Returns to Education in South Africa: A Retrospective Sensitivity Analysis of the Available Evidence

Keswell, Malcolm; Poswell, Laura

doi:10.1111/j.1813-6982.2004.tb00136.x

Cited by 50 publications

(46 citation statements)

References 44 publications

(10 reference statements)

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“…However, some of these averages will be biased by just a few outliers; for example, the return to higher education in South Africa was estimated to be as high as 51 per cent by Keswell and Poswell (2004). Moreover, the pattern of RORE by level of education varies by country.…”

Section: Literature Reviewmentioning

confidence: 98%

The Returns to Education in Africa: Some New Estimates

Barouni¹,

Broecke

2014

The Journal of Development Studies

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International audienceWe estimate the rate of return to education for 12 African countries using recent data and a range of methodologies, which we apply consistently across all countries. Our findings confirm that the return to basic education is the lowest (7-10 per cent). The returns to upper secondary and tertiary education are similar to one another (25-30 per cent). Accounting for the risk of joblessness increases these rates of return, particularly for basic education and for women at tertiary level. Our results at the country level suggest that great care should be taken in choosing the appropriate methodology to estimate rates of return

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Section: Literature Reviewmentioning

confidence: 98%

The Returns to Education in Africa: Some New Estimates

Barouni¹,

Broecke

2014

The Journal of Development Studies

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“…While the level of education obtained sends a signal to employers and thus influences the probability of employment, the convex returns to education, as found in the Mincerian earnings function for South Africa Keswell & Poswell, 2004), are evidence of higher productivity being associated with higher attainment. The second panel of Figure 4 shows the conditional log of the wage (i.e.…”

Section: The Labour Market and Inequalitymentioning

confidence: 99%

Inequality, poverty and prospects for redistribution

Berg

2014

Development Southern Africa

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This paper demonstrates that poverty and inequality trends can diverge. It then discusses inequality trends and shows that, despite measurement issues, there is consensus that inequality is very high and has been rising over much of the post-transition period. Due to rising inequality within all groups, and particularly the black population, and lower inequality between race groups, within-group inequality has become the dominant form of inequality. That does not, however, detract from the fact that inequality between groups is still very large. High income inequality largely stems from inequality in access to wage income, due more to wage inequality than to unemployment. A Gini coefficient for wage income amongst the employed of above 0.60 effectively sets a floor to overall income inequality. The high wage premium to educated workers derives from a combination of a skills shortage at the top end of the educational spectrum, driving up their wages, and a surfeit of poorly-educated workers competing for scarce unskilled jobs dampening unskilled wages; if the unemployed were to find jobs, it would be in this bottom part of the wage distribution, and consequently this would not much reduce wage inequality. A continuation of the historical pattern whereby only a small segment of the population obtained good schooling would leave the structures underlying the large wage premium unaltered. The time frame for substantial inequality reduction is thus necessarily a long one, while poverty reduction efforts should not wait for this to occur.

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“…In contrast, wage returns to higher education seem to be very high: Branson et al (2009) and Keswell and Poswell (2004) argue that marginal returns to schooling are increasing with schooling level and are as high as 50% per year at the tertiary level. Altogether, this set of facts -low attendance and high return -is compatible with some forms of constraint in access to higher education.…”

Section: The Eduloan Scheme In the South African Contextmentioning

confidence: 99%

“…We are thus unsure whether this very demand has been accepted and we don't know if we should relate this demand to enrollment the current year or the next. As a result, our baseline estimation excludes observations for which the only application of the year was posted in November 15 or December (we then keep 86% of our sample). We will test, as a robustness check, that results are not sensitive to inclusion of those observations.…”

Section: Data Constraintsmentioning

confidence: 99%

Student Loans: Liquidity Constraint and Higher Education in South Africa

Gurgand

Lorenceau

Melonio³

2011

SSRN Journal

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Empirical evidence that access to higher education is constrained by credit availability is limited and usually indirect. This paper provides direct evidence by comparing university enrollment rates of South African potential students, depending on whether they get a loan or not to cover their registration fees, in a context where such fees are high. We use matched individual data from both a credit institution (Eduloan) and the Department of Education. Based on a regression discontinuity design using the fact that loans are granted according to a credit score threshold, we can estimate the causal impact of loan obtainment.We find that the credit constraint is substantial, as it decreases the enrollment rate into higher education by more than 20 percentage points in a population of student loan applicants. * We are very grateful to Herman Steyn and all Eduloan staff for providing invaluable data and many precisions and advices regarding the South African higher education system and their work on the field; and to Jean Skene and Dr. Qhobela from the Department of Education (DoE) for providing us with the HEMIS data. Thanks to Jocelyn Vass, Fabian Arends, Mariette Visser from HSRC for very valuable discussions and advice, and to Geneviève Michaud for assistance with the data. Special thanks also to the AFD team in South Africa. We are grateful to Clément de Chaisemartin, Eric Maurin and seminar participants at

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Returns to Education in South Africa: A Retrospective Sensitivity Analysis of the Available Evidence

Cited by 50 publications

References 44 publications

The Returns to Education in Africa: Some New Estimates

The Returns to Education in Africa: Some New Estimates

Inequality, poverty and prospects for redistribution

Student Loans: Liquidity Constraint and Higher Education in South Africa

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