Capital Intensity in South African Manufacturing and Unemployment, 1972–1990

WorldDevelopment,Vol. 23, No. 2, pp. 179-192,1995 Copyright0 1995 Elsevier Science Ltd Printedin GreatBritain.All rightsreserved 0305-750x/95 $9.50 + 0.00

Pergamon

0305-750X(94)00122-7

Capital Intensity in South African Manufacturing and Unemployment, 1972-90 RAPHAEL KAPLlNSKY* Institute of Development Studies, Brighton, U.K. Summary. -This

paperexplores the changingstructureof investmentand employmentin South Africa’s manufacturingsectorduring 1972-90. It considersthe hypotheses thatpoor employmentperformanceand high levels of capital intensity have arisen as a consequence of the overexpansionof capital-intensivesectors and distortedfactor prices. In the main, these hypotheses are rejected. Instead it is argued that poor employmentperformancearises largely from political factorswhich have dulled the privatesector’sinvestment in labor-intensivesectors, have stifled the development of the informal sector, have held back productivity growth in manufacturing,and have reduce the inflow of foreign direct investment.Although the paperis not primarilyfocused on the emergingpolicy agendain the postapartheidera,the datacontainedin this analysis would not appearto supportthe beliefs either that wages should be reduced or that the state should refrainfrom actively affecting allocative decisions.

1. JNTRODUCTION South Africa makes the transition to postapartheid democracy facing a welter of formidable problems. Gn the economic front (and with particular reference to the industrial sector): - In common with many less developed countries (LDCs) the 1980s saw a sharp decline in per capita incomes. Measured in US& the fall from the highest point (1982) to the lowest point (1986) was 41.4%; the fall to the most recent set of comparative international data (1990) has been 21.2%.’ 1991 per capita income levels were at the same level as those in 1971. - Considering the growth of manufacturing value-added, during 1980-89 the first-tier newly industrializing countries @KS) grew at an annual rate of 4.3%, the second-tier NICs at 4.0%, the developed market economies (DMEs) at 2.5%, and South Africa at only 1.1%? - Productivity growth in manufacturing has been poor. During 1972-90 total factor productivity declined at an annual rate of 1.02%. This is among the very worst economic performances over this extended period of time (Shaaedin, 1988; Englander and Mittelstadt, 1988). - One reflection of South Africa’s very poor productivity performance is the difficulties which the economy has faced on the trade front. The trend rate of anuual GDP growth during the 1980s (approximately 1.5%) was appreciably lower than the trend rate of population growth (2.6% p.a.) and was in

large part held back by a balance-of-payments constraim3 Comparing 1972 and 1990, South Africa’s capacity to import rose from 74 to 96 versus from 47 to 229 for the first-tier NICs, 60 to 176 for the second-tier MCs and 78 to 162 for the DMEs (1980= 100): On the social front: - Inequalities in income and wealth are extreme, probably as unequal as that recorded for any other country. The relativities are especially high between racial groups, but are also apparent in regional-, gender- and age-structures. - Violence is prevalent throughout the system. It includes state-inspired violence and that resulting from covert “third forces,” as well as a currency throughout social discourse. of violence Consequently, measured in terms of violent deaths per 100,000 people, South Africa’s cities rank very highly, with Cape Town recording a rate significantly higher than the second-most violent city in the world (Chicago) and Johannesburg following not far behind. Jndeed violence is one of the major *Thispaper is drawn from a largerreportpreparedas partof the COSATU/Economic Trends Croup research project on an IndustrialStrategy for a Post-ApartheidSouth Africa. I am grateful to the members of this research team - and especially to by c&rectors (Avril Joffe, Dave Kaplan and Dave Lewis) - and to two anonymous reviewers for their comments on earlierdrafts.For a mom detailed treatmentof South Africa’s comparative industrial performance, see Kaplinsky (1993). Final revision accepted:July 6, 1994. 179

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WORLD DEVELOPMENT

factors accounting for the extreme underdevelopment of South Africa’s informal manufacturing sector (Manning and Mashigo, 1993). - Although difficult to measure, it is estimated that in mid-1992 around 46% of South Africa’s labor force were unemployed, up from 39% in 1988 (South African Reserve Bank, 1992). (The unemployed, here, are defined as those without wage employment in the formal sector.) In particular age groups (especially the young), racial groups (especially black citizens), gender groups (especially women), and regions (especially the Eastern Cape), the unemployment problem is even more acute. Many of these unemployed eke out a living in the informal sector; “crime” is an important source of income for much of the population. It is widely believed that a primary starting point for the meeting of basic needs and the maintenance of political stability in South Africa lies in the creation of more employment opportunities. Since the manufacturing sector is the largest contributor to formal sector employment (19.1% in 1991) and accounts for more than 20% of GDP, it is not unreasonable to expect that it will have an important role to play in this process of employment creation. The objective of this paper, therefore, is to explore some of the more important factors underlying the manufacturing sector’s role in employment creation over the past two decades, since without this historical insight into the sources of unemployment, it will be difficult to design a suitable policy response in the postapartheid era. In particular, the levels of aggregate capital intensity in the South African economy appear to be comparatively high, and this frequently leads to the policy conclusion that real wages should be reduced in order to clear the labor market. The discussion which follows is designed to throw some insight into this analytical conclusion and the policy implications which follow from it.

+

'l‘rcnd 1950-87

*

I'rcnd 1958-87 0 l’rcnd 1975-87

18 1950

I 1955

1960

I 1965

I

I

I

I

1970

1975

1980

1985

Year Source: Calculawd from Iltwghton (1967). Nattrass (1988) and 11x7 database (1992) Figure 1. Manufacturing as a percentage of GDP.

The following section provides a brief discussion of the overall size and comparative performance of South Africa’s manufacturing sector, and briefly discusses alternative definitions of this sector. This is followed by summary data on employment in manufacturing (section 3) and by an estimation of overall levels of capital intensity in manufacturing (section 4). Section 5 considers a number of potential explanations of the high observed levels of capital intensity in the formal sector and provides a brief discussion of the nature and causes of the underdevelopment of the informal manufacturing sector. The conclusion addresses the policy implications of these findings.

2. SOUTH AFRICA’S MANUFACTURING SECTOR: COMPARATIVE PERFORMANCE Figure 1 charts the changing share of manufacturing in South Africa’s GDP during 1950-90. Not surprisingly this share has tended to stabilize, settling at between 23 and 25% after the mid-1970s; this share has remained remarkably stable given the price instability of South Africa’s commodity exports and the significance of their contribution to GDP. The stabilization of the share of manufacturing in GDP reflects a reasonably close correspondence between this ratio in South Africa and that which would be expected, given South Africa’s per capita income and population, as is evident from Syrquin-Chenery normality comparisons (Figure 2.)5 In itself, the share of manufacturing in GDP does not reveal the rate of growth of manufacturing valueadded (MVA); a stable ratio can be associated with either a simultaneous rapid rate of growth, or a stagnation in the growth of MVA and GDP. During the decade of the 196Os, South Africa’s MVA growth exceeded those of most other LDCs; but in the 1970s its performance was close to the average (Moll, 1990). As can be seen from Table 1, however, during the 1980s South Africa’s MVA grew significantly less rapidly than the first and second-tier NICs as well as the developed market economies. This falling growth rate was associated, as we have seen, with a declining rate of total factory productivity growth. In addition to this poor utilization of productive inputs, South Table 1. Growth of manufacturing value-added, 1980-89 (96 p.a.)

NICs Second-tier NICs DMFS South Africa

Weighted average*

Country average?

3.22 5.05 3.37

4.29 4.01 2.49 1.07

*Average of group total MVA. tAverage of country group rates. Source: Calculated from UNIDO (1991).

CAPITAL INTENSITY IN SOUTH AFRICA

181

ii[m;y\/ 21.5 1972

I 1914

1 1976

I 1982

I 1980

1978

I I984

I I986

1988

Year Figure 2. Syrquin-Chenery

“normality”

Africa’s manufacturing output is also of relatively low quality by international standards and fails to meet the shortened innovation lead-times which are. increasingly prevalent in global markets (Joffe et al., 1994). The structure and performance of the South African manufacturing sector has been much closer to the pattern of Latin America, than to that of the East Asian NICs - for example, as Moll shows, total factor productivity (TFP) growth rates during 1973-84 in manufacturing were negative in South Africa, Argentina, Brazil, Chile and Mexico (between -0);6% and -2% p.a.), but they were positive in Korea and Taiwan (Moll, 1990). Manufacturing output has also been almost predominantly destined for the domestic market; and as will be shown below, the pattern of capital intensity in manufacturing has been much closer to that of Latin America than to the structure of the Asian NICs. Thus the underlying comparative performance of the South African manufacturing sector has been poor. Rustomjee (1993) argues, however, that the use of the manufacturing sector in the analysis of the South African economy is misleading, an argument taken up in the ANC’s Macroeconomic Research Group’s Report (MERG, 1993). Since the manufacturing sector is so closely linked to the mining sector, Rustomjee believes that a more useful analytical construct is that of the “Minerals-Energy Complex” (MEC) which consists of coal, gold, diamond and other mineral extraction; electricity; non metallic minerals production; iron and steel basic industries; non ferrous metals basic industries; and fertilizers, pesticides, synthetic resins, plastics, other chemicals, basic chemicals and petroleum (Rustomjee, 1993; pp. 36-37). The temainder of the conventionally described manufacturing sector experienced a largely stagnant share during 1960-90 (15-17% of GDP). By contrast, not only has the share of the MEC exceeded that of non-MEC man-

: manufacturing sector.

ufacturing, but it only reached a plateau in the early 1980s (25-27% of GDP). (It is evident, however, given changes in commodity prices, the share of the MEC fluctuated sharply.) It will be seen from later analysis that these key mineral-based heavy industries play an important role in the explanation of high levels of capital intensity in the economy at large.

3. THE STRUCTURE OF EMPLOYMENT IN SOUTH AFRICAN MANUFACTURING6 During the 197Os, employment in manufacturing grew at more than 3.25% per annum, exceeding the growth in population rate (but less than the rate required to mop-up all new entrants to the labor force). But during the 1980s this expansion of employment came to a virtual halt, with an annual growth rate during 1980-90 of 0.22% p.a. During 1980-89 a mere 28,360 additional jobs were created in manufacturing.’ The subsectoral distribution of total employment in manufacturing over the 19-year period has been remarkably stable. The fabricated metal products sector has consistently accounted for over one-quarter of total manufacturing employment (reflecting the laborintensive nature of the assembly activities which characterize this sector) and the basic metals and chemicals sector account for only 7% and 11% of total employment respectively; this diverges sharply with their share of total capital stock (22.1 and 37.7% respectively).8 During the 1980s none of the individual sectors experienced employment growth at the rate of population growth, while three sectors (including textiles which is often thought of as a sector in which low-wage economies have a comparative advantage) saw a decline in absolute levels of employment.

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182

Table 2. Growth of employment in a comparative context, 1980-89 NICS Second-tierNICs DMEs South Africa

Weightedaverage

Country average

0.57 1.80 -0.98

0.63 2.33 -1.16 0.22

Source: Calculatedfrom UNIDO (1991). The stabilization of employment in manufacturing during the 1980s is not atypical, and characterized economic performance in many other economies. Table 2 provides a comparative picture from which it can be seen that employment in manufacturing actually fell in the DMEs during the 1980s (at 1.2% per annum), and grew slowly in the NlCs at 0.6% annually. Only the second-tier NICs showed a sustained growth in employment over the decade. The conclusions that South Africa’s employment performance during the 1980s was relatively strong runs against much conventional wisdom, but it is striking that whereas South Africa ranked 35 out of 44 countries in the growth of output during the 1980s its ranking with respect to employment growth was 14. Even Japan only experienced annual employment growth of 0.55% (one place above South Africa); New Zealand and the United Kingdom (both countries experimenting with deregulation and privatization during the 1980s) filled the last two places with employment loss at 3.13 and 3.10% annually. South Africa’s employment structure is thus somewhat paradoxical since its relatively good performance during the 1980s (with respect to employmentgrowth) is counterposed by relatively high absolute levels of unemployment. The key to this conundrum probably lies in the relatively small share of the total labor force employed in the manufacturing sector?

4. CAPITAL INTENSITY IN SOUTH AFRICAN MANUFAClURING There is a widespread belief that capital output ratios in the South African economy in general and in the manufacturing sector in particular are high. This is one of the factors which is said to underlie the poor employment performance of the South African economy. Table 3 provides comparative data on economywide levels of capital intensity. These data suggest that the degree of capital intensity in the South African economy is indeed very large by comparison with four other NICs, most of which have similar levels of per capita income to South Africa. Although South African capital intensity appears to have fallen in recent years, it remained relatively high throughout these two decades. Table 4 provides comparative data

on incremental capital output ratios in the manufacturing sector. These, too, suggest high comparative levels of capital intensity. As noted above, it is striking that in general the South African performance is much more similar to the Latin American than to the Asian NICs. The fact that these figures “wobble” over different time periods, suggests that care must be taken in their interpretation. A number of caveats are due. First, even if the data in Tables 3 and 4 are accepted at face value, the rate of increase in recorded capital intensity was lower for South Africa than for any of these countries. Second, for much of the period for which these data are calculated, the Rand was at a high value and this tends to overstate the degree of capital intensity in the South African economy, at least until the mid 1980s. For example, the depreciation in the Rand (and the low rate of investment in South Africa during the 1980s) led to a decline in the US$ value of the capitallabor ratio for the manufacturing sector from $70,300 in 1980 to $25,300 in 1990; by contrast the ratio in constant 1990 Rands rose during the same period from R54,700 to R65,500.1° Third, the data in Table 3 relate to the economy-wide capital-labor ratio, including South Africa’s capital-intensive mining and agricultural sectors. It is notable that the relative disparities are lower for the manufacturing sector alone (Table 4). Two linked explanations for this capital intensity are often put forward. Fist, it is argued that a major factor is the primacy given to capital-intensive sectors during the last three decades. A recent influential World Bank report on the manufacturing sector concludes, for example, that [t]he evidence is clear that South African manufacturing has become increasingly capital-intensive over time, and that this increase in capital-intensity is in substantial part the result of the expansion of relatively capital-intensive subsectors of manufacturing (Levy, 1992, p. 44). In some cases this high capital intensity is said to be. a natural consequence of South Africa’s well-developed mineral sector, a view implicit in Rustomjee’s conception of the MEC (Rustomjee, 1993)” It is more often argued, however, that the high levels of capital intensity are caused by “distorted factor prices.” This has the effect of both inducing activity in relatively capital-intensive sectors, and in forcing the choice of techniques within all sectors in a suboptimally capital-intensive direction. Fallon, whose analysis underlies the World Bank’s An Economic Perspective on South Africa (World Bank, 1993), believes that the major distortion arises from wages being too high rather than from capital costs being “artificially low,” Although the results presented in this paper lend support to the idea that black employment growth has been ham-

CAPITAL INTENSITY IN SOUTH AFRICA

183

Table 3. Economy-wide capital-labor ratios (real lJS$).jive-year average 196165 Brazil Mexico Korea Malaysia South Africa

1971-75

1981-85

Per capita GNP (US$l989)

3.6 6.5 1.0 3.3

6.5 12.4 4.3 6.1

10.6 18.4 11.8 12.1

2,540 2,010 4,400 2,160

13.8

18.1

27.0

2,470

Source: Levy (1992) and World Bank Tables (diskette). Table 4. Incremental capital-output ratios in the manufacturing sector, 1971-L?9* South Africa

Mexico

Brazil

Malaysia

Korea

22.3 50.3 23.0 71.0

13.7 13.8 194.7 38.0

12.6 14.8 47.2 24.2

14.6 11.7 26.3 10.2t

7.7 8.1 13.9 8.4

1971-75 1975-79 1979-83 1983-89

*Calculated using gross fixed capital formation and incremental value-ad&d. Thus includes replacement investment so ICORs are likely to be overstated for countries with capital stock of older vintage. tExcludes 1989. Source: Levy (1992). pered by rising real wages, they do not accord with the view that slow employment growth has been heavily caused by the maintenance of an artificially low user cost of capital (pp. i-ii)...These results...suggest that changes in factor prices have had an important effect on black employment. The empirical results indicate that this can overwhelmingly be traced to upward movements in black wages (Fallon 1992,p. 27).

This view is shared by both the South African Congress of Business Report (which perhaps not unsurprisingly for a document emanating from the business community, calls for a lowering of borh real wages and the cost of capital - SACOB, 1991) and the outgoing Nationalist Government’s Normative Economic Model (see below). The discussion which follows is designed to open-

up these issues and specifically to address the concems that high levels of unemployment arise from both the overexpansion of capital-intensive sectors and the choice of inappropriate techniques within sectars, and that these are due to the prevailing factor price ratio. Both these issues, as discussed above, relate to

the policy debate on factor-price distortions. Research on South Africa’s manufacturing sector is still in an early phase, so that the level of analysis is aggregative and is reliant on the use of secondary databases. 5. EXPLANATIONS FOR OBSERVED HIGH LEVELS OF CAPITAL INTENSITY As the MERG Report observes, the conclusion that high levels of capital intensity and unemployment are

Table 5. Sectoral capital-labor ratios and share of manufacturing capital stock Capital labor ratio (R’OOO)(1990)

Share of total capital stock

As % of other

Chemicals (Other basic chemicals) Basic metal products Nonmetallic minerals Food, drink, tobacco Pulp and paper Fabricated metal products Textiles Wood, furniture Other manufactures Leather, shoes Clothing

1972

1990

basic chemicals subsector (1990)

1972

1990

79

219 631 187 58 58 51 28 20 13 10 7 2

34.7 100 29.7 9.2 9.2 8.1 4.5 3.2 2.0 1.6 1.2 0.4

19.7 11.3 29.7 6.2 12.7 6.2 16.0 4.8 2.2 0.7 0.6 1.2

37.7 29.1 22.1 5.3 14.0 4.7 11.5 2.4 1.3 0.4 0.3 0.3

187 142 32 32 38 21 19 12 14 7 5

Source: Calculated from Industrial Development Corporation (DC) database,

184

WORLD DEVELOPMENT

caused by high wages is prima facie of dubious validity on grounds of casual empiricism - the highest rates of unemployment are to be found in groups with the lowest wages (women and the young) and in rural areas where wages are lowest.‘* Moreover, the Fallon model which underlies the World Bank’s research results assumes unchanging technology and the calculations work from the presupposition that “the ratio of capital to black workers [would have]. . .remained at its 1960 value” (Fallon, 1992, p. 27); this is clearly an illegitimate basis for calculating that increases in black wages account for 42% of the observed shortfall in black employment. We will return to the policy implications of this particular analytical approach later in this paper. But, before exploring some alternative explanations for the relatively high observed levels of capital intensity in South African manufacturing, it is instructive to consider the sectoral breakdown of capital intensity and investment in the manufacturing sector. From Table 5 it is evident that there are wide variations in intersectoral capital-labor ratios. At one extreme lies the chemicals sector where the capital cost per job is R219,OOO (and R632,OOO for “other basic chemicals”); at the other extreme is the clothing sector, where the capital cost per workplace (at R2,400) is only 0.4% of that in the other basic chemicals sector. (Unless otherwise stated, all values in subsequent discussion are in constant 1990 Rands.) The “other basic chemicals” sector plays an important role in South Africa’s recent political and economic history and needs some explanation. This category of analysis is somewhat unusual by international conventions since it incorporates an amalgam of disparate subsectors (ISICs 3511, 3530 and 3540). including that which manufactures petroleum from

coal and from natural gas. A brief recapping of South Africa’s political history is important here. The growing opposition to apartheid during the 1960s and 1970s led to the widespread adoption of sanctions against South Africa, especially after the mid 1970s. A key target in this sanctions agenda was the denial of oil to the apartheid regime, and for this reason large investments were made into synthesizing petroleum from coal and natural gas (see later discussion for details). The amalgamation of these ISIC categories was deliberately undertaken to hide the extent of investments in sanctions-busting plants to produce petroleum from coal and off-shore gas. A close look at the data in Table 5 also shows a close ranking between these two sets of sectoral data. The other basic chemicals subsector has by far the highest level of capital intensity, and alone accounted for 29% of total manufacturing capital stock in 1990. Similarly, the basic metal products sector, which is also relatively capital intensive, accounted for 22% of total capital stock. By contrast, the clothing and leather and footwear sectors were relatively laborintensive, but accounted for only 0.3% each of total capital stock. Changes over 1972-90 tended to reinforce these patterns - the other basic chemicals subsector increasing its capital intensity by more than three times and its share of total capital stock rose from 11 to 29%. By contrast, capital intensity in the clothing sector fell, as did its share (and that of leather and footwear) in total capital stock. (a) Crowding out by capital-intensive

At first glance, this data might be thought to confirm the viewpoint (as in Levy, 1992, cited above) that these capital-intensive sectors have crowded out

38 .

36 -

+ * o 9

NlCs 2nd tier NICs DMECs South Africa

22 20 18 ’ 1912

.

I

1

I

I914

1976

1978

sectors?

I

I

1980 I982 Year

I

I

I

L

I984

1986

I988

I990

Figure 3. Investment OSa percentage of GDP. Source: Calculated from World Bank Tables (diskette).

CAPITAL INTBNSM’YIN SOUTH AFRICA

investment in other sectors. Reference to the investment/GDP ratio (Figure 3) suggests, however, a somewhat different picture, at least as far as the 1980s are concerned. This shows that whereas South Africa’s investment ratio was relatively high by comparison with the DMEs and the first and second-tier NICs during the 197Os, the rate of investment fell very sharply during the 1980s. In 1991 Gross Domestic Investment had fallen to only 16.2% of GDP. Through much of the 1980s the rate of investment in manufacturing was particularly low, and after 1984 it was not even adequate to cover depreciation charges, with the size of the manufacturing capital stock falling by 5.7% by 1990. Perhaps more significant than the essentially static nature of total manufacturing capital stock during the 1980s was the sectoral performance of investment. As can be seen from Table 6, in the 18 years between 1972 and 1990, the capital stock in the most laborintensive garment sector fell by 19%. Whereas the four most labor-intensive sectors together only invested R25lm in the 18 years between 1972 and 1990, this was equivalent to the average investment of the other basic chemicals sector in less than three months. From this we can conclude that instead of high levels of capital intensity being driven by “overinvestment” in the capital-intensive sectors, a more likely explanation is that these high levels of capital intensity are explained by the absence of investment in labor-intensive sectors. Thus the crowding-out hypothesis is difficult to sustain as an explanation of overall capital intensity in the manufacturing sector.13 (We return to the significance of underinvestment in the conclusions.)

185

(b) Has there been “overinvestment” in capitalintensive sectors?‘4 A second explanation for high levels of overall capital intensity may be that South Africa has invested disproportionately in the capital-intensive sectors. Since the basic metals and the chemicals sector are the most capital-intensive sectors in South African manufacturing and together account for 59.8% of total capital stock, it is instructive to explore their relative size in manufacturing value-added (MVA) by comparison with our three groups of economies. Figure 4 suggests that the role played by the basic metals goods sector is indeed large in South Africa. This reflects South Africa’s generous resource endowment with respect to mineral deposits. By contrast, Figure 5 shows that although the South African chemicals sector is relatively more prominent than that of the second-tier NICs and the DMEs (but not the first-tier NICs), this is not as prominent as the case of basic metals. A more detailed look at the subsectors in Figures 4 and 5, however, provides an important insight. In the case of the metal products subsectors, one of the key sectors of MVA growth in the global industrial sector has been the electrical machinery sector (ISIC 383). As Figure 6 indicates, whereas this subsector grew in all three groups of comparator economies during the 198Os, in South Africa it declined at an annual rate of more than 6%. Measuring relative capital intensity by the value-added per employee (the best proxy available from comparative data) this subsector’s ratio in the DMEs (in US$ for 1985) was considerably lower than that for the iron and steel and the nonferrous metals subsectors where South African industry performed well ($26,800 versus $30,700). Similarly, the plastics subsector in chemicals contributed a lower

Table 6. Net investmentby sector. 1972-90 Size of capital stock (R1990,OOO)

Investment 1972-90

% investment

(R1990’000)

1972-90

1972

1984

1990

Chemicals (Other basic chemicals) Basic metal products Nonmetallic minerals Food, drink, tobacco Pulp and paper Fabricated metal Textiles Wood, furniture Other manufactures Leather, footwear Clothing

8,181 4,687 12,331 2,582 5,251 2,559 6,648 1,992 905 305 242 484

28,090 29,187 23,181 5,990 11,500 6,688 11,793 2,415 1,261 381 320 393

35,248 29,013 20,992 5,062 13,310 4,515 10,895 2,248 1,193 385 314 295

27,707 24,326 8,661 2,480 8,059 1,955 4,247 257 288 80 72 -189

35.5 31.2 11.1 3.2 10.3 2.5 5.4 0.3 0.4 0.1 0.1 -0.2

Total

41,478

99,169

95,095

53,617

100

Source: Calculated

from IDC database.

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WORLD DEVELOPMENT

0

NIC

DMECs

2nd tier

South

NlCs m

m

Iron. steel m

Africa

Non-ferrous

Non-elec

metals

0

math

Source: Calculated

m

Metal prods

Transport equip

from UNIDO

(I 99 I )

Figure 4. Share of iron and steel industry in MVL (1989).

NIC m

Industrial

chemicals m

2nd tier NlCs a

DMECs

South Africa

Other chems prods

Petrlm. coal prods

Source: Calculated

[7

m

Refineries

Plastics

from UNIDO

(1992)

Figure 5. Share of chemicals industry in MVA (1989).

share of MVA in South Africa than in comparator countries, but declined at more than 1% annually (Figure 7). The plastics subsector is also relatively labor-intensive - value-added per employee in this subsector at $25,400 (DME average, 1985) was considerably lower than that in the industrial chemicals ($49,500) and other chemical products ($41,500) subsectors. The conclusion to be drawn from this breakdown of subsectoral activity is not that there has been overinvestment in the capital-intensive activities, but rather that there has been underinvestment in the labor-intensive activities in these sectors. This accords with our earlier observation of the decline in the share of investment in GDP.

(c) The choice of technology within sectors Another possible explanation for high levels of capital intensity (and thus low levels of employment in industry) might be that the choice of technology across the economy has been “distorted.” This is not so much with respect to intersectoral choice (which has been considered above), but in relation to microlevel decision-making processes and intrasectoral choice of technique. Once again, this raises the question of policy, since if it can be shown that these micro decisions have been systematically capital intensive in nature, then this too might reflect distortions in the factor-price ratio. This is not an easy point to evidence,

CAPITAL INTENSITY IN SOUTH AFRICA

-2

187

I

NIC

2nd tier NICs

DMECs

South Africa

Source: Calculated from UNIDO (1991) Figure 6. Plastics-Annual

m

growth (1989), share MVA (1989).

Annual growth rate

NIC

2nd tier NICs

DMECs

South Africa

Source: Calculated from UNIDO (1991) Figure 7. Electrical machinery -share and much of policy thinking on this subject is based upon the presumption of a market-clearing wage rate.15 The only detailed microeconomic study of the determinants of technical choice in South African manufacturing found little evidence that the choice of technology was affected by relative factor prices (Nattrass and Brown, 1977). Black also concludes that insofar as there is evidence that the choice of tech-

MVA (I 9891, annual growth (198940).

nique is affected by labor costs (and, perhaps more important, labor availability), this was considerably more evident for skilled (white) labor than for unskilled (black) labor (Black, 1991, p. 163). Moreover empirical studies from other countries suggest that the specification of output mix is a much more significant determinant of capital intensity than is the ratio of factor prices. Nevertheless, this evidence is inadequate to make a judgement on whether factor

188

WORLDDEVELOPMENT

price distortions have played an important role in the choice of technique at the micro level. There is, however, one exception to this judgement. The major support for the argument that capital intensity and low output and employment growth arise from inappropriate technical choice comes from the nature of the very heavy investments made in synfuels inresponseto the oil sanctions of the 1970s and 1980s. One informed estimate of recent investments in SASOL (deriving petroleum from coal) is that they were R6bn (in 1984 prices); investments in MOSSGAS (designed to produce petroleum from high-cost offshore gas) were estimated to be Rl2bn during 1987-91 (Crompton, 1993). In 1990 prices, this is equivalent to Rl3bn and R14.2bn respectively, amounting to half of total manufacturing investment growth during 1972-90. (Estimates of the value of these investments vary widely - a particularly high valuation of R3lbn in 1991 prices has recently been made by SASOL).16 All available evidence suggests that calculated on an ex-ante basis, these investments in synfuels are economically unviable, requiring an oil-price equivalent in excess of $35/barrel (the current price is less than $2O/barrel). It is significant, though, that this inappropriate choice of technique was not driven by the capital/labor price ratio. (We return to the significance of this point below.)

(d) The growth of the informal manufacturing sector The discussion so far has concentrated on the formal manufacturing sector, in large part because of the availability of national and comparative data. As observed, unemployment in this formal sector of the economy has been high, with ahnost one in two of the labor force registered as being without employment. Clearly many of these labor force participants, however, must be “in work,” if only sporadically, otherwise their ability to survive in a system bereft of effective welfare services would be virtually impossible. These activities can be grouped together in a residual economic category referred to as the “informal sector.” By comparison with other LDCs, not much is known of the informal sector in South Africa. In part this is because for many years it was illegal for black South Africans to head their own enterprises or to engage in manufacturing activities,” but it is also because the sector is not well developed. The first studies of this sector’s activities are beginning to emerge and paint a bleak picture.**It possesses a number of distinctive characteristics which have severely limited the ability of the informal manufacturing sector to create viable employment and much of South Africa’s informal sector thus fits into Moser’s survival category (Moser, 1978).19 First, considered in comparative context, the South

African informal manufacturing sector is relatively small. The share of manufacturing within the informal sector - admittedly difficult to measure - appears to be relatively low. Thus whereas the ratio was estimated at 23.5% in Mexico in 1987, 26.7% in Colombia in 1984,32% in the Nigerian city of Maradi and 36% in Lesotho, the share of manufacturing in South Africa’s informal sector is probably somewhat less than 20% (all estimates from Manning and Mashigo, 1993). Related to this are the low incomes which this sector provides in South Africa. Whereas in other LDCs heads of informal sector manufacturing enterprises tended to earn more than the average industrial wage rate, black microenterprises in South Africa (as distinct from “colored” or “Indian” enterprises) struggled to survive and provided pitiful returns to their owners and employees. Even in the more dynamic microenterprises more than 50% of incomes are below the official household subsistence level incomes (Simon and Birch, 1992). The reasons for this poor performance can be helpfully distinguished between those which are “internal” and those which are “external.” In the former category stands the absence of skills. For many decades blacks were prohibited by law from acquiring artisanal, financial or managerial skills and these jobs were reserved for whites. Thus even though this iniquitous legal framework has been rescinded over the past decade, the depth of skills among the black labor force is low. It is worth bearing in mind here that comparative evidence makes it clear that most successful heads of microenterprises in other LDCs have moved from skilled jobs in the formal sector. It is significant in this context that average levels of education in the more progressive “formalized” microenterprise is relatively high (Simon and Birch, 1992). These problems of skills shortage are exacerbated by a particularly hostile external environment. Infrastructure in black townships is weak, and few enterprises have access to telephones and/or electricity. Credit provision and extension services have historically been virtually nonexistent (although there is now increasing emphasis on assistance to the informal sector, much of which appears to be largely ineffective -Manning and Mashigo, 1993). But more urgent, the lack of “peace” and the high levels of desperation and unemployment in black communities removes many of the conditions (such as security of property rights) which are necessary for the informal manufacturing sector to flourish, Mashigo (forthcoming) relates many instances of informal sector enterprises being robbed by “the balaclavas” (gangsters) whenever they appear to be running profitably. This is confirmed by the experience of the more progressive (and now “formalized”) informal sector “graduates” who operate in industrial parks -“. . .away from the restrictions imposed by the poverty of the township environment, the firms have benefited from wide market access and

CAPITAL INTENSITY

new opportunities for diversification and expansion” (Simon and Birch, 1992, p. 1041). Taken together, the confluence of these internal and external factors places a considerable constraint on the ability of the informal manufacturing sector to provide either gainful employment or meaningful incomes for the unemployed in the South African economy. Once again, as with the formal manufacturing sector, the weakness of the informal manufacturing sector’s ability to create jobs can be closely tied to prevailing political conditions rather than to the factor price ratio. Both the internal and external constraints of South Africa’s informal manufacturing sector can be traced back to the political realm - the absence of security of property, and the severe inequalities in access to infrastructure, training and in income distribution. It is thus not surprising that South Africa’s informal manufacturing sector is so poorly developed by comparative standards.

6. CONCLUSIONS The primary purpose of this paper has been to explore the changing structure and employment performance of the South African manufacturing sector, particularly over the past two decades. It is evident from this analysis that poor manufacturing performance in the economy at large has been associated with a static labor force in the formal sector. A breakdown of sectoral growth within manufacturing shows that whereas the capital-intensive sectors maintained high levels of investment and output growth, the laborintensive sectors experienced a falling capital stock and low rates of growth. It is also evident that the labor-intensive informal manufacturing sector is poorly developed. Although this lack of employment growth has not been uncommon in the already-industrialized countries, it might have been thought that the manufacturing sector might act as a spur to employment growth in a lower per capita-income economy such as South Africa where there remains considerable potential for employment growth. The most widely cited explanation for this poor employment performance in manufacturing is that it arises from “distorted factor prices,” particularly in relation to the allegedly high price of labor. This is said to both force the “overexpansion” of capitalintensive sectors, and the systematic choice of capitalintensive techniques across all sectors. Although this factor-price ratio clearly has political underpinnings, it can be seen as a predominantly economic explanation which lends itself to a clear policy prescription reductions in real wages and (possibly) an increase in the real cost of capital. The preceding discussion, however, presents an alternative perspective - an explanation predominantly rooted in the political domain. This is not to say

IN SOUTH AFRICA

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that factor prices have no role to play in explaining the employment performance of South African manufacturing, but they appear to be a relatively unimportant factor. Instead, the high levels of observed capital intensity at the aggregate level can be seen to have arisen less from the overexpansion of the capitalintensive sectors than from underinvestment in laborintensive sectors; this underinvestment has been a consequence of the prevailing political climate in the dying years of apartheid in which private sector capitalists have been reluctant to invest in these laborintensive sectors. Five other predominantly political factors have also played a prominent role in explaining poor employment growth in manufacturing. First, there has been a systematic tendency for the inappropriate choice of technology within the basic chemicals sector, which alone accounts for almost one-third of total capital stock in manufacturing. This pattern of technical choice has been driven by the search for petroleum self-sufficiency as a consequence of the sanctions against oil supplies to the apartheid regime in South Africa. A second related point is that sanctions against apartheid had the additional impact of creating barriers to exports, a source of considerable employment growth in the Asian NICs. In the context of declining domestic incomes, this further dulled the incentive to invest. Third, labor militancy in the struggle against apartheid, and conflicting relations on the shopfloor were important factors holding back productivity growth in manufacturing, and hence in the growth of MVA and GDP. Fourth, the vibrancy of the informal manufacturing sector has been stunted by a combination of politically determined factors among which the insecurity of operations, an hostile legal environment (until the mid-1980s), the lack of electricity and telecommunications, the paucity of skills and the lack of consumption power among black urban residents have been most prominent. Finally, the importance of the political environment within which investment occurs is contirmed by the recent behavior of inward foreign direct investment. In the most recent period (1989-93) it is evident that the primary explanator of these flows has been the political climate rather than a cluster of economic and monetary factors. Garner’s analysis of these inward flows “...provides firm evidence that the state of political negotiations with the ANC, the level of political violence, and removal of sanctions have been the key determinants of the timing of new investment” (Garner, 1993, p. vi). There is a close link between the analytical explanation for the poor employment performance of the manufacturing sector and the policy prescriptions which are suggested. Thus, were it to be proven that investment and employment in the labor-intensive sectors were driven out by the expansion of the capital-intensive sectors or that there was a systematic choice of inappropriate capital-intensive techniques in

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all sectors, then an appropriate policy prescription might have been to change the factor-price ratio, notably in the South African context by reducing real wages. This is indeed the view to be found in the outgoing Nationalist Government’s Normative Economic Model which argued that South Africa’s high aggregate level of capital intensity is directly caused by high wages and thus places considerable emphasis on wage restraint (CEAS, 1993). A similar policy conclusion can be drawn from the analyses of both the World Bank (World Bank, 1993) and SACOB (SACOB, 1991). On the other hand, if poor employment performance in the manufacturing sector can be located in a confluence of political factors, then alternative policy prescriptions are relevant. These seek to locate an employment-focused manufacturing strategy in the context of fundamental changes in the political environment within which industrial investment is occurring. These perspectives more closely reflect the policy agendas of the trade union led Industrial Strategy Project (Joffe et al., 1994) and the ANC’s Reconstruction and Development Plan. The Industrial Strategy Project analysis locates poor manufacturing employment in the context of the observed reluctance of the private sector to invest (especially in laborintensive sectors) and in conllictive industrial relations which have hindered productivity growth, and thus overall economic growth. The MERG Report suggests that in addition to these manufacturing sector-specific explanations, poor employment performance arises from a failure of the government to maintain aggregate demand, to invest in inappropriate projects and to invest in training. This has led the ANC to a political program which aims to satisfy unmet

basic needs with a mass housing and electrification program and to invest heavily in human resource development. The evidence presented above has a bearing on a second policy prescription currently debated extensively in South Africa. This affects the role of the state in industry, where it is frequently asserted that the “rational” policy is to privatize existing state investments and to force the state to refrain from further equity holdings in industry. It is, however, noteworthy that in a context of low investor confidence, the only sectors where manufacturing investment held up during the 1980s were those sectors where the state played a central role in resource allocation. It may be that the high levels of political uncertainty remain for some time in the postapattheid era so that the focus of attention might be more on the ability of the state (in part through its own strategic investment) to crowd-in investments as to the dangers which it might play in

crowding-out manufacturing investment. Finally, in focusing on the role played by South Africa’s manufacturing sector with regard to employment over the past two decades -and by implication, on the role which it might play in the future - it is important to bear in mind the limits to this endeavor. It is now increasingly obvious that few of the industrialized economies are able to maintain employment in manufacturing - even where service sectors relating to the manufacturing sector are taken into account (Ormerod, 1993 and 1994). Thus although South Africa’s manufacturing sector clearly has plentiful scope for expansion, especially in export-oriented activities and in informal sector microenterprises, the employment problem will ultimately have to be met in other sectors and in other domains of state action.M

NOTES 1. There are considerable problems in estimating the size of per capita incomes in South Africa. On the one hand, the use of US$ as a numeraire almost certainly overstates the extent of decline in real per capita incomes, due to the fluctuation in the Rand/$ exchange rate during the decade. The inability to measure the informal sector also contributes to an underestimation of GDP. On the other hand, the official figures of population almost certainly are too low. The 1991 census results estimated this at around 3Om, a figure which was widely considered to be an underestimate of around five to six million. The election of 1994 suggested, however, that the real population was around 43m, although this figure is itself subject to disbelief given the widespread fraud associated with the tirst democratic election in South Africa. Notwithstanding these difficulties in estimating population sire, it is widely accepted that real purchasing power of average incomes fell between 15 and 20% during 1980-90. 2. These country groupings are based upon those identified in Forstner and Ballance (1990) and am utilized through-

out this paper as a basis for comparing South Africa’s industrial performance. The listing of countries used in this comparison are provided in the Appendix. 3. The constraint of the balance of payments on economic growth was exacerbated by trade and finance sanctions, and by internal political instability. Among other effects, these factors ma& it necessary to generate adequate trade surpluses to cover the standstill on the inflow of foreign capital. 4. The capacity to import calculations are a function of terms of trade effects and export earnings. See the Notes to the World Bank (diskette) which are the source of these calculations. 5. The variance between the two curves shown in Figure 2 between 1976 and 1982 reflects changes in the US$/Rand exchange rate during the 1980s; international comparisons have been undertaken in US$.

CAPITAL INTENSITY IN SOUTH AFRICA

6. To facilitate international comparisons, unless otherwise stated, the data on South African manufacturing employment are drawn from UNIDO statistics. Although it does not reference the South African data in detail, these employment figures almost certainly include the TVBC states of the apartheid era; the UNIDO estimate of 1989 manufacturing employment (1.459m) is not dissimilar to that cited by Fallon which includes employment in TVBC (1.516m) (Fallon, 1992). 7. These single year figures do not distort the trends. The increase in the three-year average of employment (1,423,243 for 1979-81 and 1447.983 for 1988-90) was only marginally higher, at 24,740. 8.

All figures for 1990.

9. It is very difficult to make comparisons on the share of the labor force in manufacturing. The UNIDO database refers to the formal sector and excludes microenterprise and informal sector employment. Its estimates of manufacturing employment are substantially lower than those contained in the IL0 database. Unfortunately the relative employment performance of different countries varies between these two databases. This makes reliable intercountry comparison meaningless. (I am grateful to Adrian Wood for pointing these differences out to me.) 10. The Rand/dollar rate fell from 1.2854 in 1980 to 0.3866 in 1990. 11. The high level of capital intensity in mining is compounded in the South African case by the depth at which gold is to be found. This necessitates an unusually capital-intensive form of deep-shaft mining. 12. The MERG document lists other areas in which the World Bank’s model is weak. It excludes monetary and international sectors and ignores the effect of excess (and variable) capacity on aggregate production function calculations (MERG, 1993). 13. It is simultaneously evident that there is also little sign in the aggregative data of crowding-in by these capital intensive investments. 14. The comparative analysis in this section is hampered by

191

the absence of a uniform data base. Thus the discussion of South Africa’s internal industrial structure is taken from a 76 sector breakdown provided by the Industrial Development Corporation (IDC) which, as observed, aggregates a number of subsectors in the “other basic chemicals branch.” The data on comparative industrial structure are taken from various UN’lDCJpublications and is available on a 23-subsector basis (UNIDO, 1990) or a 28-subsector basis (UNIDO, 1991). 15. In many LDCs the scale of unemployment is severe and wages are close to subsistence levels. The idea of a feasible market-clearing wage which allows for all the population to be fed and housed in these circumstances is not credible. As Fallon observes in relation to South Africa, “However, black wages cannot fall sufficiently to provide full employment as it is assumed that employers are unwilling to reduce wages below some minimum level (the efficiency wage), while trade unions may have an additional wage rising effect” (Fallon, 1992, p. 23). 16. SASOL Facts (1992). p. 13. I am indebted to Rod Crompton for drawing these various estimates to my attention. 17. For example, the 1962 Regulation for the Administration and Control of Townships in Bantu Areas prohibited anything but one-person enterprises, excluded blacks from any activity except the provision of daily domestic activities for other blacks, and explicitly forbade the pooling of resources within companies or any activities within the financial or wholesale sectors. It was only in 1976 that the first easing of such regulations began and only after the mid-1980s that any steps to promote black enterprises in general (let alone manufacturing in particular) was in evidence (see Mashigo, forthcoming and Simon and Birch, 1992, for a description of the changing legal environment). 18. See Simon andBirch (1992) andManningandMashigo (1993) for references to this literature. 19. In recent years there have been signs of the emergence of a more dynamic informal sector. See Simon and Birch (1992). 20. This is one of the key conclusions of the large sixteen sector Industrial Strategy Project undertaken between 1992 and 1994. See Joffe et al. (forthcoming).

REFERENCES Black, A., “Manufacturing development and the economic crisis: a reversion to primary production?,” in S. Gelb (Ed), South Afiicu’s Economic Crisis (Cape Town: David Philip and London: Zed Books, 1991). CBA& The Restructuring of the South African Economy: A Normative Model Approach (Pretoria: Central Economic Advisory Service, 1993). Crompton, R., The South African Commodity Plastics Filiere: History and Future Strotegy Options, Research Report, COSATU/Economic Trends Group Industrial Strategy Project (Cape Town: University of Cape Town Development Policy Research Unit, 1993).

Englander, S., and A. Mittelstadt, “Total factor productivity: Macroeconomics and structural aspects of the slowdown,” OECD Economic Studies No. 10 (Paris: OECD, 1988). Fallon, P., “An analysis of employment and wage behaviour in South African manufacturing,” World Bunk InformuZ Discussion Papers on Aspects of the Economy of South Africa, Paper No. 3 (Washington, DC: World Bank

Southern Africa Department, 1992). Fallon, P., A. Aksoy, Y. Tsikata, P. Belli and L. Pereira da Silva, “South Africa: Economic performance and some policy implications”, World Bank Informal Discussion Papers on Aspects of the Economy of South Africa, Paper

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No. 2 (Washington: World Bank Southern Africa Department, 1993). Fine, B., and Z. Rustomjee., “The political economy of postwar industrialization in South Africa,” Mime0 (London: Dept of Economics, Birkbeck College, University of London, 1994). Forstner, H., and R. Ballance, Compering in a Global Economy (London: Unwin Hymm, 1990). Gamer, J., “Determinants of recent direct investment flows to South Africa,” Centre for the Study of the South African Economy and International Finance, Research Paper No. 8 (London: London School of Economics, 1993). Houghton, H., The South Afn’can Economy, 2nd Edition (Cape Town: Oxford University Press, 1%7). Joffe, A., D. Kaplan, R. Kaplinsky and D. Lewis, A Srraregy for rhe Expansion of South Africa’s Ind&strial Sector

(Cape. Town: University of Cape. Town Press, forth coming). Kahn, B., A. Senhadji and M. Walton, “South African macroeconomic issues for the transition,” World Bank Informal Discussion Papers on Aspects of rhe Economy of South Africa, Paper No. 2 (Washington, DC: World Bank

Southern Africa Department, 1992). Kaplmsky, R., South African Industrial Performance and Structure in a Compurarive Context, Research Report, COSATU/Economic Trends Group Industrial Strategy Project (Cape Town: University of Cape Town Development Policy Research Unit, 1993). Levy, B., “How can South African manufacturing efficiently create employment? An analysis of the impact of trade and industrial policy,” World Bank informal Discussion Papers on Aspects of the Economy of South Africa, Paper No. 1 (Washington, DC: World Bank Southern Africa

Department, 1992). Manning, C. and A.

Mashigo,

Manyfacturing

in

Microenterprises

in South Africa, Research Report, COSATU/Economic Trends Group Industrial Strategy Project (Cape Town: University of Cape Town Development Policy Research Unit, 1993). Mashigo, A., “Small scale manufacturing in South African townships: The case of woodworkers and metalworkers in Cape Flats,” D. Phil Dissertation (Brighton: University of Sussex, forthcoming). MERG, Making Democracy Work: A Framework for Macroeconomic Policy in South Africa, A Report to members of the Democratic Movement of South Africa, ANC Macroeconomic Research Group (Johannesburg: ANC, 1993).

Moll, T., “Output and productivity trends in South Africa: Apartheid and economic growth, D. Phil Dissertation, (Cambridge: St. John’s College: University of Cambridge, 1990). Moser, C., “Informal sector or petty commodity production: Dualism or dependence in urban development”, World Developmenr, Vol. 6, No. 9/10 (1978). pp. 1041-1065. Nattrass, J., The South African Economy: Its Growrh and Change, 2nd Edition (Cape Town: Oxford University Press, 1988). Nattrass, J., and Brown R. P. C., “Capital intensity in South African manufacturing,” Black/White Income Gap Project, Interim Research report No. 4 (Durban: Dept of Economics, University of Natal, 1977). Ormerod, P., The Death of Economics (London: Faber and Faber, 1994). Ormerod, P., “Notes on unemployment”, Paper Presented at Unemployment Conference

at Wisron House, Sussex

(London: September 1993). Rustomjee, Z. Z., “The political economy of South African industrialization: The Role of the mineral-energy complex,” Ph.D dissertation (London: University of London, 1943). Shaaedin, E., “Sources of industrial growth in selected African countries,” African Development Bank Economic Research Paper No. 8 (Abidjan: African Development Bank, 1988). Simon, D. and S. L. Birch, “Formalizing the informal sector in a changing South Africa: Small scale manufacturing on the Witwatersrand,” World Development, Vol. 20, No. 7 (1992). pp. 1029-1045. South African Chamber of Business (SACOB), A Concepr for the Development of a New Industrial Policy for South Africa (Johannesburg: South African Chamber of

Business, 1991). South African Reserve Bank, Annual Economic Report (Pretoria: Government Printer, 1992). Stoneman, C., “Jobs or markets: some lessons from Zimbabwe, Mimeo, Centre for Southern African Studies (York: University of York, 1994). UNIDO, Handbook of Indusrrial Statisrics 1990 (Vienna: UMDO, 1990). UNIDO, Industry and Development: Global Reporr 199112 (Vienna, UNIDO, 1991). World Bank, An Economic Perspective on South Africa, Southern Africa Dept. (Washington, DC: World Bank, 1993).

APPE The country classifications in the comparative analysis are drawn from Forstner and Ballance (1990). This classification is not without its problems, since some of the inclusions are surprising (Peru in the second-tier NIC group) as are some of the omissions (India and China). Nevertheless the benefits obtained from comparative analysis outweigh these caveats. The country groupings are.as follows: NICs Argentina, Brazil, Hong Kong, Korea, Mexico, Singapore and Taiwan.

Second-tier NICs Cyprus, Colombia, Indonesia, Jordan, Malaysia, Morocco,

Peru, Philippines, Sri Lanka, Thailand, Tunisia and Uruguay. DMEs

Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Japan, Luxembourg, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom and the United Stares. Forsmer and Ballance include South Africa in the DME group, but in the calculation of group data we have excluded