatial inequality and development. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Kapur, S., & Kim, S. (2006). British colonial institutions and economic development in India. NBER Working Paper #12613. Cambridge, MA: National Bureau of Economic Research.

    Google Scholar 

  • Kim, S. (2007). Institutions and U.S. regional development: A study of Massachusetts and Virginia. NBER Working Paper #13431. Cambridge, MA: National Bureau of Economic Research.

    Google Scholar 

  • Kim, S. (2008). Spatial inequality and economic development: Theories, facts, and policies. Working Paper No. 16. Washington: Commission on Growth and Development.

    Google Scholar 

  • Krugell, W. F. (2005). The geographical economy of South Africa. Unpublished thesis, North West University, Potchefstroom.

    Google Scholar 

  • Krugell, W. F., Koekemoer, G., & Allison, J. (2005). Convergence or divergence of South African cities and towns? Evidence from kernel density estimates. Paper Presented at the Biennial Conference of the Economic Society of South Africa, Durban.

    Google Scholar 

  • Krugell, W., & Naudé, W. A. (2005). The geographical economy of South Africa. Journal of Development Perspectives, 1, 85–128.

    Google Scholar 

  • Lall, S., & Yilmaz, S. (2001). Regional economic convergence: Do policy instruments make a difference? The Annals of Regional Science, 35(1), 153–166.

    Article  Google Scholar 

  • Leibbrandt, M., Wegner, E., & Finn, A. (2011). The policies for reducing income inequality and poverty in South Africa. Southern Africa Labour and Development Research Unit Working Paper No. 64. Cape Town: University of Cape Town (SALDRU).

    Google Scholar 

  • Leibbrandt, M., Woolard, I., Finn, A., & Argent, J. (2010). Trends in African income distribution and poverty since the fall of apartheid. OECD Social, Employment and Migration Working Paper No, 101. Paris: OECD Publishing.

    Google Scholar 

  • Leibbrandt, M., Woolard, C., & Woolard, I. (2009). Poverty and inequality dynamics in South Africa: Post‐apartheid developments in the light of the long‐run legacy. In J. Aron, B. Kahn, & G. Kingdon (Eds.), South African economic policy under democracy, Chap. 10. Oxford: Oxford University Press.

    Google Scholar 

  • Lerman, R. I., & Yitzhaki, S. (1985). Income inequality effects by income source: A new approach and applications to USA. Review of Economics and Statistics, 67, 151–156.

    Article  Google Scholar 

  • Matthews, S. A. (2006). GeoDa and spatial regression modeling. Center for Spatially Integrated Social Science, Population Research Institute. University of California, Santa Barbara. http://ibis.geog.ubc.ca/~brian/workshop/GeoDa_Spatial_Regression.pdf. Santa Barbara, California, USA. Accessed April 27, 2017.

  • Møller, V. (2007). Quality of life in South Africa: The first ten years of democracy. Grahamstown: Institute of Social and Economic Research.

    Google Scholar 

  • Naudé, W. A., & Krugell, W. F. (2003). An enquiry into cities and their role in sub-national economic growth in South Africa. Journal of African Economies, 12(4), 476–499.

    Article  Google Scholar 

  • Naudé, W. A., & Krugell, W. F. (2004). An enquiry into cities and their role in sub-national economic growth in South Africa. WIDER Research Paper RP2004/08. Helsinki: UNU-WIDER.

    Google Scholar 

  • Nel, E., & Rogerson, C. M. (2009). Re-thinking spatial inequalities in South Africa: Lessons from international experience. Urban Forum, 20, 141–155.

    Article  Google Scholar 

  • Nel, E., & Rogerson, C. M. (2016). Re-engaging with spatial economic development: The recent experience of regional and local economic development in South Africa. Local Economy, 31(1–2), 3–8.

    Article  Google Scholar 

  • Niehues, J. (2011). Income inequality, inequality of opportunity and redistributive policies. Unpublished Ph.D. thesis, University of Cologne.

    Google Scholar 

  • NPC (National Planning Commission). (2011). National development plan: Vision for 2030. Pretoria: National Planning Commission.

    Google Scholar 

  • Puga, D., & Venables, A. J. (1999). Agglomeration and economic development: Import substitution vs. trade liberalisation. Economic Journal, 109, 292–311.

    Article  Google Scholar 

  • Ravallion, M. (2001). Growth, inequality and poverty: Looking beyond averages. World Development, 29(11), 1803–1815.

    Article  Google Scholar 

  • Republic of South Africa. (1996). The Constitution of the Republic of South Africa No. 108 of 1996.

    Google Scholar 

  • Republic of South Africa. (2003). Broad-based black economic empowerment (BBBEE). Pretoria: Department of Trade and Industry.

    Google Scholar 

  • Republic of South Africa. (2004). Expanded Public Works Programme (EPWP). Pretoria: Department of Public Works.

    Google Scholar 

  • Republic of South Africa. (2006). Accelerated and shared growth initiative for South Africa (AsgiSA). Pretoria: Presidency.

    Google Scholar 

  • Republic of South Africa. (2010). The new growth path: The framework. Pretoria: Economic Development Department.

    Google Scholar 

  • Rey, S. J., & Montouri, B. D. (1999). U.S. regional income convergence: A spatial econometric approach. Regional Studies, 33(2), 143–156.

    Article  Google Scholar 

  • Rogerson, C. M., & Nel, E. (2016). Redressing inequality in South Africa: The spatial targeting of distressed areas. Local Economy, 31(1–2), 28–41.

    Article  Google Scholar 

  • Romer, D. (1996). Advanced macroeconomics. New York: McGraw-Hill.

    Google Scholar 

  • Sala-i-Martin, X. (1996). Regional cohesion: Evidence and theories of regional growth and convergence. European Economic Review, 40, 1325–1352.

    Article  Google Scholar 

  • Salardi, P. (2005). How much of Brazilian inequality can we explain? An attempt of income differentials decomposition using the PNAD 2002. http://www-3.unipv.it/webdept/prin/workpv05.pdf. Accessed February 10, 2017.

  • Seekings, J. (2007). Poverty and inequality after apartheid. Paper prepared for the Second ‘After Apartheid Conference’, Yale University, 27–28 April.

    Google Scholar 

  • Solow, R. M. (1956). A contribution to the theory of economic growth. The Quarterly Journal of Economics, 70(1), 65–94.

    Article  Google Scholar 

  • StatsSA (Statistics South Africa). (2001). Census. Pretoria: Statistics South Africa.

    Google Scholar 

  • StatsSA (Statistics South Africa). (2011). Census. Pretoria: Statistics South Africa.

    Google Scholar 

  • StatsSA (Statistics South Africa). (2015). Census 2011: Income dynamics and poverty status of households in South Africa. Pretoria: Statistics South Africa.

    Google Scholar 

  • Temple, J. (1999). The new growth evidence. Journal of Economic Literature, 37, 112–156.

    Article  Google Scholar 

  • Tregenna, F. (2011). Halving poverty in South Africa: Growth and distribution aspects. Distribution implications of halving poverty in South Africa. Working Paper No 2011/60. Helsinki: UNU-WIDER.

    Google Scholar 

  • Tregenna, F., & Tsela, M. (2012). Inequality in South Africa: The distribution of income, expenditure and earnings. Development Southern Africa, 29(1), 35–61.

    Article  Google Scholar 

  • UNDP (United Nations Development Programme). (2015). The millennium development goals report 2015. New York: United Nations Publications.

    Google Scholar 

  • Van der Berg, S. (2010). The demographic and spatial distribution of inequality. In Poverty and Inequality: Facts, Trends and Hard Choices. Centre for Development and Enterprise Round Table Paper, (15). Johannesburg: Centre for Development and Enterprise.

    Google Scholar 

  • Van der Berg, S., & Louw, M. (2004). Changing patterns of South African income distribution: Towards time series estimates of distribution and poverty. South African Journal of Economics, 72(3), 546–572.

    Article  Google Scholar 

  • Woolard, I. (2002). An overview of poverty and inequality in South Africa. Working paper prepared for Department for International Development (DFID) (SA), July. Pretoria: DFID.

    Google Scholar 

  • Woolard, I., Leibbrandt, M., & McEwen, H. (2009). The persistence of high income inequality in South Africa: Some recent evidence. In J. Hofmeyr (Ed.), Recession and recovery. Cape Town: Institute for Justice and Reconciliation.

    Google Scholar 

  • World Bank. (2009). World development report 2009: Reshaping economic geography. Washington, D.C.: World Bank.

    Google Scholar 

  • SALDRU (Southern Africa Labour and Development Research Unit). (Various dates). National income dynamics study. Cape Town & Pretoria: Department of Planning Monitoring and Evaluation.

    Google Scholar 

  • Young, A. T., Higgins, M. J., & Levy, D. (2008). Sigma convergence versus beta convergence: Evidence from U.S. county-level data. Journal of Money, Credit and Banking, 40(5), 1083–1093.

    Article  Google Scholar 

  • Yusuf, F., Martins, J. M., & Swanson, D. A. (2014). Methods of demographic analysis. New York: Springer.

    Book  Google Scholar 

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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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  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 government, Private Bag 3, WITS, Johannesburg, 2050, South Africa

    Koech Cheruiyot & Darlington Mushongera

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  1. Koech Cheruiyot
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  2. Darlington Mushongera
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Correspondence to Koech Cheruiyot .

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  1. University of the Witwatersrand, Gauteng City-Region Observatory, a partnership between the University of Johannesburg, The University of the Witwatersrand, the Gauteng Provincial Government and organized local government, Johannesburg, South Africa

    Koech Cheruiyot

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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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  • DOI: https://doi.org/10.1007/978-3-319-67483-4_8

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