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Development, Poverty and Inequality: A Spatial Analysis of South African Provinces

Author

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  • Carlos P. Barros
  • Rangan Gupta

    (ISEG – Lisbon School of Economics and Management, Portugal
    University of Pretoria, South Africa)

Abstract

The literature that relates average income rise of the economy with increase in average income of the poorest population is well established. However poverty continues to be predominant in Africa indicating that income rise is not sufficient to decrease poverty. As a middle-income country, South Africa has consistently held the unappealing record of the country with the most unequal income distribution in the world. The increasing inequality in South Africa represents a substantial policy challenge to policymakers as it affects socio-political stability and economic development. This paper investigates the relation between growth, poverty and inequality in South Africa at the regional level using data over the annual period of 1996-2013. We adopt a spatial econometric model motivated by two noteworthy facts: (i) the high rate of poverty in South Africa and (ii) the high levels of poverty and inequality in the studied regions. In addition we account for the spatial dependence between regions which might affect the relationship between growth and poverty. Also, we develop and test five hypotheses and account for the possible endogeneity in specified model. The results reveal that the autoregressive parameter, lagged poverty is positive and statistically significant in all cases, which supports the use of a dynamic panel data model. Furthermore it reveals poverty increases along the period and the autocorrelation poverty variable is also found to be positive and statistically significant. The trend also reveals that poverty increases but at a decreasing rate, with the latter indicated by the square trend term. Log per capita income increases poverty and is statistically significant. Log GDP Growth is also statistically significant but only in the Arellano-Bond model, signifying that it is an endogenous variable. Log Employment increases poverty and is statistically significant. The Gini indicator (a measure of inequality) is found to increase poverty; signifying that poverty and inequality are affecting each other. This result signifies that poverty is increasing in South Africa at decreasing rate. Moreover the economic variables (for example, income per capita, GDP growth and employment) are also decreasing poverty. Therefore it appears that South Africa is on the right road to decrease poverty, but the spatial slipovers on poverty implies that the government needs an active anti-poverty policy to attack this persistent problem, since it cannot rely on economy growth to overcome it.

Suggested Citation

  • Carlos P. Barros & Rangan Gupta, 2017. "Development, Poverty and Inequality: A Spatial Analysis of South African Provinces," Journal of Developing Areas, Tennessee State University, College of Business, vol. 51(1), pages 19-32, January-M.
  • Handle: RePEc:jda:journl:vol.51:year:2017:issue1:pp:19-32
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    Cited by:

    1. Byron Quito & María de la Cruz del Río‐Rama & José Álvarez‐García & Ronny Correa‐Quezada, 2022. "Impact factors and space‐time characteristics of income inequality in a global sample," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(6), pages 1850-1868, December.

    More about this item

    Keywords

    South Africa; poverty; inequality; spatial model;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E41 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Demand for Money
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development

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