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Analysis of the results in the 1999 October Household Survey and the 2002 Labour Force Survey
suggests that the number of people in the bottom two expenditure classes (R0–R399 and
R400–R799 per household per month) increased by about 4,2 million over the period. As the
boundaries of these expenditure classes remained constant in nominal terms, there is a likelihood
that the number of people in poverty will have increased as well. This article attempts to discover
whether this is indeed the case. The possible increase in the number of people in poverty is not
equal to the increase in the number of people in these two expenditure categories. Rather, it is
equal to the difference between the numbers of people in poverty in the two years. Our first crude
estimate of the maximum potential number of ‘new’ poor suggests that it could be as high as 4,5
million. This estimate, which excludes any adjustments for possible underreporting of expenditure,
child cost economies and household economies of scale, and the ‘social wage’, is whittled
down as we attempt to make the relevant allowances. Responding to claims that poverty is
increasing in the country, the government has pointed to a failure to consider the contribution
of the social wage to the alleviation of poverty. Accordingly, we have also attempted to estimate
the impact of the social wage.
Introduction
As the governing party, the African National Congress (ANC) knows full well that
combating poverty is its most important task. Not surprisingly, the government and
party spokespeople are extremely sensitive to suggestions that poverty in South Africa
is worsening. Briefing Parliament’s communications committee on the work of the
Government Communication and Information System (GCIS) in advance of a debate
in the house earlier this year on ‘whether conditions in South Africa had improved
since the democratic elections in 1994’, its CEO, Joel Netshitenzhe, said that the GCIS
‘had to correct mistaken views that the poor were worse off than they were during
apartheid years’ (Business Day, 2003). He is quoted as saying that:
…the tide had turned on the unemployment front as the economy was
beginning to create jobs. A ‘social wage’ had also been introduced,
reflecting government’s efforts to deal with poverty. This had contributed
to an improved quality of life. The social wage included social grants, tax
relief, the provision of free basic services. In addition, the acquisition of
human rights had also improved the quality of people’s lives. While partial
data and focus on single points in time may attract shallow claims of no
delivery and increasing poverty, a contrary conclusion follows from a rounded picture of trends including the social wage, tax relief and social
grants over and above cash income from employment.
If by tax relief, Netshitenzhe means the reductions in income tax rates made over the
last several years, then these are of limited relevance to the people with this study is
concerned. None of the households from which they come pay income tax. If tax
reductions have had some impact on the wellbeing of poor households, it is most likely
to have been via remittances. Given the relatively small number of remittances
received, the effect is unlikely to have been very large. This is a matter that requires
further research.
By about 2000, analyses of poverty and income inequality based on, or linked to, the
1996 Population Census and the 1995 Income and Expenditure Survey (IES) had
reached the end of the road – further developments awaited the publication of the IES
results for 2000. Taking the analyses as far as they would go, most commentators
seemed to agree that between-group inequalities have fallen, while within-group
inequalities have risen. Having concluded thus, the examination of South Africa’s
changing income distribution in the period 1991–6 by Whiteford & Van Seventer
(2000:28) argues that:
…the rise in inequality within population groups and within society as a
whole is driven, on the one hand, by rising employment of well-paid,
highly-skilled persons and, on the other hand, declining employment of
lower-paid, less-skilled persons who are forced into poorly remunerated
informal sector employment or into unemployment.
Posing the question of whether the trends they have detected ‘which occurred in all
population groups’ (ibid., 25) are likely to continue into the future the answer, they
insist, has to be in the affirmative. Their analysis of labour market processes, and
projections that one of the authors made in another study, has led them to predict that
(ibid., 28):
…the employment of highly skilled persons will continue to rise while the
employment of less skilled persons will decline, resulting in rising unemployment.
Unless there is a fundamental shift in the path along which the
economy is moving, there is little hope for a reduction in inequality and
income poverty.
Up to the mid-1990s, most households (72 per cent of all households and 64 per cent
of African households) contained no unemployed people. By 1999, these proportions
had fallen to 64 and 57 per cent, respectively. They fell still further, reaching 58 and
52 per cent, respectively, by 2002. Research (Leibbrandt et al., 2001:48) suggests that:
…most household-level inequality [inequality between households] is
driven by income dynamics within households with no unemployed members
because most households do not have unemployed members and
households with unemployed members tend to be crowded below the
poverty line at the lower end of the household income distribution.
This conclusion no longer holds. Rising unemployment in the period since 1996 makes
it likely that Whiteford & Van Seventer’s prediction on poverty and inequality would
have been fulfilled. Not only has the required fundamental shift not taken place – the
numbers of unemployed have climbed to record levels, almost doubling between 1995
and 2002. With some large proportion of the unemployed located in the lowest expenditure categories (we discuss the numbers below), it seems almost inevitable that
poverty would have worsened.
Unfortunately, the statistical basis on which reliable judgements about poverty and
inequality in the period after 1996 were to be based – the 2000 IES (StatsSA, 2000b)
– turned out to be deeply flawed. An analysis of its results, presented in Earning and
spending in South Africa (StatsSA, 2002), which shows an increase in poverty and
inequality over the period 1995–2000, was dismissed by the government.
This article uses a variant of the headcount method to attempt to discover what
happened to the numbers of people in poverty between 1999 and 2002. There is an
excellent discussion of the advantages and limitations of the various estimates of
poverty that can be made in Woolard & Leibbrandt (2001). By comparison with that
work, the estimates presented in this study are crude in the extreme. We make no
apology for this – our intention is to measure the extent of poverty between two
well-defined groups in society, not its intensity. We are also aware of the difficulties
of using expenditure estimates. The way in which we deal with this difficulty will
become clear below. We could, in addition, have performed a consistency test on our
results by attempting to estimate the incomes of the households whose results we are
working with in the study.
The usual technique for conducting a headcount is to establish a poverty line (PL) and
then to count the number of individuals whose expenditure or income falls below this
level. In order to do so, data on the distribution of households by expenditure level are
required, as are data on the age distribution of individuals within households. The latter
are used to adjust the size of those households containing children to lower costs (i.e.
estimate adult equivalents), and to make allowance for economies of scale in those
households containing more than one individual. The number of people in poverty is
the total number of people in those households below the PL. Rather obviously, to
measure changes in poverty, one estimates and compares the numbers below the PL at
the beginning and end of the period in which one is interested or for which one has
the relevant data.
Each study will have peculiarities imposed upon it by both the nature of the inquiry
undertaken and by the availability of data. In the case of the present study, a major
feature is the allowance to be made for in-kind consumption (the social wage). Another
feature of this study is that rather than attempting to measure changes in poverty in the
nation as a whole, it aims to count the total number of people in poverty in the two
bottom expenditure categories, i.e. those in households where expenditure lies between
R0–R399 and R400–R799 per month, respectively.
As far as data constraints are concerned, although detailed information is available on
household composition from the relevant surveys, the Labour Force Survey (LFS) for
September 2002 (StatsSA, 2003) and the October Household Survey (OHS) for 1999
(StatsSA, 2000a), nothing is known about the distribution of households by expenditure
level. In order to overcome this hurdle, it has been necessary to construct the relevant
distributions by assumption. This is a less hazardous process than may be thought –
estimates of the number of poor appear to be relatively insensitive to quite wide
variations in the assumed distributions of expenditure. This is tested by allowing mean
expenditure in the lowest category (R0–R399 per month) to vary.
The investigation was conducted in stages:
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An estimate was made of the change in the number of poor between 1999–2002,
using the data extracted from the two data sets.
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Allowing for child costs and for household economies of scale, an estimate of
maximum potential consumption levels for different types of household was made.
Estimates were made of daily maximum potential consumption levels of people
living in households containing adults and children, in the bottom two expenditure
categories, while allowing for underreporting of expenditure. The social wage was
still excluded.
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An attempt was made to value the social wage. Maximum potential consumption
levels were established, allowing for child costs and household economies of scale,
including the social wage but not allowing for underreporting errors.
-
Estimates of changes in the numbers of the poor, taking the social wage into
account, were made. The estimates show the effects of underreporting of household
expenditure on the likely numbers of ‘new poor’.
Our results, the basic data from which they were generated and the simple devices used
to perform operations such as adult equivalence calculations, social wage valuation and
expenditure underestimation corrections, are contained in four linked spreadsheets
called ‘Poverty-0.xls’, ‘Poverty-50.xls’, ‘Poverty-100.xls’ and ‘Poverty-150.xls’. Using
these spreadsheets, a large number of simulations that deliver estimates of the numbers
in poverty may be performed. These make use of a wide variety of assumptions about
some of the variables about which our knowledge is hazy. The spreadsheets are
available on the website of the School of Development Studies at the University of
Natal. Using them, a person can make any changes to the assumptions that we have
made. By this means, one can test the sensitivity of our results to variations in those
assumptions.
Footnote:
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Respectively, Research Fellow, School of Development Studies; and Lecturer, Division of
Economics, both of the University of Natal, Durban, South Africa. We are grateful for helpful
comments made by the discussant of our paper, David Fryer of Rhodes University, to Nicoli
Nattrass of the University of Cape Town, to Ingrid Woolard of the Human Sciences Research
Council (HSRC) and to Michael Noble of the Centre for the Analysis of South African Social
Policy (CASASP) at the University of Oxford. Thanks are due as well to colleagues and friends
who attended a seminar in the School of Development Studies at the University of Natal, where
we test-flew the pre-conference version of the article. The usual disclaimer applies – the
remaining errors are all our own.
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