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The Lure of Ill-Fitting Unemployment Statistics: How South Africa’s Discouraged Work Seekers Disappeared From the Unemployment Rate


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Unemployment refuses unambiguous definition. Its statistical representation is always open to contestation, especially where labour markets differ from the Western-industrial norm. Why do countries adopt international standards even if they may fit local conditions poorly? South Africa is an exemplary case to answer this question. When Apartheid ended in the early 1990s, South African statisticians embraced the new emancipatory spirit. Their broad unemployment indicator defied international conventions but did justice to the marginalised Black population, and to Black women in particular. Since then, however, South Africa has fallen in line with the much narrower definition of the International Labour Organization (ILO), in spite of widespread criticism. Why? We find that ILO standards were not forced upon South Africa. Instead, South African statisticians themselves embraced international standards to repel charges of arbitrary or politically motivated numbers. Counterintuitively, international standards become alluring precisely when doubts about statistics’ fit with local conditions are the greatest.
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The Lure of Ill-Fitting Unemployment Statistics: How South Africas
Discouraged Work Seekers Disappeared From the Unemployment
Juliette Alenda-Demoutiez and Daniel Mügge
Department of Political Sciences, University of Amsterdam, Amsterdam, The Netherlands
Unemployment refuses unambiguous denition. Its statistical
representation is always open to contestation, especially where labour
markets dier from the Western-industrial norm. Why do countries
adopt international standards even if they may t local conditions
poorly? South Africa is an exemplary case to answer this question. When
Apartheid ended in the early 1990s, South African statisticians embraced
the new emancipatory spirit. Their broad unemployment indicator
deed international conventions but did justice to the marginalised
Black population, and to Black women in particular. Since then, however,
South Africa has fallen in line with the much narrower denition of the
International Labour Organization (ILO), in spite of widespread criticism.
Why? We nd that ILO standards were not forced upon South Africa.
Instead, South African statisticians themselves embraced international
standards to repel charges of arbitrary or politically motivated numbers.
Counterintuitively, international standards become alluring precisely
when doubts about statisticst with local conditions are the greatest.
Received 10 December 2018
Accepted 26 April 2019
International standards;
political economy; Sociology
of quantication; South
Africa; unemployment
For people who want to work, the inability to nd employment can be a source of enormous
hardship economically, socially and personally. For societies at large, widespread unemployment
is a fundamental political challenge. When labour market conditions are particularly dire, unemploy-
ment may be the central economic problem to be tackled. Eective policy and informed public
debate, in turn, hinge on an accurate understanding of the size and shape of the issue. Statistics
about unemployment are central to the ght against it.
Unemployment is not a natural category (Salais et al.1986). Nineteenth century labourers pushed
for censuses of the nascent working class to reveal its plight (Desrosières 1998). At their inception,
unemployment statistics were a weapon for class struggle. Since then, just how we should concep-
tualise joblessness has been contested: who is included in the gures and who is not, how much do
you have to work to fall in one or the other category, and so on (Baxandall 2004, Zimmermann 2006).
These measurement choices are highly consequential: they highlight or obscure changes in labour
markets and peoples working lives, and the statistics based on them guide policymakers and the
publics understanding (Gautié 2002, Hoskyns and Rai 2007). Unemployment statistics, in short, are
deeply political: their denitions create winners and losers, and they lead us to ask who writes
them in the rst place (Desrosières 1998).
© 2019 Informa UK Limited, trading as Taylor & Francis Group
CONTACT Juliette Alenda-Demoutiez
We know little about such indicator politics outside the OECD world. That is surprising. Labour
market conditions in many developing countries are strained, and in the absence of strong
welfare states, joblessness threatens people existentially.
Yet it is not obvious that the essentially
Western concept of unemployment (Garraty 1979, Topalov 1994) is well-suited to developing
country labour markets. Subsistence agriculture is widespread outside large cities. Labour markets
are highly segmented, often along racial or ethnic lines. And large parts of the population may
nd themselves in informal, precarious employment, below the statistical radar. These features com-
plicate labour market statistics, and they enlarge the scope for political ghts about them. At the
same time, poorer countries often have asymmetrical and fraught relationships with international
organisations, whose push for harmonised statistical standards may meet little enthusiasm on the
ground. It is not clear why developing countries would stick to international statistical standards at
odds with their socio-economic realities.
This article sets out to map and explain such unemployment indicator politics in South Africa. Job-
lessness has been an enormously political challenge in the country (Kingdon and Knight 2001).
Unemployment there is one of the highest in the world: dierent measurement approaches put it
somewhere between 26 and 38 percent in the rst quarter of 2018.
The central dierence
between these estimates lies in the treatment of discouraged work seekers, people who do not
count as unemployed following the ILO denition but would still like to work.
Over the past two decades, South Africa has increasingly embraced the narrow ILO denition of
unemployment and privileged it in its unemployment statistics even if it remains politically dis-
puted and arguably ill-suited to the country. Our central question is what has pushed South
African unemployment statistics in this surprising direction. We can break it down into a descrip-
tive-empirical as well as a more theoretical question: what have been the main political ghts over
unemployment statistics in South Africa since the mid-1990s? And which factors explain the
choices that have been made?
Counterintuitively, South Africa has embraced international standards not in spite of their limited
t with domestic conditions, but precisely because of these diculties. Dening and measuring
unemployment in South Africa is such a fraught endeavour that every practical solution has immedi-
ately invited plausible criticism. Politicians quickly cast doubt on ocial gures: political incumbents
in particular the African National Congress have criticised gures as too high; those in political
opposition or advocating for the labour movement have embraced the opposite position. These criti-
cisms have gnawed at the credibility of Statistics South Africa (Stats SA) the ocial oce for
national statistics even when the problem has not been the agencys competence and determi-
nation, but rather the fundamental mismatch between the structure of the South African society
and economy, and unemployment as a concept.
The ultimate choice for a narrow ocial denition has been driven by the wish to conform to inter-
national standards. The latter have not been forced on South Africa. Instead, they have been
embraced bottom-up to buttress South Africas credibility with the international community as
well as that of national statisticians vis-à-vis the political class, and to allow at least a supercial (if
ultimately misleading) comparability between South Africas labour market conditions and those
in the rest of the world.
This article builds on 25 interviews, conducted in 2018, with present and past South African stat-
isticians, labour and business representatives, researchers, politicians and consultants, as well as on a
range of primary documents about statistical debates and development there. It is structured as
follows: the next section outlines the main insights social scientists have gathered about the political
nature of unemployment indicators in Europe and North America and asks how well we should
expect them to travel to developing countries. In the body of this article we then detail the two
main phases in which South African unemployment statistics have been embattled and demonstrate
how the quest for legitimacy has driven Stats SA to embrace an unemployment denition that
matches local circumstances poorly. Our conclusions outline the implications of the South African
experience for our thinking about the politics of economic statistics more generally and in develop-
ing countries in particular.
The Politics of Unemployment Indicators
Ubiquitous as internationally harmonised economic indicators are these days, they had been devised
for domestic purposes: to evidence the plight of the nineteenth century working class in case of
unemployment (Salais et al.1986) and cost of living indicators (Stapleford 2009); to facilitate macro-
economic management in the case of gross domestic product (GDP), whose predecessors were
developed in the 1930s and 1940s (Lepenies 2013). Economic statistics, in other words, were
tailor-made for Western industrialised nations, and they had clear political purposes.
Their global spread only gathered pace after the Second World War (Ward 2004). International
organisations such as the International Labour Organisation (ILO), the United Nations, and later
the International Monetary Fund, the World Bank and the Organisation for Economic Co-operatio-
nand Development proselytised for their use and the developmentalist ideas underlying them
(Masood 2016). Such governance by numbers has extended further with Millennium Development
Goals and Sustainable Development Goals, which champion indicators as tools for economic and
social development (Taylor 2016). Indeed, global benchmarking has emerged as a prominent all-
purpose mode of transnational governance (Desrosières 1998, Davis et al.2012, Jany-Catrice 2012,
Broome and Quirk 2015, Cooley and Snyder 2015, Kelley 2017), with indices covering everything
from gender equality and business climates to nancial opacity and good governance.
Globally proliferating quantication can suer from shortcomings that parallel those we nd in
domestic governance by numbers (Porter 1995): statisticsair of objectivity and accuracy can hide
shoddy methodologies (Broome et al.2018), poor data (Jerven 2013, Linsi and Mügge 2019), out-
dated policy priorities (Fioramonti 2013), and biases in the data (Mügge 2019). These below-the-
radar politics of economic statistics motivate us to investigate political ghts over South African
unemployment measures and the roles that domestic actors and international organisations play
in them.
In public and political discourse, the ocial unemployment rate often functions as the de facto
thermometer for national labour market conditions. Across history and societies, quite dierent
phenomena have been collected under the heading unemployment(Zimmermann 2006). On the
one hand, unemployment as a label, and the statistics later built on it, consciously recognised that
joblessness was not necessarily a sign of individual failure but could be caused by structural econ-
omic factors beyond personal reach. This framing of joblessness attenuated the moral opprobrium
attached to it and shifted part of the responsibility for the plight of the unemployed onto govern-
ments (Gautié 2002).
Unemployment statistics as they solidied after the Second World War in Europe and the USA
increasingly coalesced around a clear prototype:
An able-bodied, prime-age male industrial breadwinner with plant specic skills who [had] been laid ofrom full-
time formal work as the result of a plant closing in a declining industry. (Baxandall 2004, p. 212)
On that basis, employment statisticians typically distinguish three categories of people: the
employed, the unemployed, and the economically inactive. People in both the second and third
groups have no jobs. However, the unemployed want a job, are available for one and are actively
searching; the economically inactive normally fail the last criterion (Green 2000). The active
search-criterion functions as a litmus test to gauge whether joblessness is voluntary or not.
This approach has shortcomings, as statisticians themselves concede (for example Sengenberger
2011 from the ILO). It excludes people who want a job but do not look for one because they are dis-
couraged or deem their qualications insucient (Kingdon and Knight 2001). In many Western
countries, controversies about unemployment statistics have focused on such involuntary economic
inactivity (Baxandall 2004). Indeed, in 1982 the International Conference of Labour Statisticians
included two distinct denitions in its guidelines: a narrow one, excluding the jobless who wanted
work but did not search actively, and a broad one, which did include this group. In practice, most
countries around the world have settled on the narrow denition as the ocial headline gure.
This choice matters because it shapes the political priority attached to reducing unemployment of
one or the other kind. Governments are likely to develop very dierent policies via-a-vis the
people who fall between the two denitions, not least the welfare measures benetting them.
A second contentious aspect of the ILO denition gains particular signicance in developing
countries: the unemployed have to be available for work. In Western contexts, that means being
ready to begin work more or less right away impossible only under special circumstances, for
example due to impending childbirth or medical constraints. By implication, the unemployed are
those people for whom the main barrier to a job is that the right one simply cannot be found.
In poor countries, the reasons not to be available may be very dierent. Rural subsistence farmers,
for example, might long for formal employment but be unable simply to take up a paid job. Their
whole life situation, as that of their dependents, may forbid that, and the employment sought
may not be anywhere nearby. Even if someone is unable to walk away from her living situation
not availableand hence not unemployed there may still be a serious labour market problem
(Kingdon and Knight 2001, Posel et al.2014).
Because of their monetary bias (Mügge 2019), economic statistics systematically sideline unre-
munerated (reproductive) labour, much of which is done by women within households (Hoskyns
and Rai 2007). Such gender bias also feeds into unemployment statistics, and the gap between
narrow and wide denitions: because a disproportionate share of household and care responsibilities
lands on their shoulders, women are often not available for paid employment, even if under a more
equal division of tasks between men and women they might be happy to seek employment, not
least to buttress their economic independence. A narrow unemployment rate can thus hide the
specic socio-economic diculties women face.
High South African unemployment rates have repeatedly been doubted with the argument that, if
joblessness really were that sky-high, we should witness large-scale riots. Yet in fact, socio-economic
deprivation may be institutionalised:
The elaborate mechanisms of proletarianization, repression, and discrimination not only impoverished indigen-
ous people physically, but probably did even more psychological damage. As soon as family and other social
structures were disrupted, the disciplinary and civilising eects of those traditional structures were undermined.
In this way a subculture or syndrome of poverty was institutionalised among poorer Africans and coloureds.
(Terreblanche 2002, p. 40)
Hence, if there is a specic form of discouragement that is a legacy of apartheid and racism, the of-
cial unemployment denition may obscure that in particularly pernicious ways.
The question is how, among all the imperfect and potentially ill-tting options, that single
leading labour market indicator is constructed which in turn dominates policy, public debate
and external perceptions (cf. Khan et al.2015). The literature oers several hunches, which we
take as inspirations as we investigate the indicator politics in South Africa. Most obviously, poli-
ticians may tinker with denitions to embellish their economic achievements or, if in the opposi-
tion, detract from those of the ruling government (Moon and Richardson 1985). Second,
international organisations such as the ILO and the United Nations have promulgated standards
such as the System of National Accounts since the end of the Second World War (Ward 2004,
Clegg 2010). It is unclear, however, how these internationalisation eects have played out in devel-
oping countries, where the gulf between international standards and the local situation may be
particularly wide. Third, measurement approaches can become path-dependent once specic
policy commitments are attached to them (Baxandall 2004,p.216),suchasworkersrights to
nancial assistance. The interests that congeal around particular denitions may serve to entrench
them. To what degree do these hunches help us make sense of the politics surrounding unemploy-
ment indicators in South Africa?
Unemployment Measures and the end of Apartheid
South African statistics have always been tightly linked to the countrys idiosyncratic politics and
followed a strict racial logic. Its Current Population Survey (CPS) measured the Whites, the Colour-
eds and the Indians (as the categories went) until 1990 (Standing, Sender and Weeks 1996). The
Black Africans, in contrast, were excluded. For the rest, the Central Statistical Service (CSS)
mainly concentrated on Whites (Lehohla 2002). Nevertheless, already in the 1970s and 1980s,
South African debates about unemployment statistics asked how much of it was in fact voluntary
(Standing et al.1996). Some argued that many rural-dwellers chose to be unemployed, content
with subsistence agriculture (Kantor 1980,Gerson1981); others pushed back (Simkins 1982,
Kingdon and Knight 2001).
The apartheid legacy is fundamental to understand the specicities of South African labour
markets and why narrow denitions may be particularly ill-tting. Rural unemployment in the
country is higher than urban unemployment because apartheid had severely restricted blacks
mobility. Black homelands were rural areas with poor land and little formal employment.
people living there, nding paid work often meant waiting for formal-sector job opportunities
to arise far away, outside the homelands. The geographical and racial mismatch between
where people live and where employment is to be found mars South African labour markets to
this day.
Apartheid legacies continue to shape present-day labour markets in other ways, as well: through
highly unequal access to education (du Toit and Neves 2014) as well as through a large (and again
racialized) informal economy (Rogerson 1992, Chandra et al., 2002). Given the history of unequal
access to paid employment, unpaid and highly gendered household labour continues to play a
central role especially for poor South African families (du Toit and Neves 2014, p. 834, Cousins
et al.2018).
In addition, Apartheid-age repression of black labour had meant that it was available cheaply, not
least for the labour-intensive resources extraction and agricultural sector. International boycotts and
foreign companiesreluctance to invest in Apartheid South Africa had held productivity growth back.
Post-apartheid economic modernisation then meant that catch-up productivity growth hurt demand
for labour. 500.000 jobs were lost in the rst ve years of democratic government, while an additional
Figure 1. Labour Market Evolution since 1994 (%). Source: authors, based on Stats SA databases and statistics publications.
450.000 young people entered the formal labour market. By whichever measure, unemployment sky-
rocketed (Cling 1999), as Figure 1 shows.
In 1994, the democratic movement in South Africa released the Reconstruction and Development
Programme (RDP), which focused on redistribution following a Keynesian paradigm (Adelzadeh 1996,
Koelble 2004). Two years later, the government shifted to an orthodox economic reform programme,
encouraged not least by the major conglomerates of the country and the wish to attract foreign
direct investment (Carmody 2002, Hamilton 2014). This international orientation, as we will argue
below, eventually bolstered the case for adoption of international standards, including in economic
The government opted for regulated exibilityof the post-1994 labour market: minimum wages,
combined with a recognition of a two-tier labour market of permanent, protected workers, as well
as temporarily employed and less protected ones. Overoptimistically, the government had banked
on a nine-fold increase in foreign direct investment (FDI) to meet employment targets. In the
event, South Africa registered a net FDI outow of around $1.6 billion between 1994 and 1999 as
domestic companies internationalised. Old cleavages in South Africas labour market therefore
have persisted, as does stiing unemployment and rampant inequality (the Gini coecient varied
between 0.66 and 0.70 between 19932012, see Isaacs, 2016).
The abolition of apartheid legislation in 1991 and the wider economic and political reversals in its
wake brought challenges for economic statistics, too. The October Household Survey (OHS) of 1993
was the rst one that aspired to include the entire population. The mission was to transform the CSS,
formerly part of an oppressive apartheid state, into a democratic institution. In 1994, the government
set up a task force to craft what would eventually become the Statistics Act. With the assistance of the
Swedish, Australian and Canadian statistical agencies, it published a widely discussed policy paper in
1997; two years later, Stats SA was established and enshrined as the only institution producing ocial
statistics (Stats SA 1999).
With the apartheid approach discredited, statistical standards were up in the air. Using this
opening, the CSS deed international practice and adopted the expanded unemployment denition
in the rst 1993 OHS (Bangane 1999).
It stuck to this denition for the subsequent years. An ocial
report on the 1995 OHS dened unemployment as follows:
The proportion of people in the economically active population who are not in paid employment or self-employ-
ment at a given point in time, but who are available for work or for other income-generation activities, and who
want to be employed or self-employed. (CSS 1996, p. 15)
This wantelement is the key characteristic of the expanded denition; people are not obliged to
actively look fora job to be included in the statistics.
This approach was a conscious policy decision. As Mark Orkin and Ros Hirschowitz
explained in
the same report:
It has been widely recognised that the strict denition is too limited in the present South African context, where
employment opportunities are extremely limited, and many unemployed people have ceased to seek work
actively [] This applies mainly to women, particularly those in rural areas, where employment or income-gen-
erating activities are scarce, and transport is expensive. The unemployment rate is consequently dened by the
CSS in terms of the expanded denition. (CSS 1996,p.1415)
Even with apartheid ofcially abolished, the South African labour market remained highly fragmen-
ted and extremely unequal. In the spirit of wanting to help redress these imbalances by highlighting
them, the 1996 CSS report disaggregated the gap between expanded and strict rates by race and
gender (Figure 2).
Three features are particularly striking: the unemployment rates vary strongly in line with the
dierent racial categories, unemployment rates are substantially higher for women across all racial
groups, and most important for our purposes the gap between the strict and expanded
denitions is particularly high for Black South Africans and for women. In eect, economic inactivity
that might potentially count as unemployment is Black, and it is heavily female. That gives the
diering denitions a clearly gendered and racialized charge. In early post-Apartheid South Africa,
CSS ocials consciously deed international conventions and used unemployment denitions that
would avoid such biases.
The Creeping Rise of an OcialDenition
No single indicator narrow or broad can answer all questions about labour markets. A struggle
over indicator denitions therefore is a struggle over which perspective is highlighted and which
one is sidelined. When several denitions and time series exist side by side, it still matters which
one is designated as the ocialset of gures, relegating competing data to a secondary status.
During the second half of the 1990s, the narrow unemployment denition creepingly emerged as
the ocialone setting the stage for the increasing marginalisation of the broad denition in
the two decades to follow.
In South Africa, this denitional struggle has played out between the politician who, as minister,
was in charge of economic statistics, and the head of statistics himself. Trevor Manuel has been min-
ister in South African governments from 1994 to 2014, covering a range of portfolios. During the tran-
sition from CSS to Stats SA, he was in charge of statistics as Minister of Trade and Industry. Realizing
how crucial statistics were for economic and political development of South Africa, Manuel fought
hard for their reform once apartheid had ended (Green 2008). The debate was deeply politicised,
as Ravi Naidoo, director of the National Labour and Economic Development Institute in the 1990s
and early 2000s and part of the Statistics Council remembers:
It was very contentious because the [trade] union was keen to say that unemployment was a much bigger
problem. And that therefore the government should be proactive in the economy. Whereas business, at that
time, was happy to say we dont need much intervention [] The ght was really to make the government
more interventionist, because we had a very conservative economic team then in government. (Interview with
Ravi Naidoo, Johannesburg, 2018)
Awage-citizenship nexustook a central role in the post-apartheid South Africa (Barchiesi 2011). A
strong focus on jobsnormalised paid work at the centre of the liberation of South Africans but, by
implication, excluded non-wage workers. This narrative combined economic modernisation and for-
malisation with a catch-up to neoliberal, eciency- and productivity-driven economic policies fash-
ionable elsewhere in the world at the time (cf. Ferguson 2015).
Figure 2. Unemployment Rates by Race and Gender (%). Source: October Household Survey, 1995.
After an initial phase in which statistical development was mainly inspired by the wish to shed
Apartheid-legacies, public statistics professionalised. Statistics SA gained increasing autonomy
through the Statistical Act of 1999. According to Peter Buwembo, chief director of the Quarterly
Labour Force Survey, this autonomy became crucial for Stats SA:
That is the good thing, they give us enough space, good space. They dont tell us at all what to do, they have to
accept what we say. It is a story from a long time ago, when the minister [Manuel] said dont give me what I want
to hear but what I need, what I need to understand, because what I cannot measure, I cannot manage it.Nobody
asked for gures before. They get to know them at the same time as everybody, in the media. We have a strong
Act; it helped us. (Interview with Peter Buwembo, Pretoria, January 2018)
This changed status also meant that methodological and inferential considerations rather than
purely political ones increasingly gained weight. Hence, the rst challenge to the broad denition
which asked whether people wantedto work rather than whether they were looking for a job’–was
rooted in a statistical argument about robustness. A 1998 Stats SA report critically noted that
the expanded unemployment rate does, however, introduce more subjectivity into the measure of the unemploy-
ment rate, and instability in tracking trends, as it is more dicult to distinguish what constitutes wantinga job
than to say whether someone has engaged in denite actions to nd one. (Stats SA 1998, p. 63)
The technical demands on statistics might come to trump the appropriateness of the underlying
It was clear to all involved that peoples labour market situations come in many shades of grey.
Nevertheless, translating those nuances into hard and fast categories presented diculties of its
own. One option was a very expandeddenition of unemployment, including even the jobless
who professed no desire for employment.
The other one was to classify the not lookingsimply
as economically inactive. Table 1 shows the dierence this categorisation makes.
The gaps between the gures were vast. The eventual compromise between Orkin and Manuel
was to publish the narrow and the expanded numbers, with all attendant detail (age, sex, region,
and so on.), but to designate the narrow yardstick as the ocial one (Green 2008).
As a former sociologist, whos worked for [the Congress of South African Trade Unions] and for Jay Naidoo [its
leader until 1993], we wouldnt gain by ceasing to report the expanded denition, so now we report both. (Inter-
view with Mark Orkin, Johannesburg, 2018)
Table 2 reproduce how Statistics SA decided to present unemployment trends in its 1998 report.
The second driver behind the narrow measure came from outside South Africa in the form of ILO
standards. To be sure, the ILO did not impose its denitions in any way. Yet in the years after the
immediate post-Apartheid enthusiasm, South African politicians felt a need to build international
credibility, including by adherence to international technical norms and standards. The desire
seemed to justify privileging a strict measure, and an increasing use of international consultants
and rising regard for social development indicators further pushed South Africa in that direction.
The ILO denition granted countries some leeway in the treatment of the jobless who were not
looking for a work, depending on the labour market structure and social constraints for job-searchers
and non-searchers (Hussmanns et al.1990, p. 107108). That said, a 1996 ILO report stressed that
including the non-searching unemployed might exaggerate unemployment (Standing et al.1996).
The ILO would tolerate the broad denition, but clearly not encourage it, and indeed three quarters
of countries around the world ignored the jobless who were not actively looking for work from their
unemployment statistics (Posel et al.2014, Stats SA 1998).
Table 1. October Household survey, 19941997: unemployment rates.
Rates of unemployment (%) 1994 1995 1996 1997
Very expanded unemployment rate 38.4 37.4 41.7 42.4
Expanded unemployment rate 30.9 29.1 35.6 37.8
Ocial unemployment rate 19.2 16.9 21.0 22.9
Source: Statistics South Africa, 1998.
On top, Orkin, and then Hirschowitz, argued that the broad denition would dent the countrys
investment ratings through an excessively gloomy picture of economic conditions and disadvantage
it in the international use made of comparative statistics (Green 2008; Interviews). Hence, South Africa
published its new ocial unemployment rate following widely-accepted international practice(Stats
SA 1998, p. 11).
The ILO supported the eort and assisted South Africa in tackling the many practical
problems they confronted in building new statistics, remembers Neva Makgetla of the Trade & Indus-
trial Policy Strategies Institute:
The ILO provided a lot of help to set up the system. Before 1994, even in the census Africans were not counted at
all if they were in the former so-called homelands’–at that time close to half the population and they only
counted 10 percent of Africans living in the nominally Whiteareas. The then Central Statistical Oce had no
idea how to manage a survey of any kind that included Africans fully. They were themselves all White, for a
start (Interview with Neva Makgetla
, Johannesburg, 2018)
The move towards international standards was buttressed by international consultants who sup-
ported Orkin and his team. The Swedish programme for example assisted not only with strategic
management systems and the development of provincial oces and census planning; it also
helped to rene household survey methodologies and to improve South Africas national accounts
(Stats SA 1999). Transnational expert networks helped diuse de facto international standards.
The 2000s: Discouraged Work Seekers or an Expanded Denition?
If the 1990s had earned the narrow unemployment indicator the ociallabel, the 2000s solidied
this position. The September 2004 Labour Force Survey (LFS) was the last to detail the expanded
unemployment as much as the strict, ocial one. After that, the broad unemployment indicator
became an occasional, ancillary shadow statistic even if debate has refused to die down about
the discouraged work seekers-category and the mist of international standards with South
African conditions.
Early in the 2000s, statisticians were still content defending the legitimacy of both unemployment
measures. In a 2002 brieng Hirschowitz, then Deputy Director-General for Quality and Integration,
was ask to respond to criticism of the ocial (ie, narrow) unemployment gures from the Congress
of South African Trade Unions (COSATU), the largest trade union confederation in the country. She
replied that
there is an ocial and an expanded denition of unemployment. Countries are given the discretion to use either
denition depending on the circumstances [] both denitions are valid in South Africa and therefore Stats SA
used both of them. (Finance Standing Committee 2002)
Table 2 Ocial and Expanded unemployment rates measured by OHS 199497, and corollaries.
(ii): Ocial unemployment rate measured by OHS 19941997, and corollaries
1994 1995 1996 1997
d Unemployed measured by OHS: ocial denition (000s) 1,988 1,644 2,019 2,238
e = b+d Economically active (000s) 9,959 9,713 9,609 9,787
f = a-e Not economically active (000s) 10,907 11,612 12,206 12,507
g = 100*d/e Ocial unemployment rate ( % ) 20.0 16.9 21.0 22.9
h = 100*e/a Labour force participation rate ( % ) 47.7 45.5 44.0 43.9
(iii): Expanded unemployment rate measured by OHS 199497, and corollaries
1994 1995 1996 1997
i Unemployed measured by OHS: expanded denition: (000s) 3,672 3,321 4,197 4,551
j = b+i Economically active (000s) 11,643 11,390 11,787 12,100
k = a-j Not economically active (000s) 9,223 9,934 10,028 10,195
l = 100*i/j Expanded unemployment rate (%) 31.5 29.2 35.6 37.6
m = 100*j/a Labour force participation rate (%) 55.8 53.4 54.0 54.3
Source: Stats SA (1998).
Yet in the mid-2000s, South African labour statistics shifted further towards the narrow denition. The
LFS of the early 2000s still featured both the ofcial and the expanded unemployment numbers, even
in the highlights; the annexes contained detailed information about the latter. Nevertheless, the Ten
Year Review (a decade after the end of apartheid) of government programmes, issued by the Policy
Co-ordination and Advisory Services, clearly supported the strict denition (PCAS 2003), and the
mood shifted further against the broad one.
By 2005 the broad unemployment rate had reached roughly 40 percent. Finance minister Manuel earlier a sup-
porter of a exible approach was incredulous: If 40 percent of South Africans were really unemployed, thered
be a revolution.He warned that unemployment gures should not simply be bandied about.Sure, unemploy-
ment is a problem,he said, but that gure is wrong.(IOL 2005)
Thabo Mbeki, the president himself, towed a similar line: in an ANC Today column, he observed that, if
one were to believe the gures,
in March 2004 there were at least 4 million South Africans walking about in our villages, our towns and cities
actively looking for work. This is such a large number of people that nobody could possibly have missed the
millions that would be in the streets and village paths actively looking for workin all likely places of employment.
It, therefore, seems quite unlikely that the Stats SA gure is correct, if indeed it used the standard international ILO
denition to determine the unemployment rate. (Mbeki 2005)
In the LFS from September 2004, expanded unemployment numbers had been relegated to
the annexes. Half a year later, the March 2005 LFS replaced the expanded unemploymentcategory
with a separate entry for discouraged work seekers’–the jobless who wanted a job and were
available but had not sought work because no jobswereavailableinthearea,becausethey
were unable to nd work requiring their skills, or because they had lost hope of nding any kind
of work (Stats SA 2009). The statistics increasingly walled othe formally unemployed from
This shift attracted political attention. The opposition decried the narrowness of the indicator. In
October 2005, the Finance Standing Committee questioned dropping the broad denition of unem-
ployment as the strict denition did not accommodate the large informal and self-employed sector,
which needed to be measured(Finance Portfolio Committee 2005). The South African Reserve Bank
(SARB) also raised doubts, given the importance of unemployment for its monetary policy. Hirscho-
witz oered three defences: rst, a separate discouraged work seekerscategory would allow better
identication of this groups characteristics. Second, the new approach followed recommendations
by the IMF, which had reviewed South African labour statistics. Third, the old presentation might
confuse people who would [compare] South Africas broad denition with other countriesstrict
denitions. Ian Davidson of the opposition Democratic Alliance remained unimpressed, fearing a
growing disconnect between the real and the statistical world. The new approach would not
provide the necessary information about the dierence between the broad and strict unemployment
denitions. The broad category of unemployment must be retained and captured as it would reect
the real jobless rate(Ibid).
Spats continued between observers who found the gures too high or too low, and they further
discredited the home-grown measures. Pali Lehohla, Statistician General until 2017 and Orkins
deputy before 2000, conceded that Stats SA had previously suered negative publicity regarding
the accuracy of its statistics pertaining to its community survey, after irresponsible reporting by a
certain journalist [..] and after allegations(Finance Standing Committee 2008). However, the
narrow denition was adopted for international comparability and hence was the ocial denition
for unemployment, he avowed (Ibid).
To regain credibility, Stats SA asked the World Bank to review its statistical approach (interview
with Peter Buwembo, Pretoria, January 2018). Heeding the Banks advice, Stats SA completely over-
hauled its survey design and shifted from the bi-annual LFS to a Quarterly Labour Force Survey (QLFS)
(Yu 2009).
The report introducing the new statistical tools highlights conformity with internationally
acclaimed practices(Stats SA 2009, p. 19) no less than six times. To avoid being ground up
between politically opposing domestic parties, national statisticians sought refuge among inter-
national statistical experts and their standards. That spirit lingers. In the words of Rashad Cassim,
head of the SARB research department, former Deputy Director-General at Stats SA and member
of the Statistics Council:
We really invest in making sure that what we do is keeping international practices. So we follow very strictly the
ILO convention around what is considered an informal worker, what is considered a discouraged worker. (Inter-
view with Rashad Cassim, Pretoria, February 2018)
Through this full embrace of ILO denitions, the ambiguity about where unemployment ends and
genuine inactivity begins in South African statistics disappeared: the QLFS unequivocally les discour-
aged work seekers under not economically active. It has remained that way since (see Table 3, taken
from the rst QLFS 2018).
The Evolution and Debates Until Today
In specialist circles, the debate about these categories continues. As always with statistical categor-
isation, the devil is in the detail. Reviewing the rst QLFS of 2008, Meth observed that
it would seem that in the past, those who said that they lacked the money to pay for transport to seek work, or
who said that there was no transport available, were classied as discouraged. The new denition no longer
includes such folk, an important change, and one which deserves to be widely debated, especially in view of
apartheids horrible distortions of South Africas spatial economy. (Meth 2009, p. 84)
Even disregarding such seeming technicalities, many discouraged work seekers are arguably still part
of the labour force. Posel et al.(2014) show that many do not search actively because of the literal and
gurative costs of job search and the low chances of success; instead, they rely on their social net-
works for sustenance (cf. Lloyd and Leibbrandt 2013, Merten 2016). Faldie Esau, member of the
South African Statistics Council, conrmed that argument:
Table 3. Key labour market indicators, as presented in the rst QFLS 2018.
Thousand Per cent
Population 1564 yrs 37,061 37,525 37,678 153 618 0.4 1.7
Labour Force 22,426 22,051 22,358 307 68 1.4 0.3
Employed 16,212 16,171 16,378 206 165 1.3 1.0
Formal sector (Non-
11,337 11,244 11,355 111 18 1.0 0.2
Informal sector (Non-
2,681 2,808 2,901 93 220 3.3 8.2
Agriculture 875 849 847 328 0.3 3.3
Private households 1,319 1,270 1,275 5 45 0.4 3.4
Unemployed 6,214 5,880 5,980 100 234 1.7 3.8
Not economically active 14,634 15,474 15,320 154 686 1.0 4.7
Discouraged work-
2,277 2,538 2,787 249 510 9.8 22.4
Other (not economically
12,357 12,936 12,533 403 176 3.1 1.4
Rates (%)
Unemployment rate 27.7 26.7 26.7 0.0 1.0
Employed / population
ratio (Absorption)
43.7 43.1 43.5 0.4 0.2
Labour force participation
60.5 58.8 59.3 0.5 1.2
Source: Stats SA (2018).
The challenge that you have is the tools [are] not designed for lower levels. There are certainly pockets of unem-
ployment in certain provinces for a lot of reasons. I will give you some examples. Its called Murraysburg and the
closest town, a big town, is Gra-Reinet. So the challenge for those people is that they dont have the money to go
to Gra-Reinet and register. So they may do for a few months and after they stop doing that. (Interview with
Faldie Esau, Cape Town, May 2018)
These arguments frequently run along political lines. In the words of Peter Buwembo:
Some people prefer to use the broader [denition], because they have some interest, especially the unions. (Inter-
view with Peter Buwembo, Pretoria, January 2018)
Neva Makgetla doubted whether these political motivations would not distort the unionsunder-
standing of the statistics:
The important thing, of course, is what you are trying to reect the ratio of people seeking work actively to the
employed, or the ratio of those who want work, even if theyve given up looking for it. [..] People who dont actu-
ally work with the numbers often fetishize them there were some people in COSATU who insisted on the broad
gure mostly because they wanted to get government to prioritise unemployment more. (Interview with Neva
Makgetla, Johannesburg, May 2018)
Thus, in South Africa, nding employment is widely seen as the key to escaping poverty. Political
debates hence revolve around unemployment and poverty, but sideline the large number of working
poor, who do not t the jobs vs. poverty dichotomy. In 2012, more than a fth of workers lived in
households unable to meet basic needs, and 58 percent of poor South Africans lived in a household
with an employed person (Rogan and Reynolds 2015). Indeed, Scully (2016) calculated that 42
percent of South Africas employed labour force can count as precarious, such that unremunerated
labour in the household and beyond remains essential to peoples survival strategies. Dominant
views of unemployment eectively hide such problems.
Where criticism from the unions tends to cast unemployment gures as too low, criticism from the
business sector has veered in the opposite direction. In 2011 the Adcorp work agency and consul-
tancy avowed that the actual unemployment rate was only around 11.3 percent (Harding 2014), as
opposed to the ocial 24.8 percent. Adcorp economist Loane Sharp observed that this latter
number is simply incredible, because we should have expected civil disobedience and disorder on
a grand scale if this were true(Harding 2014). Whence this discrepancy between the real and the
ocial numbers? Stats SA vastly underestimated informal employment, Adcorp argued, and
should add more than six million people to its employment gures. The Adcorp methodology
immediately drew academic re (Wittenberg and Kerr 2012), but also fuelled doubts about the
reliability and usefulness of ocial statistics (van der Berg 2013).
On the back of such incessant debate, the Finance Standing Committee debated the unemploy-
ment denition yet again in May 2013. Speaking for the Democratic Alliance, Tim Harris suggested
that Stats SA be asked to compile data on the broader denition to enable the Committee to get
a better picture of the situation(Finance Standing Committee 2013). The former Deputy Director-
General of Stats SA agrees:
I do think that saying that the narrow unemployment rate is 27 percent is misleading. Because at the end of the
day youre saying that discouraged workers are technically not part of your unemployment, because they tech-
nically stopped looking for a job. So because they stopped looking for a job, they are not unemployed anymore.
But theyve stopped looking because they couldntnd [one]. So my view is that although, in terms of compar-
ability, we give the narrow denition, I do think as a country we constantly have to give two together [] And we
should be constantly monitoring why these discouraged workers are discouraged. (Interview with Rashad Cassim,
Pretoria, February 2018)
Based on these arguments, Stats SA has carefully reintroduced some of this information by listing
the expanded denition in the QLFS annexes detailing unemployment by province in 2010. In
addition, three years later, it is inserted it in the last section of the principal results, through a map
summarising the QLFS (see the example in Figure 3). Since then, the expanded rate has operated
as a kind of shadow statistic. The gures are available to those who really want to know and look
for them; for the rest, the narrow denition of unemployment remains the ocial one to be used in
political discourse and the media.
Unemployment has no obvious demarcations, and indicators to capture it are therefore fundamen-
tally ambiguous and potentially vulnerable to contestation. This ambiguity becomes particularly clear
in countries such as South Africa, in which broad and narrow denitions produce such widely dispa-
rate numbers.
This ambiguity has been hard to sustain, certainly for a edging statistical oce such as the South
African one. During the past decades, unemployment measures in the country have undergone a
dual movement. After the end of Apartheid, the Central Statistical Service initially embraced a
broad unemployment denition to capture the socio-economic realities particularly of Black commu-
nities. Yet over the course of the 1990s and the 2000s, international standards increasingly dominated
South African statistics, narrowing the unemployment indicator evermore.
Denitional quandaries do not only aect South African statistics. Labour markets in rich countries
also change rapidly. Automation aects which kind of labour is in demand and which one is no
longer. Entrepreneurial forms of self-employment are on the rise, as are part-time work and combi-
nations of several jobs to make ends meet. Female labour force participation rates have risen substan-
tially over the past decades, as well. The male factory worker as unemployment statistics lodestar is
less and less useful all around the world.
South Africa had tried to move beyond established unemployment standards in the early years
of democratisation, and current Stats SA publications oer useful, nuanced detail about the
countries labour markets. Nevertheless, the narrow unemployment rate is now unambiguously
the ocial series. Whenever a single number for South African labour market conditions is being
sought whether by international investors, for global comparisons or by academics using
Figure 3. Summary of labour market measures at a glance, Q1: 2018. Source: Stats SA (2018).
large-n data sets in their research they will use one that has been fought over for decades, and
which remains contested as a reection of South African labour markets. As far as I know, the
debate about broad versus narrow is no longer particularly important,Neva Makgetla told us.
Thus, as Desrosières (1998) put it, the statistical measure of unemployment in South Africa has
now become an established convention –‘information’–insofar as it has become reliable, even
if it oers a skewed representation of reality.
What has driven this dynamic? It is worth noting rst what we did not nd. As pointed out above,
alternative unemployment denitions and measures clearly have a racial dimension. An expanded
rate emphasises the poor labour market conditions of Black South Africans much more clearly
than a narrow denition does. Critics could have levelled the charge of (potentially inadvertent)
racism at narrow unemployment measures.
In our interviews and document research, however, we found that actual debate in South Africa
has accorded surprisingly little attention to this issue. Presumably this relative silence is explained by
the ANCs grip on political power since the end of Apartheid. With its roots in the Black South African
community, the party might have an incentive to highlight racial biases in political institutions such as
ocial statistics. However, it also has a political track record to defend, and for that, the expanded rate
is counterproductive. The charge of racial bias might have been much more prominent if other pol-
itical actors would have wielded power in South Africa.
Instead, our analysis highlights the counterintuitive role of international statistical harmonisation.
The high speed of statistical (and concurrent democratic) construction in the country since the end of
apartheid has engendered a direct need to legitimize the new ways of measuring South Africas social
and economic conditions. In line with our expectations, this legitimacy was rst sought internation-
ally. Compliance with international standards increasingly functioned as a seal of approval and
quality, insulating gures against claims of political bias.
This nding is not as obvious as it may seem. We have argued above that unemployment indi-
cators are fundamentally ambiguous; there never is one obviously correct measurement, and the
merits of alternative standards vary across countries. That may seem to make international standards
both harder to achieve and less attractive, because no single size ts all. Instead, we nd ambiguity to
have the opposite eect: it incentivizes national statistical agencies to sign up to international stan-
dards as buers against domestic criticism, which itself feeds on the indicator ambiguity. Inter-
national harmonisation may thus be alluring not in spite, but because of the indeterminacy of
statistical measures and their inevitable political weight.
1. The label developing countriescarries regrettable connotations, for example dierences in countriesadvance-
ment along a single developmentpath or a materialist conception of national progress. We dont endorse those
connotations. Lacking better alternatives, we simply use it, reluctantly, to designate relatively poor, non-Western
2. Early in 2018, there were approximately 5.9 million ocially unemployed in South Africa (actively searching for a
job) as well as 2.7 million discouraged work-seekers out of a population of somewhat below 60 million (Stats SA,
3. 10 years after the establishment of the Representation of Native Act in 1936, the ethnic homelands (or Bantu-
stans) were created to assign black Africans.
4. At the time, the four largest of those conglomerates controlled 83 per cent of the companies listed on the Johan-
nesburg Stock Exchange before apartheid ended. Their close links to the state made for a highly coordinated
nationalapproach to economic policy.
5. Two central characters in the evolution of South African statistics have been Mark Orkin, then the Head of CSS and
later the rst Statistician-General of Statistics SA, and Trevor Manuel, the rst post-1994 Minister of Finance.
6. One of the designers of the OHS, which initially underpinned unemployment gures, and Statistician General for a
short period after Mark Orkin and before Pali Lehohla at Stats SA.
7. Linguistic dierence can complicate things further. In some ocial languages, interviewers would have trans-
lated unemployedas looking for work, [..] others [..] simply as not working(Stats SA, 1998, 64).
8. All the reports (OHS, LFS, QFLS) have three parts: the highlighted results, which are a table summarising the prin-
ciple results of the study; some principal results, regarding employment, unemployment, and other specic infor-
mation; the annexes, were all the rest of the information is delivered in tables.
9. Henceforth, the unemployed were those people, within the economically active population, who did not work
during the seven days prior to the interview, want to work and are available to start work within a week of
the interview, and have taken active steps to look for work or to start some form of self-employment in the
four weeks prior to the interview.
10. Senior Economist at the Trade & Industrial Policy Strategies institute. She has been head of the COSATU Policy
Unit, and has been involved at the Development Bank of Southern Africa and at the Economic Development
This research is part of the FICKLEFORMS project at the University of Amsterdam. We are grateful to the team members
for their support and helpful comments.
Disclosure statement
No potential conict of interest was reported by the authors.
This work was supported by Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Vidi grant 016.145.395]; H2020
European Research Council [Grant Number 637683].
Notes on contributors
After a PhD in France, Juliette Alenda-Demoutiez is now a Post-doctoral Fellow at the University of Amsterdam, working
on the history of macroeconomics indicators in South Africa. Her research interests are, besides in political economy of
statistics, in development and social protection, still in Sub-Saharan Africa.
Daniel Mügge is Professor of Political Arithmetic at the University of Amsterdam. Together with a team of researchers, he
studies the political roots of macroeconomic indicators and their political baggage.
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... Inevitably, the latter was smaller due to the under-provision of education for black South Africans (Moll, 1996;Nattrass, 2014), and higher capital intensity decreased their wages. Consequently, since 1994, the total unemployment rate in the country has been increasing steadily reaching almost 30 and 40% according to the strict and the expanded definitions, respectively (Alenda-Demoutiez and Mügge, 2020). ...
... The continuing rise in unemployment since 1994 has been particularly harmful to black South Africans, who experienced dramatically higher rates due to the long-lasting effects of apartheid (Alenda-Demoutiez and Mügge, 2020). Indian and coloured South Africans also suffer from higher unemployment rates compared to white South Africans, whilst unemployment rates are remarkably higher for women across all racial categories (Alenda-Demoutiez and Mügge, 2020). ...
... Unemployment itself is found to decrease the private sector labour share and is statistically significant at the 1% level. However, this finding must be viewed with some caution, given the long-standing issues with the calculation of this indicator in South Africa (Alenda-Demoutiez and Mügge, 2020). Table 2 reports the additional econometric findings. ...
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... Currently, South Africa's labour market consists of formal and informal employment. Formal employment is defined as employment created by businesses or the government where an employee is hired under established working agreements (Alenda-Demoutiez & Mügge, 2019;Quain, 2018). In 2014, only 25% of South Africa's workforce were skilled workers with formal employment, that is, including graduate health workers (Statistics South Africa, 2014). ...
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Background: Before the coronavirus disease 2019 (COVID-19) pandemic in early 2020, the unemployment rate in South Africa was at its highest in history at 29.1%. During the COVID-19 pandemic to date, unemployment rose even higher to 35.3%. In this context, there has been an increase in the number of unemployed health professionals in South Africa. Objectives: This study aimed to determine the employment rates of newly graduated South African audiologists and identify the challenges in obtaining and maintaining employment for audiologists in South Africa. Methods: A descriptive online survey design was used. Participants were recruited online through professional association webpages using the snowball sampling technique. All qualified audiologists registered with the Health Professionals Council of South Africa were eligible to participate. Results: A total of 132 audiologists completed the survey. In the first-year postgraduation, 16% of the participants were unemployed, and this increased to 19% in the second-year postgraduation. In the majority (81%) of employed participants, almost a fifth (19%) were working within non-audiology/healthcare fields. The most common workplace challenges reported were remuneration (37%) followed by lack of resources (18%), workload (18%), work environment (10%), working hours (9%) and, lastly, interprofessional relationships (8%). Conclusion: Findings from this study are the first to document employment rates amongst South African audiologists. These findings have the potential to influence the critical discourse on hearing healthcare human resource planning, hearing healthcare labour capacity and potential for growth in the South African context post-COVID-19.
Only ten years ago, there were more internet users in countries like France or Germany than in all of Africa put together. But much has changed in a decade. The year 2018 marks the first year in human history in which a majority of the world’s population are now connected to the internet. This mass connectivity means that we have an internet that no longer connects only the world’s wealthy. Workers from Lagos to Johannesburg to Nairobi and everywhere in between can now apply for and carry out jobs coming from clients who themselves can be located anywhere in the world. Digital outsourcing firms can now also set up operations in the most unlikely of places in order to tap into hitherto disconnected labour forces. With CEOs in the Global North proclaiming that ‘location is a thing of the past’ (Upwork, 2018), and governments and civil society in Africa promising to create millions of jobs on the continent, the book asks what this ‘new world of digital work’ means to the lives of African workers. It draws from a year-long fieldwork in South Africa, Kenya, Nigeria, Ghana, and Uganda, with over 200 interviews with participants including gig workers, call and contact centre workers, self-employed freelancers, small-business owners, government officials, labour union officials, and industry experts. Focusing on both platform-based remote work and call and contact centre work, the book examines the job quality implications of digital work for the lives and livelihoods of African workers.
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Orientation: Heterodox economic scholarship has challenged the neoclassical doctrine that fiscal deficit increases unemployment in the long-term. Research purpose: This article examined the relationship between fiscal deficits and unemployment. Motivation for the study: The renewed debate about the role of fiscal consolidation in controlling unemployment in South Africa motivated the study. Neoclassicists in South Africa maintain that fiscal consolidation is the solution to unemployment, while heterodox thinkers argue for active fiscal policy. Research approach/design and method: The study utilised the Toda-Yamamoto Granger non-causality test and the Autoregressive Distributed Lag Modelling framework to test the relationship between unemployment and fiscal deficit. The quarterly data for the period 1994–2019 were obtained from the South African Reserve Bank. Main findings: This study found that fiscal deficits reduce unemployment in the short- run but increase it in the long run, thus confirming the neoclassical claim. This study found no statistical evidence for the heterodox view that fiscal deficits reduce interest rates and the neoclassical crowding-out hypothesis. Rather, the interest-neutrality of fiscal deficits was found. The adoption of a fiscal belief system that builds on the expansionary fiscal contraction hypothesis has been associated with high unemployment. Practical/managerial implications: Fiscal authorities have to use fiscal deficits creatively in managing unemployment to create a balanced economy. The fiscal balance, up to a threshold, between 0.8% (surplus) and 1.9% (deficit) of gross domestic product (GDP) in the short term and between 1.7% (deficit) and 1.9% (deficit) in the long term reduces unemployment as per the estimates of the study. Contribution/value-add: The finding that fiscal deficits increase unemployment does not justify a weak fiscal policy stance. The finding that fiscal deficits reduce unemployment up to a point before they begin to increase it in the long-term complements existing literature, which shows that South Africa’s government expenditure to GDP ratio has exceeded its optimal level.
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PURPOSE OF THE STUDY: Women-owned SMEs in South Africa are plagued with numerous challenges that contribute to the slow growth and failure of their businesses. Among these challenges are inadequate managerial skills related to the formulation and implementation of suitable strategies. This study aimed to determine the influence of strategy implementation on financial performance and the survival of women-owned SMEs in Gauteng province, South AfricaDESIGN/METHODOLOGY/APPROACH: The study followed a quantitative method in which a six-section survey questionnaire was administered to 347 women entrepreneurs conveniently selected from SMEs in Gauteng Province. Statistical analyses techniques applied in the study included descriptive statistics, exploratory factor analysis, Pearson correlations and regression analysisFINDINGS: Corporate and business strategies predicted financial performance. However, operational strategy was statistically insignificant. Additionally, all three strategies, namely operational, business, and corporate, significantly predicted SME survival. Financial performance predicted SME survivalRECOMMENDATIONS/VALUE: Efforts to alleviate the decline and failure of women-owned SMEs should centre on imparting the owners with business management skills that primarily include an understanding of the formulation and implementation of strategy. Future research suggestions include extending the study to male-owned SMEs, other provinces of South Africa and the inclusion of non-registered SMEsMANAGERIAL IMPLICATIONS: Strategy formulation and implementation remain important anchors for the success of women-owned SMEs in South AfricaJEL CLASSIFICATION: L26
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Party nieregeringsorganisasies (NRO's) help werklose mense om in diens geneem te word of om vir hul eie sak te werk. Sulke NRO's bied gewoonlik opleiding en ondersteuning aan werklose mense met die doel om hulle vermoë te ontwikkel op terreine waar hulle dit dalk nodig het. Die doel van hierdie verkennende navorsing was om te bepaal hoe geskoolde en hooggeskoolde werklose persone wat by 'n NRO in Pretoria, Gauteng, betrokke is, hulle eie vermoë sien om hulle indiensneembaarheid en selfwerksaamheid te verbeter. Die kapasiteitsbenadering van Sen en van Kolbe is in hierdie studie as teoretiese raamwerke gebruik, soos ook interpretativisme, fenomenologie en 'n kwalitatiewe navorsingsmetode. Twee semigestruktureerde fokusgroeponderhoude is gebruik om inligting van die deelnemers te bekom. Die bevindinge kan in drie hooftemas saamgevat word, naamlik die kognitiewe, of denke (selfbeeld, nuwe denke en vaardighede); die affektiewe, of emosies (motivering, negatiewe emosies ten opsigte van verhoudings); en strategieë om kapasiteit te bou (erkenning van vorige leer en werkskaduwing). Die konatiewe (strewe, gedrag) as deel van Kolbe se teorie is nie in die narratiewe gevind nie. Op grond van die navorsingsbevindinge en die literatuur is 'n raamwerk saamgestel om die "hoe" (watter strategieë) en die "wat" (watter kapasiteit) van kapasiteitsontwikkeling van geskoolde en hooggeskoolde werklose persone uit te lig.
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In taking the lens of the smartphone to understand experiences of ageing in a diverse neighbourhood in central Kampala, Uganda, this ethnography presents the articulation and practice of ‘togetherness in the dotcom age’. Taking a situated and ‘convivial’ approach, which celebrates multiple and partial ways of knowing about sociality, the thesis draws from these vernacular concepts of cooperative morality and modernity to consider the everyday mitigation of wide-reaching social processes. Dotcom is understood to encompass everything from the influence of ICTs to urban migration and lifestyles in the city, to profound shifts in ways of knowing and relating. At the same time, dotcom tools such as mobile phones and smartphones facilitate elder care obligations despite distances, for example through regular mobile money remittances. Whilst phones are a global phenomenon, both the concept of dotcom and the way people creatively adapt and adopt their phones has to be understood in relation to specific contextual conditions. This thesis is concerned with how dotcom manifests in relation to older people’s health, their care norms, their social standing, their values of respect and relatedness, and their intergenerational relationships - both political and personal. It thus re-frames the youth-centricity of research on the city and work, new media and technology, politics and service provision in Uganda. Through ethnographic consideration of everyday life and self-formation in this context, the thesis seeks to contribute to an ever-incomplete understanding of ‘intersubjectivity’, how we relate to each other and to the world around us.
Central for governance, official statistics are far from natural artefacts. The purpose, meaning and interpretation of statistical conventions evolve across time and space, in relation to social and political aspects. If criticism of indicators is growing since several years, less is understood on the process of quantification himself, especially in non-Western countries. Understanding quantification processes in different contexts is even more important as statistics are widely used in the development field. With a different complexity compared to Northern societies, African countries appear as privileged fields for this understanding and its connection with state-building. By using the analytical framework of the conventions school, I reread the case of official statistics in South Africa. Based on process-tracing, I show the history of the quantification process through its relations with the state, from a racial state during the apartheid to a developmental state nowadays.
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The purpose of the study is to gauge the unemployment level of selected one hundred and thirteen countries. The design of the study includes a survey of the literature, extraction of relevant data and analysis. The study follows a quantitative paradigm of research that uses secondary data set taken from the website of World Development Indicators (WDI). The analysis encompasses selected countries based on the availability of data. The data has been analyzed using Grey Incidence Analysis Model, commonly known as GRA. For interpretation of the results, the methodology has been augmented with the scheme of ensigns (i.e. classification of countries into Extremely Low, Very Low, Low, Moderate, High, Very High, Extremely High) of the level of unemployment. Results show that J&APR have an extremely low level of unemployment and member countries of SADC have an extremely high level of unemployment. Pakistan fall under the ensign of very low, therefore have a low level of unemployment. It is valuable to study equally useful for governments, academia and the international community. This study provides critical new information on the phenomenon.
This study estimates the drivers of the South African private sector labour share over the period 1971-2019. The focus on South Africa is instructive as its distributional contestation is bounded in a matrix of ethnic conflict. We observe a steady decline in its wage share from 1971 to the late 1990s, followed by an upward trend after 2009. Our econometric findings suggest that globalisation, financialisation, and public spending decreased the wage share. Yet, human capital development, strike activity, and periodic revolts against Apartheid lowered functional income inequality. Crucially, reforms on trade, finance, and welfare were undertaken after the democratisation period of 1994, and we find little evidence that the extension of the franchise is a robust determinant of the labour share. One explanation for this puzzle is that the white economic elites invest in de facto political power, by allying with emerging black economic elites and/or purchasing political support.
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International economic statistics play central roles in global economic governance. Governments and international organizations rely on them to monitor international economic agreements; governments use them to understand potential imbalances in bilateral relationships; and international investors build their country assessments on such data. These statistics increasingly suffer from serious defects, however, due to globalization, the digitization of our economies, and the prominence of secrecy jurisdictions and multinational corporations. For that reason, economic data is not a neutral arbiter in international affairs. Instead, it suffers from four kinds of bias: Expert attention bias means that the objects of measurement—what they are meant to capture—depend on the preoccupations of the small circle of statistical experts. Countability bias skews economic figures in favor of countable objects and away from, for example, unremunerated labor and production as well as ephemeral economic process, such as knowledge production. Capitalist bias emerges because economic statistics naturalize unequal power relations in the global economy: They mistake a country’s inability to fetch high prices for its products for low productivity and a lack of added value. Stealth-wealth bias, finally, means that statistics naturalize the distorted image we have of the global economy as corporations and individual hide profits and wealth in secrecy jurisdictions. This article cautions against an insufficiently critical use of statistics in international affairs. And it encourages policymakers to “know thy data” lest biases in the numbers generate skewed policies, unnecessary disputes and a gradual delegitimization of statistics in general.
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Official international economic statistics are generally considered accurate and meaningful gauges of cross-border flows of trade and capital. Most data users also assume that the quality of the underlying data keeps improving over time. Through an extensive review of the national accounting literature, archival research, two dozen interviews with high-level statisticians, and a series of data quality tests, we evaluate this common view for the primary source of data on trade and capital flows: the International Monetary Fund’s Balance of Payments (BOP) Statistics. Our assessment paints a less rosy picture: reported figures are far less accurate than they are typically imagined to be and often do not correspond to the theoretical concepts with which users associate them. At the same time, measurement quality deteriorates over time as the transnationalization of economic production gradually undermines the validity of BOP statistics. Our findings raise serious questions about the widespread use of these numbers, with their deceptive pretense to accuracy, in scholarly research and public debate about the international political economy.
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What can the international community do when countries would rather ignore a thorny problem? Scorecard Diplomacy shows that, despite lacking traditional force, public grades are potent symbols that can evoke countries' concerns about their reputations and motivate them to address the problem. The book develops an unconventional but careful argument about the growing phenomenon of such ratings and rankings. It supports this by examining the United States' foreign policy on human trafficking using a global survey of NGOs, case studies, thousands of diplomatic cables, media stories, 90 interviews worldwide, and other documents. All of this is gathered together in a format that walks the reader through the mechanisms of scorecard diplomacy, including an assessment of the outcomes. Scorecard Diplomacy speaks both to those keen to understand the pros and cons of US policy on human trafficking and to those interested in the central question of influence in international relations. The book's companion website can be found at
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Despite South Africa's successful transition to democracy and lauded constitution, political freedom for the majority of South Africans remains elusive. The poor and unemployed majority are poorly represented and lack power and thus freedom. Under these conditions, the freedom of the privileged minority is also seriously impaired due to the costs of maintaining their relative security and well-being. Lawrence Hamilton is an internationally-known political theorist, who has spent ten years teaching in South African universities. In this unique book he brings ideas - political and philosophical - to the fore to understand a contemporary political conundrum. He outlines the persistent, unresolved problems characterizing contemporary South Africa: poverty and quality of life statistics that are appalling for a middle-income country, levels of inequality that make South Africa one of the most unequal places in the world, skewed economic and political representation that reproduces elites rather than generating opportunities for all and an electoral system that implements the idea of proportional representation so literally that it undermines meaningful representation. Are South Africans Free? aims not only to explain the current state of South Africa but to provide positive new directions and suggestions for institutional change. Hamilton argues that freedom as power in South Africa does not depend on good will, charity or duty, and it goes beyond the complete realization of the political and civil liberties currently safeguarded in its constitution. Such change will depend on courageous leadership, active citizenship, new forms of representation and a macroeconomic policy that offers radical redistribution of actual and potential wealth.
Marxist agrarian political economy has focused largely on the problematic of accumulation and its politics, but the dynamics of social reproduction in rural contexts remain somewhat under-theorised. These are explored through consideration of empirical evidence from communal areas and land reform farms in South Africa. Key arguments advanced are that social reproduction in such contexts include the reproduction of distinctive forms of marriage, systems of kinship and community membership, as well as of property relations that are not characterised by private ownership. Much social reproduction occurs outside of (direct) market relations, but it is nevertheless deeply conditioned and shaped by the dynamics of the wider capitalist economy, including in relation to wage labour and small-scale agricultural production. As a result, social reproduction in rural areas involves contradictions, tensions and contestations, and these are often at the centre of local forms of politics. The wider significance of these findings is discussed, and it is suggested that similar dynamics may be at work across the Global South.
Over the last decade, international rankings have emerged as a critical tool used by international actors engaged in global governance. State practices and performance are now judged by a number of high-profile indices, including assessments of their levels of corruption, quality of democracy, creditworthiness, media freedom, and business environment. However, these rankings always carry value judgments, methodological choices, and implicit political agendas. This volume expertly addresses the important analytical, normative, and policy issues associated with the contemporary practice of 'grading states'. The chapters explore how rankings affect our perceptions of state performance, how states react to being ranked, why some rankings exert more global influence than others, and how states have come to strategize and respond to these public judgments. The book also critically examines how treating state rankings like popular consumer choice indices may actually lead policymakers to internalize questionable normative assumptions and lead to poorer, not improved, public policy outcomes.