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Spatial Change in the Concentration of Multidimensional Poverty in Gauteng, South Africa: Evidence from Quality of Life Survey Data

  • Samy Katumba
  • Koech Cheruiyot
  • Darlington MushongeraEmail author
Article
  • 22 Downloads

Abstract

The multidimensional poverty index (MPI) is generally credited for better capturing the various components of poverty. Where such indexes have a spatial component, opportunity arises for analyzing changes in the spatial concentration of multidimensional poverty over given periods across space. Using current available MPI data for Gauteng province, South Africa, we apply spatial statistical analysis techniques to measure the degree of spatial concentration, spread and orientation of poverty across the various wards. Results reveal distinct variations in concentration, spatial spread and orientation of poverty across the province. These results open up possibilities of spatially targeted state interventions for reducing poverty.

Keywords

Multidimensional poverty index Quality of Life Gauteng Standard deviational ellipse Spatial autocorrelation South Africa 

Notes

Acknowledgements

This work benefited from comments from colleagues in the GCRO in particular the QoL team that worked on the data.

References

  1. Alkire, S., & Foster, J. (2011). Understandings and misunderstandings of multidimensional poverty measurement. The Journal of Economic Inequality, 9, 289–314.CrossRefGoogle Scholar
  2. Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27, 93–115.CrossRefGoogle Scholar
  3. Anselin, L. (1996). The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In M. Fischer, H. J. Scholten & D. Unwin (Eds.), Spatial analytical perspectives on GIS in environmental and socioeconomic sciences (pp. 111–125). London: Taylor and Francis.Google Scholar
  4. Baud, I. S. A., Sridharan, N., & Pfeffer, K. (2008). Mapping urban poverty for local governance in an Indian mega-city: The case of Delhi. Urban Studies, 45, 1385–1412.CrossRefGoogle Scholar
  5. Cheruiyot, K. (2018). City-regions and their changing space economies. In K. Cheruiyot (Ed.), The changing space economy of city-regions (pp. 1–24). Cham: Springer.CrossRefGoogle Scholar
  6. Cheruiyot, K., & Mushongera, D. (2018). Testing economic growth convergence and its policy implications in the Gauteng City-Region. In K. Cheruiyot (Ed.), The changing space economy of city-regions (pp. 213–239). Cham: Springer.CrossRefGoogle Scholar
  7. Cliff, A. D., & Ord, J. K. (1981). Spatial processes: Models & applications. London: Taylor & Francis.Google Scholar
  8. David, A., Guilbert, N., Hamaguchi, N., Higashi, Y., Hino, H., Leibbrant, M., et al. (2018). Spatial poverty and inequality in South Africa: A municipality level analysis. AFD Research Papers Series, No. 2018-66, January.Google Scholar
  9. Epprecht, M., Minot, N., Dewina, R., Messerli, P., & Heinimann, A. (2008). The geography of poverty and inequality in the Lao PDR. Bern: Geographica Bernensia.Google Scholar
  10. Everatt, D. (2017). Quality of Life in the Gauteng City-Region, South Africa. Social Indicators Ressearch, 130, 71–86.CrossRefGoogle Scholar
  11. GCRO QoL. (2015). Quality of Life survey. http://www.gcro.ac.za/research/project/detail/quality-of-life-survey-iv-2015/. Accessed June 06, 2018.
  12. Kwenda, P., & Benhura, M. (2018). Poverty and inequality in the GCR: Inequalities in the GCR labour market. GCRO Research Report, Johannesburg.Google Scholar
  13. Lefever, D. Welty. (1926). Measuring geographic concentration by means of the standard deviational ellipse. American Journal of Sociology, 32, 88–94.CrossRefGoogle Scholar
  14. Moran, P. A. (1948). The interpretation of statistical maps. Journal of the Royal Statistical Society: Series B (Methodological), 10, 243–251.Google Scholar
  15. Mushongera, D., Zikhali, P., & Ngwenya, P. (2017). A multidimensional poverty index for Gauteng province, South Africa: Evidence from Quality of Life survey data. Social Indicators Research, 130, 277–303.CrossRefGoogle Scholar
  16. OECD. (2011). OECD territorial reviews: The Gauteng City-Region, South Africa 2011. Paris: OECD Publishing.  https://doi.org/10.1787/9789264122840-en.Google Scholar
  17. Okwi, P. O., Ndeng’e, G., Kristjanson, P., Arunga, M., Notenbaert, A., Omolo, A., et al. (2007). Spatial determinants of poverty in rural Kenya. Proceedings of the National Academy of Sciences, 104, 16769–16774.CrossRefGoogle Scholar
  18. Orford, S. (2004). Identifying and comparing changes in the spatial concentrations of urban poverty and affluence: A case study of inner London. Computers, Environment and Urban Systems, 28, 701–717.CrossRefGoogle Scholar
  19. Parilla, J., & Trujillo, J. L. (2015). South Africa’s global gateway: Profiling the Gauteng City-Region’s international competitiveness and connections. Global Cities Initiative, a Joint Project of Brookings and J P Morgan Chase.Google Scholar
  20. StatsSA. (2014). The South African MPI, Creating a multidimensional poverty index using census data. http://www.statssa.gov.za/publications/Report-03-10-08/Report-03-10-082014.pdf. Accessed October 04, 2017.
  21. StatsSA. (2017). Poverty Trends in South Africa, An examination of absolute poverty between 2006 and 2015. http://www.statssa.gov.za/publications/Report-03-10-06/Report-03-10-062015.pdf. Accessed October 04, 2017.
  22. Thongdara, R., Samarakoon, L., Shrestha, R. P., & Ranamukhaarachchi, S. L. (2012). Using GIS and spatial statistics to target poverty and improve poverty alleviation programs: A case study in northeast Thailand. Applied Spatial Analysis and Policy, 5, 157–182.CrossRefGoogle Scholar
  23. Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234–240.CrossRefGoogle Scholar
  24. Tseng, D. (2018). Poverty and inequality in the GCR: Income and expenditure analysis. GCRO Research Report, Johannesburg.Google Scholar
  25. Vista, B. M., & Murayama, Y. (2011). Spatial determinants of poverty using GIS-based mapping. In Y. Murayama & R. Thapa (Eds.), Spatial analysis and modeling in geographical transformation process (pp. 275–296). Dordrecht: Springer.CrossRefGoogle Scholar
  26. Wong, D. W. (1999). Geostatistics as measures of spatial segregation. Urban Geography, 20, 635–647.CrossRefGoogle Scholar
  27. Wong, D. W. (2003). Implementing spatial segregation measures in GIS. Computers, Environment and Urban Systems, 27, 53–70.CrossRefGoogle Scholar
  28. Yuill, R. S. (1971). The standard deviational ellipse; an updated tool for spatial description. Geografiska Annaler: Series B, Human Geography, 53, 28–39.CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Gauteng City-Region ObservatoryA Partnership Between the University of the Witwatersrand, University of Johannesburg, Gauteng Provincial Government and Organized Local GovernmentJohannesburgSouth Africa

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