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Flogging a dead horse:
Attempts by van der Berg et al to measure changes in poverty and inequality


Charles Meth

Southern Africa Labour and Development Research Unit (SALDRU)
University of Cape Town (UCT)

2007

SARPN acknowledges the SALDRU website as the source of this report: www.saldru.uct.ac.za
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Abstract1

This paper seeks an explanation for the large differences in the extent and severity of poverty published respectively in van der Berg et al (2005: 2007a) and Meth (2006b). Headcounts in 2004 suggested by van der Berg et al (2007a) exceed by five million, those reported by (Meth, 2006b).

Household survey respondents often under-report income (and expenditure). To address this, it is common (if not necessarily wise) to scale household survey income means until the grossed-up survey income totals are approximately the same as those yielded by the national accounts. The apparent reason for the differences between our respective poverty estimates lies in the poor quality of the income estimates in the surveys used by van der Berg et al as primary data source for estimating income distributions (by race). Scaling these survey estimates to make them consistent with the national accounts, it is argued, causes them to under-estimate the extent and severity of the poverty problem.

As part of their analysis of changes in the welfare of Africans in South Africa since the advent of democracy (and in support of their claim that poverty has fallen), van der Berg et al attempt to measure changes in the racial shares of remuneration. The present paper ends with a brief examination of some of the problems of doing so using Statistics South Africa household surveys (the Labour Force Surveys) as primary data source.

Welcomed by government because of the apparent progress they report in the fight against poverty, the possible consequences for anti-poverty policy (and for the poor) of the van der Berg et al figures being wrong are non-trivial.


Footnote:
  1. I am grateful to Murray Leibbrandt in the School of Economics in the University of Cape Town, who read and commented critically on this paper (the third in a series of papers on the topic). From the outset, he has been immensely supportive of a project that has tried to extract credible poverty estimates from Statistics South Africa’s Labour Force and General Household Surveys. It should go without saying, of course, that any errors in the present paper are my responsibility.


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