The challenge of growth, employment and poverty in the South African economy since democracy: an exploratory review of selected issues

Abstract

The welfare challenges in post‐apartheid South Africa are best represented by the triumvirate of poverty, income inequality and unemployment. In turn, the one generally accepted mechanism for overcoming these challenges is for an economy to realise sustained levels of high economic growth. Herein lie the essential coordinates of this article. We attempt first to describe the post‐apartheid experience with economic growth and its determinants. Secondly, we describe the nature of the welfare challenges that the society faces in terms of poverty, income inequality and unemployment. Finally, and perhaps most critically, we explore the various constraints on economic growth that may be hindering the realisation of higher standards of living amongst the population.

1 INTRODUCTION

Since the birth of South Africa's democracy, the government introduced a series of policies that were aimed primarily at creating an environment conducive to growth. It adopted an economic reform package, consisting of fiscal prudence, trade reform and deregulation of various sectors of the economy. These initiatives are an important precondition, or enabling environment, for growth. The government has carried out a series of market‐friendly economic policies that have contributed to the increasing efficiency and productivity of the economy. It is, however, a well‐known fact that we cannot rely simply on growth alone to reduce poverty and inequality. Moreover, in view of the policy trajectory of the country, we cannot rely on simply preserving jobs in protected and inefficient sectors, nor can we automatically expand the public sector (Berry et al., 2002).

Growth is dependent on a range of issues beyond macroeconomic stability, trade liberalisation or labour market flexibility. In particular, the roles of institutions, microeconomic reforms and governance have become important indicators or predictors of economic outcomes. These are, however, areas in which empirical work is sparse and hence it is difficult to provide concrete links between growth and reform. What we attempt to do within the limited empirical work available is to provide some evidence, albeit incomplete, which allows us to make linkages between policy changes and growth and equality. A specific area of contention in the economic policy debate is the extent to which reform such as privatisation, trade or macroeconomic policy actually has a negative impact on distribution.

2 GROWTH AND WELFARE TRENDS IN THE SOUTH AFRICAN ECONOMY

Table 1 provides a set of estimates of a variety of key economic indicators over the period 1995–2002. Note that all these variables, excluding the deficit‐to‐gross domestic product (GDP) numbers, are annual growth rates and, where relevant, all are real values at 1995 constant prices. It is clear, first, that economic growth rates have been modest, with the highest recorded being 4,3 per cent in 1996. Furthermore, the trend over this short period has been downward until 1999, followed by a levelling off to the 3 per cent growth rate recorded at the beginning of the period.

Selected economic indicators for South Africa, 1995–2002

	Percentage change in:
Year	GDP	Gross fixed capital formation	Exports of Goods and Services	Imports of goods and Services	Disposable household income	Core inflation	Deficit‐to‐GDP ratio	Savings‐to‐GDP ratio
1995	3,1	10,7	10,3	16,8	4,8	8,7	−4,6	16,5
1996	4,3	9,0	9,2	8,7	4,6	7,4	−5,1	16,1
1997	2,6	5,7	5,6	5,4	3,0	8,6	−5,0	15,1
1998	0,8	4,6	2,5	1,5	0,5	6,9	−3,7	14,8
1999	2,0	−8,1	1,4	−7,4	1,1	5,2	−2,8	15,4
2000	3,5	0,8	8,4	7,1	3,4	5,4	−2,2	15,2
2001	2,8	3,2	2,5	0,3	2,9	5,7	−2,0	14,8
2002	3,0	6,5	−1,4	3,1	3,4	10,1	−1,4	16,1
Notes: 1. The GDP growth rate is the percentage change in real GDP at market prices. 2. Core inflation is at a 2000 base year, and refers to metropolitan households only. Source: SARB (2003).

Reflective of these tepid growth rates, then, has been a secular decline in gross capital formation. This is indicative of the relatively poor domestic and foreign investment climate since 1995. Often the key driver of domestic investment levels, the stagnant national savings levels – which remained in the 15–16 per cent to GDP band – are indicative of the inability of the economy to provide the financial resources required to kick‐start the economy onto a higher growth trajectory. However, as we will see later, the reasons behind low investment levels are more complex than just the low levels of savings.

Slow growth in aggregate demand has resulted in decreasing household disposable income growth which, as the table illustrates, remained stagnant in the period 2000–2. The country's difficulties with integrating into the world economy and maintaining international competitiveness are most evident in the export growth rates. At their highest in 1995 at over 10 per cent, export volumes have grown steadily at a slower pace since 1995. For the first time in 2002 we witnessed an absolute decline in export growth rates.

One fact that emerges clearly is that macroeconomic stability has been rigidly maintained in the economy. Hence, inflation rates have remained within a fairly narrow band and were in the one‐digit range until 2001. (The double‐digit inflation in 2002 is a function of the excessive food price inflation during the year; see Bhorat & Oosthuizen, 2002.) In addition, the deficit‐to‐GDP ratio has come down remarkably from a high of 5,1 per cent in 1996 to 1,4 per cent in 2002. It is fair to say that the deficit reduction programme of the new government has probably been its most successful policy intervention to date. However, growth rates together with export volumes did not expand fast enough initially, and furthermore have declined over the period. Given the size and scale of the poverty, inequality and labour market challenges that South African society faces, it is clear that the current domestic economic performance has not been sufficient to begin to affect these problems.

South Africa's Gini coefficient has always served as the starkest indicator of the country's unequal distribution of income. (The Gini coefficient always has a value between zero and one. The larger the number, the higher the level of inequality within the given distribution.) For a long time, our Gini was the highest recorded in the world. Table 2 compares South Africa's Gini coefficient and income shares with those of countries with similar income levels. The Gini and headcount indices are drawn from the Income and Expenditure Survey of 1999 (WEFA Southern Africa, 1999), which is an unofficial update of the IES for 1995. Both estimates are based upon household income figures. It represents the latest available data set, at the time of writing, on household income and expenditure accounts in South Africa. More recent labour market statistics, such as those provided for in the Labour Force Surveys (LFSs), do not allow for the construction of inequality and poverty indices.

Measures of poverty and inequality by race and gender of household head and international estimates

Household head	Headcount index	Poverty gap ratio (%)	Gini	Coefficient of Variation
African	38,22	14,2	0,53	1,80
	(0,021)	(0,142)
Coloured	21,51	6,6	0,48	1,13
	(0,022)	(0,066)
Asian	3,73	0,9	0,47	1,23
	(0,006)	(0,009)
White	3,03	0,8	0,46	1,25
	(0,030)	(0,008)
Male	26,39	9,2	0,60	1,81
	(0,029)	(0,011)
Female	43,52	17,0	0,53	1,81
	(0,027)	(0,012)
Total	32,02	11,8	0,60	1,91
	(0,029)	(0,011)
International estimates
Brazil	17,4 (1990)		0,607 (1998)
Malaysia	15,5 (1989)		0,492 (1997)
Venezuela	31,3 (1989)		0,495 (1998)
Poland	23,8 (1993)		0,414 (1998)
Thailand	13,1 (1992)		0,316 (1998)
Notes: 1. Standard errors are in parenthesis, and are corrected for according to frequency weights, the primary sampling unit and sampling stratification. 2. Figures in parenthesis for international estimates refer to the year the survey was undertaken to derive estimates. 3. The headcount measures for the international estimates refer to the share of the population below the national poverty line of the individual country. Sources: WEFA Southern Africa (1999).

From the table it is clear that Brazil and South Africa are far less egalitarian societies than the other nations presented here, but also that Brazil has a slightly higher level of income inequality compared with South Africa. (Note that because of variability in the date of data collection and differing methodologies, these figures should be taken as indicative only.) Both these Gini values are extremely high, however, indicating very skewed distributions of income. By comparison, Poland and Thailand have Gini coefficients of 0,41 and 0,32, respectively, showing that these economies have a significantly more equitable distribution of income.

The Gini has also been isolated by race and gender for South Africa. It is therefore evident that by race, higher levels of inequality are found amongst African households, where the Gini stands at 0,53. In comparison, the Gini for non‐African households is significantly lower – ranging between 0,46 and 0,48. This highlights the well‐known fact that in recent years it has been the growing inequality amongst African households that is driving the national inequality measure. Interestingly, the highest recorded Gini in these subgroups is for male‐headed households where the index stands at 0,60, while female‐headed households yield a lower level of inequality, measured at 0,53.

The poverty measures, based on the simple headcount index, yield equally disturbing trends. Hence, the data show that in 1999, just under a third of South African households were poor. Of the estimated total of 11,4 million households, approximately 3,7 million were below the poverty line. The poverty line used here was an annual household income of R12 982,50. This was based on the 1995 household poverty line of R903 per month, drawn from May et al. (1995), and updated using the core inflation figures for the period 1995–9.

The racial breakdowns reveal the maldistribution of this poverty incidence. Hence, we find that while about 38 per cent of African households are poor, only 3 and 4 per cent of white and Asian households, respectively, are earning below the poverty line. Coloured households reflect poverty figures much closer to those of Africans. Given that access to income is derived primarily through the labour market, the differing opportunities and options available to Africans and coloureds in the labour market remain key to understanding this differential poverty status.

3 DETERMINANTS OF GROWTH IN SOUTH AFRICA

A wide range of micro‐ and macrofactors influence economic growth in the long term. Typical determinants of growth are changes in the physical stock of capital (investment) in an economy, the accumulation of human capital and technology (i.e. the process by which progress in technology contributes to the increasing productivity of the economy). While increases in investment and productivity in the economy can explain growth, the reasons behind slow growth in productivity and investment in capital and human stock depend on, inter alia, supply‐side and demand‐side factors, institutional issues and the policy environment.

It is important for policy makers to grasp how the economics literature provides a framework for contemplating the growth question. Growth in its simplest form is determined primarily by three critical variables – the growth of capital, labour and technology and/or productivity. Based on Solow (1956), output is a function of total factor productivity, physical capital and labour: (--1)

where:

1.	Y is output at time t
2.	A is the overall productivity parameter
3.	K is capital
4.	L is labour
5.	a and a–1 are the elasticity of output with respect to capital and labour

This basic equation explains growth accounting by telling us what the relative contribution of capital, labour and productivity effects are to total growth in an economy. We take as our point of departure that growth in an open economy is associated with increasing efficiency – it is this efficiency parameter (a) in the production function Y=f(K, L, a) that ultimately drives growth. Sustained increases in physical capital are unlikely to occur in an economy where inefficiency and productivity levels are low. However, myriad policy decisions in different sectors of the economy ultimately drive the efficiency parameter and it is therefore difficult to trace every possible factor. A useful approach is to think conceptually about how specific policies in specific areas impact on the GDP.

3.1 Investment

One of the factors that explain South Africa's low growth is low investment. Investment in capital stock is generally considered the primary source of growth. During the second half of the 1990s investment languished at around 16–18 per cent of GDP, while other countries at comparable levels of income averaged considerably higher rates. While private sector investment (including in public corporations) has grown by an average of 5 per cent per annum over the decade, it has declined during the second half of the period. Public sector investment has remained more or less constant in real terms at about 2,5 per cent of GDP.

If we compare South Africa's investment ratio in the 1990s relative to other comparable countries, the figures are startling (Table 3).

Investment as a percentage of GDP, selected countries

Region	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000
South Africa	11,83	11,89	12,03	13,97	15,55	18,22	16,90	16,00	15,52	14,60	15,03
Brazil	20,17	19,77	18,93	20,85	22,15	22,29	20,67	21,50	21,20	20,40	20,50
Chile	25,11	22,55	23,81	26,50	24,10	25,79	26,88	27,23	26,64	21,42	23,44
Malaysia	32,22	35,63	35,98	38,30	39,74	43,15	42,11	42,77	26,83	22,14	25,58
Thailand	41,35	42,84	39,96	39,94	40,18	41,85	41,58	33,33	20,32	19,94	22,67
Source: World Bank (2002).

Recent research shows that crime, theft and instability (comprised of various aspects such as policy uncertainty and governance‐related issues) remain the most important deterrents to growth and investment in South Africa (Gelb, 2001). These issues will be discussed in more detail later.

It is, however, important to bear in mind that the relationship between investment levels and growth is not monotonic. For example, in Ireland growth was higher in periods where investment as a percentage of GDP was lower. Investment as a percentage of GDP in Ireland was one of the highest in the 1970s (25 per cent) relative to the United Kingdom, for example, for the same period (15 per cent), but failed to converge with the latter. This is attributed to the inefficiency of investment due to high levels of protection in the Irish economy. Similarly, Fedderke (2001) argues that the allocation of capital stock in South Africa has changed to reflect more market‐based incentives for improving the efficiency of investment. Notwithstanding the importance of the increased efficiency of investment, we cannot get away from the fundamental problem that increased growth cannot be achieved without a substantial increase in the investment‐GDP ratio.

3.2 Productivity growth

From the supply side, the two factors that explain growth in an economy are growth in capital accumulation (physical and/or human), and productivity growth (Figure 1). Multifactor productivity (MFP) is a measure of the growth in output that is not explained by the growth in the quantity of inputs. Rather, it is the increase in the efficiency of inputs relative to outputs that drives MFP. There has been a consistent decline in MFP in the last three decades. However, MFP began picking up during the mid‐ to late 1990s. Average productivity growth in the 1990s was about 2 per cent and picked up from 1995 onwards.

Productivity growth in South Africa, 1970–2001

Note: Series is a productivity index, where 1995 = 100.

The source of South Africa's productivity growth (Figure 1) remains a subject of debate. One argument is that the country's productivity growth in the 1980s was based on increasing accumulation of capital, but in the 1990s was largely attributed to increases in efficiency or total factor productivity (TFP) (see Fedderke, 2001).

Various production function estimates were conducted. Two particular studies achieved strikingly similar results, as seen from Table 4. In essence, these estimates show that while South Africa relied on investment for its growth in the 1970s, it came to rely more on productivity growth in the 1990s.

Relative contribution of factors to growth (% contribution)

Source	Period	Capital	Labour	TFP
Goldman Sachs (2003)	1970s	2,6	1,6	−1,0
	1980s	1,3	1,0	0,0
	1990s	0,5	−0,9	1,8
Fedderke (2001)	1970s	2,54	1,77	−0,49
	1980s	1,24	0,62	0,34
	1990s	0,44	−0,58	1,07

The view that South Africa has seen increasing growth in productivity has, however, been questioned. One explanation is that low economic growth and a decline in investment – or a reduction in capital stock – partly account for TFP growth (TIPS Forum Proceedings, 2001). In other words, a declining proportion of gross capital accumulation in GDP drove efficiency growth as enterprises were forced to use existing capital stock more effectively (Hartzenberg & Stuart, 2002). Another explanation is that there have been a series of government policies – such as trade reform, some privatisation and liberalisation – that have contributed to efficiency in the economy. Without these policies, growth could have been lower than current levels. However, it can also be argued that these efficiency policies have resulted in higher labour productivity, in that firms have started shedding labour in order to remain competitive in liberalised markets.

In summary, productivity growth in the economy has, on average, increased in the 1990s relative to the 1980s. This has to do partly with increasing efficiency associated with, for example, trade reform and other efficiency‐enhancing measures in the economy, as well as reductions in capital stock and labour shedding. As a result, both factors of production are employed more productively. These are, however, of a low base. It is important to emphasise that as much as we have detected improvements in productivity growth, we have to be careful of the interpretation of this growth. TFP can rise as firms shed workers (perhaps to raise competitiveness), but this is not efficient from an economy‐wide point of view if it leads to unemployment of potentially productive resources.

3.3 Labour market trends

Human capital is another important variable in a typical production function. We do not, however, study the human capital problem directly, but simply look at the skills constraint in the economy through a review of the labour market. The democratic government inherited a labour market that had been subject to the long‐term effects of both structural shifts and technological change in the domestic economy. The former was represented by the shift in output away from the primary sectors towards the services sectors, while the latter has been manifest in the onset of the microelectronics revolution as well as significant increases in capital–labour ratios. The labour market consequences of these changes have been to increase the demand for highly skilled workers, combined with large‐scale attrition at the bottom end of the labour market. For a historical account of these shifts and their impact on the South African labour market, see Bhorat & Hodge (1999), Bhorat (2000) and Edwards (2000).

Table 5 presents a snapshot of the key labour market statistics for the period 1995–2002. Concentrating on the labour force data according to the expanded definition of unemployment (the ‘unofficial’ definition), it is evident that the economy created about 1,6 million jobs over this period. While the sectoral and skills detail of this growth varied, it is clear that the notion of aggregate ‘jobless growth’ in the South African economy is erroneous. The economy, in the aggregate, has been creating jobs rather than shedding them.

A snapshot of key labour market trends: 1995–2002

Category	1995	2002	Change	% change	Target growth rate	Employment absorption Rate
Employment	9 557 185	11 157 818	1 600 633	16,75
Unemployment			3 405 014	87,67
(expanded definition)	3 883 819	7 288 833
Labour force	13 441 004	18 446 651	5 005 647	37,24	52,38	31,98
Official definition estimates
Employment	9 557 185	11 157 818	1 600 633	16,75
Unemployment				123,69
(strict definition)	1 909 468	4 271 302	2 361 834
Labour force	11 466 653	15 429 120	3 962 467	34,56	41,46	40,39
Notes: 1. The official definition estimates are based on the assumption of the strict definition of unemployment, and hence presume a labour market that excludes the discouraged work‐seeker. 2. The 1995 data have been reweighted with the 1996 Census weights to ensure comparability across the two time periods. Sources: StatsSA (1996; 2003).

It is important to place this absolute expansion of employment into context. Specifically, it is necessary to assess the number of jobs that have been created, relative to the annual numbers of new entrants to the labour market between 1995 and 2002. The data indicate that between 1995 and 2002 the number of new entrants increased by about 5 million. This means that about 3,4 million individuals – some of whom were first‐time entrants to the labour market – have been rendered jobless or have remained so since 1995. As a result, unemployment levels increased to over 7 million individuals in 2002.

Much of the debate around employment trends in the post‐apartheid period have become anchored around the notion of ‘jobless growth’, namely that simultaneously with unspectacular economic growth, jobs have been shed across most sectors in the economy. The initial data here make it plain that the economy did not experience an absolute decline in employment. Put differently, applying the notion of ‘jobless growth’ to characterise post‐1995 employment trends is simply wrong. However, it is important to note that while we did not have jobless growth in this period, we have clearly had ‘poor employment growth’. In order to provide a basic litmus test for these labour market trends, this study uses two very simple performance indicators, shown in Table 5. These are the ‘target growth rate’ and the ‘employment absorption gap’. The former summarises the desired employment growth rate for the economy as a whole, measured by simply allowing employment to grow from 1995 onwards by the full change in the labour force over the period 1995–2002. Specifically, the target growth rate is measured by: (--2)

where:

1.	EAP refers to the economically active population for group k
2.	L is the number of employed individuals by any given covariate

Note that because this target growth rate captures the growth required to provide employment to only the new entrants since 1995, it is essentially the rate of growth required to absorb all net new entrants, independent of the unemployment numbers existent in the base year (1995). The employment absorption rate is the ratio between the actual employment growth and the desired (or ‘target’) rate, and is expressed as a percentage. The closer the employment absorption rate is to 100, the better the actual employment performance is relative to the desired performance. These figures are critical, as they are predictors of relative employment performance – something that the standard growth rates are unable to do.

The data from Table 5 thus suggest that while employment grew by 17 per cent over the period concerned, if all the new entrants were to have been placed in employment since 1995 employment would have had to grow by 52 per cent over the period. In other words, in order to maintain unemployment at its 1995 levels, employment should have risen by just over three times the existing rate. In terms of the employment absorption rate, the data suggest that over the period the economy was able to provide 32 jobs for every 100 economically active individuals in the labour market. Even by the strict definition of unemployment, which is the government's official representation of the labour market, the economy has created only 40 jobs for every 100 members of the labour force.

While this analysis falls well short of providing formal output–employment elasticities, it provides fairly powerful (albeit initial) evidence for the fact that the growth–employment relationship in this seven‐year period has been notably inelastic. This low elasticity is not as critical a problem when growth rates are in order of 10–15 per cent, but in the context of a growth rate of 2–3 per cent we are facing daunting challenges.

4 A REVIEW OF KEY CONSTRAINTS TO GROWTH AND EMPLOYMENT

Having tried to identify what we view to be the key drivers of long‐term economic growth in South Africa, it is important that we attempt to clarify some of the potential constraints on this growth trajectory. These constraints lie in diverse areas such as the labour legislative environment; the role of capital markets and financial intermediation, given South Africa's status as a small, open economy; trade and tariff liberalisation; the macroeconomic and regulatory policy environment; and, finally, a variety of political and institutional concerns that are important for understanding long‐term economic growth. The sections that follow provide an overview of the issues of concern within each of these broad areas and, in doing so, implicitly create a framework for understanding in more detail the mechanics of those factors that may be inhibiting growth in South Africa.

4.1 Labour market policy

The structure of the South African labour market either as a source of, or deterrent to, growth is a highly contentious area of economic policy. The labour market as a factor is unique in the sense that it directly contributes to equality and efficiency. One must first distinguish how much of the wage rates impact on growth and efficiency and what the implications are for employment. The relationship between wage rates and employment is conceptually more straightforward than is the relationship between wage rates and growth. This section focuses specifically on the link between the former. The more direct link between wages and growth is more complex and requires in‐depth research. However, based on a review of the literature on unemployment in South Africa, we can conclude that the unemployment problem is not exclusively a macroeconomic problem, or a trade policy problem or, for that matter, a labour market problem. Secondly, wages in and of themselves are not necessarily the sole explanatory factor behind the employment crisis. Thirdly, the changing demand for increasing skilled labour is the result of a complex array of factors and cannot be attributed simply to globalisation or trade liberalisation (Cassim et al., 2002).

Notwithstanding the argument that wages in themselves do not constitute the main problem, there is some evidence to suggest that wages may deter employment in some sectors but not in others. High wage rates matter for some sectors but not for others – or they may matter less for the semi‐skilled than for the unskilled. At the end of the day, however, there is some trade‐off between real wage growth and employment (Mazumdar & Van Seventer, 2002). It all depends on how the gains from real wages growth are shared.

The use of wage–employment elasticities to inform policy is often contentious. However, economists generally agree that the labour demand curve is downward sloping, and that the more desirable outcome is the possibility of shifting the curve of derived demand for labour so that more workers are demanded at any given wage than before.

Table 6 provides estimates of overall wage–employment elasticities for African, coloured and Asian workers in South Africa's formal sector.

Wage elasticities for African, coloured and Asian employees in the formal sector

Sector	Long‐term	Short‐term
Beverages	−0,184	−0,095
Tobacco	−0,057	−0,018
Textiles	−0,984	−0,346
Wearing apparel	−2,508	−0,709
Wood products	−0,196	−0,603
Furniture	−0,364	−0,139
Chemicals	−1,166	−0,344
Rubber and plastic	−0,243	−0,153
Non‐metal minerals	−2,929	−0,451
Basic metals	−0,758	−0,166
Fabricated metals	−0,466	−0,175
Non‐electric machinery	−0,632	−0,408
Transport equipment	−0,440	−0,201
Mining	−0,146	−0,118
Construction	−0,554	−0,360
Services	−0,948	−0,147
Weighted mean	−0,709	−0,156
Source:Fallon & Lucas (1998).

From the table it is evident that the long‐term national average of elasticity is –0,71, which is reported as the weighted mean. This is the most widely quoted elasticity figure in the debate thus far. In other words, for the economy as a whole, a 10 per cent increase in the wage rate will lead to a 7,1 per cent decrease in these employment levels. Note that this is the long‐term elasticity, seen to be about three years. The short‐term elasticity (being about one year) is much lower. In other words, the argument is that the disemployment effects of a wage hike will grow over time. Generally, the short‐term estimates are always lower than the long‐term results. This long‐term estimate agrees with other studies on the South African economy. For example, Bowles & Heintz (1996), using a different model, derive an aggregate elasticity of 0,73, although their sample is composed only of subsectors within the manufacturing industry. Bhorat & Leibbrandt (1998) estimate the wage elasticity of employment for manufacturing as a whole and for a select set of manufacturing subsectors. Several of these estimates are in the region of –0,7.

Most recently, Fields et al. (1999) estimated elasticities for the period 1980–98. These estimates are provided in Table 7. These authors conclude that the elasticities are large and have been increasing over time. Hence, as the table illustrates, their estimate for the period 1990–3 was –0,35, but for the period 1994–8 it had increased to –0,52. These aggregate elasticities are for the private sector only. The public sector elasticities are lower, but statistically insignificant. In addition, the private sector estimates are slightly lower than in the studies quoted above.

Wage elasticities by main sector

Sector	1990–3	1994–8
Mining and quarrying	−0,19	−0,96*
Manufacturing	−0,06	−0,45*
Construction	−0,49*	−0,63*
Utilities	−0,02	−0,03
Commerce, catering and accommodation	−0,13	0,50*
Transport and communication	−0,10	−0,22
Financial services	0,20*	−0,01
Community, social and personal services	0,05	−0,50*
Private sector total	−0,35**	−0,53**
Notes: *Statistically significant at the 5 per cent level; **statistically significant at the 1 per cent level. Source: Fields et al. (1999).

Ultimately, these elasticity estimates indicate that employment levels are sensitive to rising wage levels. However, employment losses have in the past been attributed to non‐wage variables such as structural changes in the economy with the decline of the mining sectors, as well as technological changes in the economy. Therefore, while wage increases will no doubt result in employment losses, it is not immediately clear whether these wage increases were the sole reason for the employment patterns we have observed thus far in the economy. An interrelated issue on the wage–employment nexus is the need to initiate more research and work on the wage bill as a whole. South Africa's chronic skills shortage means that workers at the top end are paid a premium. The question is to what extent this premium is not accounted for by the ‘shortage effect’, but rather by firms paying their skilled workers excessively. Shares of the wage bill that go to skilled workers relative to unskilled workers – compared with the situation in other countries – would be a good starting point in such an analysis. Should there be more than just a skills premium paid to these employees, then clearly the excessiveness in the wage bill would not only be at the bottom end.

One of the key debates on the labour market and its role in shaping economic growth patterns concerns the extent and level of employment flexibility that exists for both employers and employees. We are able to garner at least some initial primary and some secondary evidence reflecting on whether laws governing hiring and firing in the South African labour market may or may not be inimical to long‐term employment growth. One of the few surveys, the World Bank Large Manufacturing Firm Survey conducted under the joint auspices of the Greater Johannesburg Metropolitan Council and the World Bank in 1999, looks at a formalised bargaining environment as a key consideration in hiring decisions.

Interestingly, the majority of firms in the sample (61 per cent) viewed bargaining council agreements and their extensions as having no effect on firm employment levels (Table 8). Some 21 per cent of firms viewed the bargaining councils as hindrances to employment expansion.

Impact of bargaining council agreements on employment

Category	No. of firms	Percentage
Increases	13	4,04
Declines	67	20,81
No effect	197	61,18
Not applicable	45	13,98
Total	322	100
Source: World Bank (1999).

The second question in the survey asked firms to reflect on the effect of specific labour legislation introduced by the democratic government, namely the Basic Conditions of Employment Act (BCEA) and the Labour Relations Act (LRA). Once again, the majority of firms felt that the Labour Relations Act had no effect on their employment levels. The employment effects of the Skills Development Act and the Employment Equity Act were also raised in the survey although, as expected, an overwhelming number of firms viewed these laws as having no effect on employment levels.

Ultimately, however, this admittedly tentative evidence on a very confined sample of firms does suggest that manufacturing firms on the whole do not view the labour legislation environment as a significant constraint on employment expansion within their enterprises. Hence, whether one refers to specific legislation such as the LRA and the BCEA, or the more general industrial relations environment, there is little to suggest as yet that these laws are inhibiting the growth of employment. A critical addendum, however, is the fact that the survey questions make extremely general reference to the role of labour legislation in employment creation. They do not deal with specific clauses of the BCEA and LRA to which employers, if prodded, may have responded more negatively. For example, it is often argued that the legislation governing dismissal procedures are particularly onerous for employers, and even more so for small‐ and medium‐sized enterprises. No hard data, however, exist on employers' experiences with, and responses to, these specific clauses in the legislation. One would need to undertake a more in‐depth firm survey to uncover these more detailed reservations and concerns around the relevant components of the legislation.

4.2 Capital markets and financial intermediation

With regard to capital markets, it has often been pointed out that South Africa's financial sector is fairly developed. However, there are some structural problems that need to be examined in more detail. What is considered an important question is whether we are reaping the benefits of a well‐developed financial sector, and whether this is translating into growth in South Africa. Notwithstanding the sophistication of the sector, there is a great deal of financial exclusion owing to high inequality in income in South Africa.

As far as financial regulation is concerned, South Africa does not suffer from the levels of systemic failure characteristic of many other emerging markets. This is very important to our growth prospects, as it reduces the risk factor to foreign investment, whether direct or indirect. Although there have been minor crises in the banking sector with the collapse of some small banks, by and large the sector is well regulated.

Preliminary evidence indicates the following financial sector‐related problems in South Africa. The cost of capital is high, and this has a negative influence on investment. However, it is unclear whether this is a function of the lending spread or monetary policy that influences interest rates. Okeahalam (2002) argues that margins in the South African banking market have been high by international standards – 4 per cent in South Africa, relative to of approximately 2 per cent in European markets.

Access to finance for small enterprises is difficult. In the case of small, medium and microenterprises (SMMEs), this market failure reflects a lack of information and causes high transaction costs. SMMEs largely lack information about banking procedures and loan requirements, while banks struggle to assess the viability of SMMEs as loan applicants. As a consequence, many potential borrowers do not receive or even apply for loans. The issue of financial intermediation and SMMEs remains complex. More research is needed to come to reasonable conclusions as to how capital markets, or government intervention in the capital markets, can facilitate better access (see Berry et al., 2002).

The South African financial sector is undergoing a process of gradual liberalisation. Considerable regulatory changes have taken place in the sector, particularly in opening it to foreign investment. However, although foreign competition has raised the stakes in providing services for the public and corporate sectors and for wealthy individuals, increased competition for the lower‐income market has not been forthcoming.

Despite the opening‐up of the financial sector, some markets remain uncontested. There are high levels of concentration in the banking sector – the four largest banks in South Africa (Standard Bank, ABSA, First National Bank and Nedbank) hold over 80 per cent of the market share. There is some evidence to suggest that the high level of concentration does impact on performance and pricing behaviour. For example, banking costs are considered high in South Africa. This may be related to market structure issues.

In summary, the lack of competition in the banking sector, as well as the increasing cost of capital (both as a result of monetary policy and bank risk), has had an effect on equality and investment. Nevertheless, these are rather sweeping statements and more thought needs to be given here.

4.3 Trade reform

The South African economy can be described as a moderately protected economy by middle‐income country standards. The country embarked on a gradual process of liberalisation since the 1980s. A significant milestone in South Africa's trade reform history has been the process of transparent commitment to phase down tariff schedules under our World Trade Organisation (WTO) commitments.

The tariff phase‐down schedule under the WTO appears in Table 9, which shows that South Africa's average tariff declined from 11,7 per cent in 1994 to 5,3 per cent in 2000.

Tariff phase‐down under the WTO commitments

New ISIC	Description	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004
3	Textiles	30,1	33,8	31,8	24,9	23,4	21,9	20,3	18,7	17,3	17,3	17,3
4	Clothing, excluding footwear	73,7	73,6	68,2	54,6	50,5	46,4	42,4	37,7	33,2	33,2	33,2
5	Leather and leather products	14,9	14,8	14,1	16,5	15,7	14,8	14,8	14,8	14,8	14,8	14,8
6	Footwear	37,5	41,6	39,1	36,8	34,2	29,1	29,1	29,1	29,1	29,1	29,1
7	Wood and wood products	13,9	3,6	3,4	3,5	3,3	3,1	3,1	3,1	3,1	3,1	3,1
8	Paper and paper products	9,6	9,3	9,1	8,8	8,7	8,5	7,9	7,3	6,8	6,2	5,6
9	Printing and publishing	8,1	1,3	1,2	1,1	1,0	1,0	1,0	1,0	1,0	1,0	1,0
10	Petroleum and petroleum products	1,6	–	–	–	–	–	–	–	–	–	–
11	Industrial chemicals	9,3	7,5	7,5	1,7	1,7	1,6	1,6	1,6	1,6	1,6	1,6
12	Other chemical products	9,0	3,8	3,7	2,7	2,6	2,5	2,5	2,5	2,5	2,5	2,5
13	Rubber products	30,5	14,5	14,1	15,8	15,4	14,9	14,6	14,4	14,0	14,0	14,0
14	Plastic products	19,8	14,7	13,7	13,2	12,6	12,0	12,0	12,0	12,0	12,0	12,0
15	Glass and glass products	11,8	9,5	9,0	8,3	7,9	7,6	7,6	7,6	7,6	7,6	7,6
16	Non‐metallic mineral products	10,6	8,7	8,1	8,4	8,0	7,7	7,7	7,7	7,7	7,7	7,7
17	Basic iron and steel products	7,6	4,4	4,2	4,2	4,1	3,9	3,9	3,9	3,9	3,9	3,9
18	Non‐ferrous metal products	2,3	2,3	2,3	2,3	2,2	2,0	2,0	2,0	1,9	1,7	1,7
19	Metal products, excluding machinery	13,1	8,2	7,8	7,8	7,6	7,4	7,4	7,4	7,4	7,4	7,4
20	Non‐electrical machinery	6,5	1,4	1,3	1,4	1,3	1,3	1,3	1,3	1,3	1,3	1,3
21	Electrical machinery	11,0	6,1	6,0	5,8	5,8	5,7	5,7	5,7	5,7	5,7	5,7
22	Radio, television and communication apparatus	12,1	5,1	3,7	2,4	2,3	2,3	2,3	2,3	2,3	2,3	2,3
23	Professional equipment, etc.	7,2	0,2	0,2	0,3	0,3	0,3	0,3	0,3	0,3	0,3	0,3
24	Motor vehicles, parts and accessories	55,4	33,5	31,7	29,3	27,9	26,1	24,8	23,2	22,1	22,1	22,1
25	Other transport equipment	1,4	0,4	0,4	0,3	0,3	0,2	0,2	0,2	0,2	0,2	0,2
26	Furniture	28,1	21,4	20,8	20,2	19,6	18,9	18,9	18,9	18,9	18,9	18,9
27	Other manufacturing	2,9	1,0	1,0	5,2	5,1	5,0	4,9	4,9	4,9	4,9	4,9
82	Mining	2,7	0,6	0,6	0,5	0,4	0,4	0,4	0,4	0,4	0,4	0,4
Total		11,7	7,2	6,8	6,1	5,8	5,5	5,3	5,1	4,9	4,9	4,9
Source: IDC (1993).

Other aspects of the WTO offer included increasing the proportion of bound tariffs from less than 20 per cent to just over 50 per cent; increasing the percentage of bound zero‐rated tariff lines to just over 25 per cent; and reducing the simple average tariff for industrial tariffs by one‐third in a phased reduction programme (GATT, 1995: 3).

Table 10 shows that South Africa's tariffs in agriculture are low by international standards. As far as industrial tariffs are concerned, these are relatively moderate. There are, however, peak tariffs above 20 per cent in products such as motor components and motor vehicles, and clothing and textiles. The major problem is that many tariff categories exist in the economy, meaning that South Africa's tariff structure is highly dispersed. The standard deviation is higher for manufacturing but has come down significantly from 18 per cent in 1997 to 9,3 per cent in 2001. The key priority for the government is to reduce the level of dispersion of tariffs and render the tariff structure more uniform.

Tariff structure for 1997, 2000 and 2001, with imports for 2000

Sector Year	Number of lines 2000	Imports (5) 2000	Imports 2000	Weighted average 2000	Average 1997	Average 2000	Average 2001	Standard deviation 1997	Standard deviation 2000	Standard deviation 2001
Agriculture	295	1,459	0,8%	1,4%	5,6%	4,2%	4,0%	8,9%	7,5%	7,2%
Mining	107	25,559	14,5%	0,0%	1,4%	1,2%	1,4%	3,4%	3,2%	3,7%
Manufacturing	5,479	149,539	84,7%	8,6%	15,6%	6,7%	6,7%	18,0%	9,6%	9,4%
Total	5,883	176,564	100,0%	7,3%	15,1%	6,5%	6,5%	17,8%	9,4%	9,3%
Notes: Unless otherwise stated, averages are unweighted. The second column reports imports in R million at current prices, while the third column reflects percentages of total imports across the reported sectors. Sources: Data obtained from the Department of Trade and Industry, the Department of Customs and Excise and Trade and Industrial Policy Strategies (TIPS).

Has trade reform in the 1990s induced productivity growth, or acted as a constraint on it? While some evidence is suggestive of the positive contributions to overall productivity growth, it can be argued that South Africa has experienced an increase in import penetration in almost every manufacturing sector, although no major deindustrialisation has been witnessed. There is also some evidence to show that trade liberalisation has had a positive effect on South Africa's agricultural sector. Trends in trade of agricultural products since the start of the trade liberalisation period indicate that the quantity of both imports and exports has increased almost fourfold. Moreover, studies have also established that liberalisation, which is anticipated to induce greater efficiency via the reallocation of resources to more productive activities, has seen a positive relationship between trade and TFP (Cassim et al., 2002).

Although further reform is desirable, major acceleration in this regard will not have a correspondingly major impact on growth. A reduction of tariff peaks will nevertheless be significant. It must be emphasised that trade distortions in the economy are not very serious if protection is moderate; however, they are quite serious if protection is high. The distorted effect of tariff peaks in clothing (40 per cent) and agroprocessing, as well as tariffs on inputs such as sugar and textiles, can have a significant cost‐raising effect on consumers, producers and the economy as a whole.

It is also important to bear in mind that there is no conclusive evidence to show that South Africa's trade reform has had a major important influence on poverty or employment in either direction. Certainly at the margins it may have contributed to some employment losses or increasing capital intensity. What is clear is that trade liberalisation is not responsible for major job losses, nor is it simply a major employment creator in the short term. Other factors such as low domestic demand, lack of skills, technology and so on have a more direct relationship with employment.

4.4 Macroeconomic policy as a constraint on growth

It is generally difficult to reach solid conclusions about the impact of macroeconomic policy on growth. There is a lively, if somewhat ill‐informed, debate in South Africa on whether macroeconomic policy in the last five to ten years has served as a catalyst for, or deterrent to, overall growth. Since the adoption of the Growth, Employment and Redistribution (GEAR) strategy in 1996, the South African government has successfully reduced its fiscal deficit and contained inflation, albeit by means of raising real interest rates (Berry et al., 2002).

According to some schools of thought, a major constraint on economic growth is macroeconomic policy, where fiscal discipline and conservative monetary policy are creating macrostability at the cost of growth. It is common logic that fiscal discipline will dampen the growth prospects as increasing expenditure by the government creates more economic activity. Increasing fiscal expenditure may boost short‐term aggregate demand, but it depends on the behaviour of entrepreneurs whether this boost will be sufficient to ignite the accelerator mechanism by which investment will take place to meet higher demand. If the accelerator mechanism is strong enough to outweigh the possible crowding‐out mechanism of fiscal deficits, a permanently higher level of output will be reached. Adherents of the Lucas Curve,2 of course, believe that this is not possible because rational expectations assume that these entrepreneurs will com ‐pletely foresee the crowding out and abstain from investment. However, if expenditure is undertaken in infrastructure investment and human capital accumulation, this could be different. Fiscal policy does not operate in isolation and demand effects could still be short term if other major structural problems in the economy persist.

Nevertheless, it has been argued that the signalling value to investors about responsible management of the macroeconomy and the minimisation of the risk of increasing budget deficits in the context of economic stagnation – which is evident in many developing countries – must not be underestimated. This is not to suggest that macroeconomic management alone determines investor confidence. There are many other subjective factors (such as those in Zimbabwe) over which the government has no control. This said, there may be room for increases in fiscal spending in the right areas (e.g. maintenance of infrastructure) and this may contribute to growth.

Monetary policy has increased the cost of formal credit as a capital source for new investments. Fluctuations in the exchange rate impact negatively on firms that are highly dependent on imported supplies and equipment, while its depreciation was seemingly not sufficient to make South African products more competitive in export markets. It is the differential impact on the spectrum of micro‐ to medium firms and the sectors in which they operate that matters and needs to be investigated further. Previous econometric investigation has suggested that the cost of capital (in which the interest rate has a large weight) is an important factor in explaining private sector investment (Fedderke, 2001).

Another important macrophenomenon is the low savings rates in the South African economy. Gross domestic savings fell sharply in the 1990s to around 15 per cent of GDP, relative to the 1970s when it was about 24 per cent of GDP. An important and controversial issue is whether an economy such as that of South Africa is savings constrained or investment constrained. What is important, however, is that if investment were to increase, the low savings rate would be a significant constraint. The reasons behind the low savings in the economy stem from growing indebtedness due to the high prevalence of credit facilities in South Africa. More significantly, income distribution and high levels of poverty in the context of low economic growth mean that savings levels will stay low.

An economy that has low savings rates and no foreign capital inflows will not be able to mobilise resources for investment in the economy (Nell, 2003). However, as Gibson & Van Seventer (1996) point out, even if an economy generated sufficient savings, we cannot assume that total savings will automatically be invested; proper incentives must exist for the investment to be undertaken. This is particularly true in the context of high levels of capital mobility, such as corporations in South Africa with high savings levels that do not translate these into productive investment activities in the country.

The role of macroeconomic policy in either spurring on or deterring growth is not straightforward. It is, however, unrealistic to rely only on macropolicy for growth in an economy where fundamental structural problems exist.

4.5 Privatisation, regulation and competition³

Indeed, the slow pace of privatisation in South Africa is often cited in the media and the business community as one of the major reasons for low growth. The specific mechanisms by which privatisation chokes growth have rarely been specified. This is one of the areas in which potentially high welfare gains to the economy can be generated but, unfortunately, it is also an area that we know very little about. International experience has shown that privatisation per se is not a major determinant of growth and efficiency. A more significant constraint has been posed by the inefficiencies generated by monopolies or market‐structure problems.

The more relevant question is how the persistence of monopolies in major services and utilities hampers growth potential in the economy. Put differently, to what extent has the slow restructuring of South Africa's parastatals in the last decade resulted in foregone efficiency and productivity gains in the economy, specifically in utility sectors such as energy, transport and telecommunications? These gains provide significant inputs into downstream industries and services sectors, affecting their (international) competitiveness. The actual lack of liberalisation in services and utilities markets in the economy as whole (e.g. telephone prices that exceed international prices, high harbour costs, etc.) comes at quite a cost to economic growth – both financial and transaction costs. In addition, there is the potential impact on poverty. Access to basic infrastructure is a central tenet of the poverty debate in South Africa. Regulation of parastatals in utilities has had an impact on the penetration ratios of vital services such as water, telecommunications and electricity, thereby affecting the quality of life of the poor. The other important issue has been the extent to which market structure or regulation policy has had an impact on infrastructural investment.

The democratic government of South Africa inherited over 300 state‐owned enterprises (SOEs), with four of the firms accounting for 86 per cent of aggregate turnover, 94 per cent of total income, 77 per cent of all employment and 91 per cent of the total assets of these enterprises. The major state‐owned enterprises (parastatals) today are Eskom (energy sector), Transnet (transport sector), Telkom (telecommunications sector) and Denel (defence industry). They also comprise 91 per cent of estimated total state assets and 77 per cent of all employees in the top 30 SOEs.

The privatisation process in South Africa has been focused largely on divestiture of ‘non‐core businesses’, such as resorts, broadcasting stations and related services in the transport sector, as well as the restructuring of utilities by selling minority stakes to so‐called strategic equity partners and black economic empowerment groupings. What has been lagging is the introduction of greater competition in utilities and services that may have choked growth in the country.

We present some casual observations on two utility sectors to give a sense of how they impact on the growth question. The telecommunications industry, for example, has serious implications for communications costs, which are so critical to the economy. The African National Congress government inherited a fixed‐line monopoly that has been on a slow road to liberalisation. There has been less emphasis on introducing competition by allowing new entry than on allowing foreign equity participation and protecting the positions of incumbents. In March 1997, the government sold a 30 per cent stake in Telkom to a ‘strategic equity partner’, Thintana Communications.

Notwithstanding the introduction of some competition in telecommunications through the introduction of mobile services, the costs (including those of mobile services) in South Africa are currently still well above international costs. This situation is aggravated by major deficiencies in client services (Hodge 1999). Telkom remains a fixed‐line monopoly and therefore continues to reap monopoly rents. The problem of competition is compounded by the regulatory body's failure to impose stringent price capping, and by the government's decision to leave the incumbent as a vertically integrated entity responsible for grid management. Moreover, policy credibility, or at least policy predictability, has suffered from the wrangling over a second or third national operator. In sum, there are several ways in which telecommunications constrain growth – through prices, foregone investment in new fixed lines, and limited and high‐cost internet bandwidth.

Similarly, regulation and restructuring of transport have a critical impact on growth. Transport services are the most important services after distribution in South Africa and they account for at least 3 per cent of total intermediate inputs for most of the manufacturing sectors. The transport sector is very diverse and encompasses various broad sectors and subsectors. Apart from modes of road, rail, air and maritime transport, there are significant sub‐industries within each of these sectors. For example, road transport includes passenger transport, freight transport, support services for roads, and so forth.

Deregulation has been uneven in South Africa's transport sector, with significant liberalisation in some sectors relative to others. In civil aviation, for example, the domestic market has been significantly liberalised. The nature of competition within the transport sector is fairly significant in some areas and less so in others. One has to distinguish between intramodal and intermodal competition. A classic case of the latter is the competition between road and rail transport in South Africa. Road transport now accounts for 80 per cent and rail for 20 per cent of the overland freight transport market. The impact this has had on transport costs and the competitive edge, specifically on inland firms that export, has been considerable.

Shipping costs, on the other hand, are high and constitute an estimated 60 per cent of exports of many manufactured or primary products. It is important to note that these are financial and economic costs related to insufficient competition in shipping, and not simply because South Africa is geographically distant from markets. At another level, South Africa's port turnaround times tend to be up to five times slower than those of competitors. This is related to government monopoly in the sector. Other port‐related problems include, inter alia, poor rail–port interface and inadequate shunting locomotives. Once again, this is less a problem of regulation than of lack of competition in the sector.

In general, investment constraints have been the main problem in the transport sector. This relates to, for example, the inertia to initiate the right regulatory environment for port handling and airfreight.

Other efficiencies in the economy include mark‐ups in the goods sector. Recent econometric studies on pricing behaviour in South Africa suggest that mark‐ups at the macrolevel and at the sectoral level are well above those found in other countries. The economy‐wide impact of public policies in an economy with fixed mark‐up pricing, compared with one where prices clear markets, could well be far‐reaching but still need to be explored for South Africa.

4.6 The institutional, political and social context of growth

Although South Africa has its economic fundamentals right, growth and employment creation have been limited owing to inherent policy instability, corruption, crime, weak public institutions and weak corporate governance. Factors such as property rights, appropriate regulatory structures, quality and independence of the judiciary have been identified in the international literature as major contributors to growth. These so‐called non‐economic determinants of growth have been critical to South Africa's growth trajectory in the last decade. They are, however, difficult to quantify and very little research has been carried out in these areas. What we do know, based on time‐series econometric work and microeconomic evidence, is that they are of critical importance. We subsequently highlight three prominent deterrents to growth in South Africa.

4.6.1 Uncertainty

Various firm surveys (World Bank, 1999; Gelb, 2001) and econometric analyses (Fedderke, 2001) conducted in the last few years point out that uncertainty remains one of the key deterrents to investment and therefore to growth. Identifying sources of uncertainty is complex because the notion of uncertainty is amorphous, at best, and it is interpreted in different ways by investors.

There is a range of highly subjective factors that underpin the role of uncertainty as a deterrent to growth and investment. For example, the credibility of government policies may be questioned or uncertainty may be brought about by policies that could be reversed, such as the erratic liberalisation of utilities or trade reform. Perceptions of a weak property rights regime or poor governance are equally important to investor perceptions. Another form of uncertainty may come about through the social effects of HIV/Aids or crime. Although there is not authoritative literature on this aspect, uncertainty clearly has a critical effect on investment in the South African manufacturing industry. The threshold rate of return to investment is increased to provide for uncertainty. In other words, uncertainty implies risk that puts a higher premium on the rate of return to investment compared with a risk‐free environment (Fedderke, 2001).

4.6.2 Crime

South Africa is infamous for its crime rates. Actual statistics on crime are riddled with problems such as the capacity to record crime, the way it is reported, identifying the specific nature of the crime, as well as lack of reporting by victims. Notwithstanding these problems, the evidence suggests that crime is an overwhelming problem in South Africa by any standards. For example, United Nations statistics for 2000 show that South Africa has the highest rate of murder in the world (60 per 100 000 of population), followed by Columbia at 55 per 100 000 and Peru at 10 per 100 000. It is hard to conceive of an economy growing at the expected levels without dealing with the nature of violent crime.

The World Bank and the Greater Johannesburg Metropolitan Council conducted a series of firm surveys in 1999, the details of which we have noted earlier. A key finding of the study was that crime and theft were rated as the most important constraints on firm growth by most of the CEOs interviewed. For example, based on the sample, 83 per cent of firms experienced crime in 1998 and over 60 per cent experienced break‐ins and property theft.

There is limited empirical work on how exactly crime affects growth in South Africa. Nevertheless, from casual evidence it is clear that there are essentially three ways in which crime impacts on investment and the efficiency and skills level:

1.	First, crime contributes to systemic uncertainty in the economy owing to risk to both personal lives and private poverty.
2.	Secondly, it raises the operational cost of firms. Crime prevention can also be considered as foregone resources and is therefore a constraint on growth.
3.	Finally, crime contributes to skilled emigration.

No macrocosts estimates on crime exist – however, the said World Bank study in the Gauteng region reveals that, on average, firms spend between R700 and R2 500 (US$100–400) per employee per year on crime prevention. Table 11 gives the median rand per employee in categories of firms based on size.

Firm expenditure on crime prevention, 1998 rand values

	Security guards	Security devices	Total security	Median rand/employee
Microfirms (1–5 employees)	3 500	3 000	6 500	1 200
Small firms (6–20 employees)	6 000	5 000	11 000	600
Medium firms (21–49 employees)	16 000	8 000	24 000	450
Average	8 500	5 333	13 833	750
Source: World Bank (1999).

It is hard to make a judgement on how exactly crime has made a difference. It is equally hard to suggest how economic policy, in particular in the last ten years, could have made a difference. A more fundamental question is whether the resources expanded on crime prevention were optimum enough and whether the government in the greater scheme of things was prepared to trade off, for instance, R3 billion in investment incentives for an increase in police salaries.

4.6.3 HIV/Aids

The spread of the HIV/Aids virus in South Africa has put the economy under serious strain. South Africa has one of the largest infected populations in the world, with almost 20 per cent of adults carrying the disease. There are several ways in which Aids impacts on economic performance. Apart from the serious loss of human capital, there are high labour market costs as well as the pressure to direct more resources to medication, care and prevention. These resources could otherwise have gone towards growth‐enhancing expenditure.

Arndt & Lewis (2002) point out that Aids is more prevalent among young adults. This not only reduces overall life expectancy and the rate of population growth, but also increases the burden of the working population who would be required to care for those affected. Moreover, HIV‐positive individuals are likely to have declining labour productivity. Based on their model, these authors argue that GDP growth is likely to be affected by 1 per cent every year if we factor in the Aids pandemic.

5 CONCLUSION

This study has attempted to undertake an analysis within two broad areas. First, we have outlined the nature of the welfare challenge facing the country's first democratic government. This was represented around a low growth/high poverty axis, manifest in the figures and trends shown at the outset in the article. In addition, we implicitly view the labour market as the transmitter of this welfare challenge, and hence considerable attention has been paid to understanding the nature of relative employment trends in the post‐apartheid period. However, given that the demand for labour is essentially a derived demand, it remains essential that attention be paid to understanding the economy's growth pattern. Hence, the second key component of the article has been devoted to understanding both the determinants of and constraints on long‐term economic growth in South Africa. Issues such as trade reform, the labour legislative environment and the management of crime were raised as critical nodes for policy formulation designed to kick‐start economic growth.

We have excluded a range of other factors that impact fundamentally on the growth prospects of the economy. For example, an important aspect of governance is the way in which the behaviour and performance of the state influence growth. Public sector accountability is the most important signal of a well‐functioning economy and inspires confidence in investors. Government institutions that are linked directly to the transactions and enterprises doing business in South Africa can directly affect investment decisions. Important areas that typically constrain growth in many developing countries are, for example, legal enforcement capacity (the judiciary), as well as bureaucratic capacity (the efficiency of both national and local government).

Ultimately, however, the article has attempted to provide a framework for understanding the nature and determinants of economic growth in South Africa. To state the obvious: for South Africa to address seriously its substantial welfare challenges, a qualitatively and quantitatively different growth trajectory will be required. We hope to have identified some of the key trigger points required for placing the economy onto this path.

Additional information

Notes on contributors

Rashad Cassim

Notes

Lucas's model implies that unexpectedly high realisations of aggregate demand lead to both higher output and higher‐than‐expected prices (see Romer, 2001).