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Inequality Traps and Human Capital Accumulation in South Africa

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Miquel Pellicer; Vimal Ranchhod (2012). Inequality Traps and Human Capital Accumulation in South Africa. Paper presented at 'Towards Carnegie III', University of Cape Town, 3-7 September 2012. University of Cape Town (conference paper).
Type conference paper
Scope Post-1994 South African economy
Method mixed
Period studied 2002–2011
Regions South Africa, Cape Metropolitan Area
Themes inequality poverty unemployment, education human capital, labour markets wages, comparative theory, transition post apartheid
Citation key pellicer2012

Argument

The paper reviews three theoretical frameworks linking inequality and education investment: perfect markets, imperfect credit markets, and social externalities. It asks which best fits South Africa, using NIDS Wave 1 (2008) and CAPS Wave 1 (2002). It finds most support for credit constraints, together with unequal primary and secondary schooling that leaves poor youth ineligible for tertiary study. It concludes South Africa is plausibly caught in an inequality trap running through tertiary education. It proposes policies on financial aid information and registration fees, intermediate FET qualifications, and school quality and teacher quality, rather than integrating poor pupils into good schools.

Evidence and method

NIDS Wave 1 (2008, about 30,000 individuals, nationally representative) for returns to education, tertiary attainment by per capita household income quintile, and reasons for non-enrolment. CAPS Wave 1 (2002, about 4,800 youth aged 14-22 in Cape Town) for career aspirations and standardized literacy/numeracy scores. Also cited: other studies (Lam 1999, Branson et al. 2009, Garlick 2012, Wittenberg 2005) and preliminary focus groups with matric students.

Findings

  • Returns to a post-secondary qualification are very high, and employment rates rise sharply with schooling among 25-29 year olds. (p. 16)

    getting a matric will triple your expected earnings, while moving from a matric to some tertiary qualification will increase your expected earnings by about 167%.

  • Few young adults hold tertiary qualifications, while about three in five have no matric. (p. 16)

    the fraction with any type of tertiary qualification in this group is approximately 1 in 6. In fact, the largest group are people who never finished secondary school, at about 3 in 5.

  • Tertiary attainment is strongly skewed to the richest quintile, consistent with credit constraints. (p. 17)

    by age 24 the proportion of youth in the richest households remains double that of those in the second richest quintile, at 31.4%.

  • Financial cost is a major reason poorer youth are not enrolled, much less so for the richest. (p. 18)

    somewhere between 1 in 3 and 1 in 4 respondents left their education due to the financial costs of remaining in school, in quintile 4 this number drops to about 1 in 6.

  • The authors judge the data to favour credit constraints over perfect credit markets. (p. 19)

    we find clear evidence that returns to education are very high, that richer students are much more likely to attain a tertiary qualification, and that financial costs are a significant deterrent to poorer students.

  • Aspirations do not appear to be depressed among poor youth, so there is no clear evidence of aspiration-based traps. (p. 20)

    even the poorest youth expect to be doctors and lawyers, suggests that aspirations are not being negatively affected through social externalities.

  • Scholastic aptitude differs by income already in early secondary school, and gaps widen with age. (p. 21)

    the distributions are clearly different, and unambiguously improve with income. Even amongst the youngest CAPS respondents, these differences are already pronounced

  • South Africa is characterised as caught in an inequality trap operating mainly via tertiary education. (p. 23)

    South Africa is caught in an inequality trap where high inequality leads to low levels of skill accumulation, which in turn consolidates the high levels of inequality.

  • Credit constraints bind for only a minority, because most poor students are ineligible for university. (p. 23)

    credit constraints in the tertiary decision are likely to apply to a minority of the population and are unlikely to bring about dramatic improvements in access

  • Teaching is rarely chosen as a career, which the authors link to cost of qualification and low pay. (p. 26)

    fewer than 10 respondents, out of approximately 4800, plan to be teachers at the age of 30.