CHAPTER NINE

SOCIO-ECONOMIC ASPECTS OF INFORMAL

SETTLEMENTS

By Nick Wilkins and Julian Hofmeyer >I E 0 z 0

It has been estimated that more than two million people in KwaZulu-Natal 0 live in informal settlements. Settlers comprise half of the total Durban Functional Region population, and 70% of Africans. The combination of high rates of unemployment in these settlements with an often almost complete absence of infrastructure is a daunting socio-economic challenge.

A possible solution to this situation is the implementation of an urban public works programme. Public works programmes (PWPs) are generally projects funded by the public sector, designed to reduce unemployment and economic hardship by providing jobs and incomes to those unable to obtain employment elsewhere in the economy. At the same time, PWPs can be used to create durable assets, such as physical infrastructure and skills, which benefit society in the long term.

A comprehensive account of PWPs, their implications and implementation, is contained in the original report for the project. This chapter merely contains extracts of the part of the report outlining the socio-economic characteristics of informal settlements in KwaZulu-Natal.

Limitations in the data relating to informal settlements should be borne in mind. Much of what is available is from studies by Cross et al and

Data Research Africa. Most research into informal settlements has focused on the Durban Functional Region (DFR), but since the vast majority of settlement inhabitants in the region are found in the DFR, those settlements constitute a reasonably representative sample.

Informal settlements in the DFR are not homogeneous, and have been differentiated according to their historical development and systems of land tenure. Settlements can also be differentiated according to their age, whether they are located in or around formal townships, and the relative density of spacing of shacks.

Because of these differences it is difficult to group settlements together for socio-economic analysis and comparison. There is also at least as much variation across socio-economic categories of households within informal settrements as there is between them. However, it is possible to discern certain broad general characteristics of informal settlements in the region.

DEMOGRAPHIC CHARACTERISTICS

KwaZulu-Natal has a population of around 8,5 million people, or 21% of South Africa's population. In projecting population trends for settlements in the region, it is helpful to use the Urban Foundation's Population Model, which classifies settlements into four generic types: metropolitan, cities and towns, dense or closer settlements, and rural areas. May refined this model further using 10 generic sub-regions. Population estimates are hampered by the inclusion of the northern portion of the Transkei in Region E.

As can be seen from Table 1, in 1992 roughly 26% of Region E's population lived in informal settlements, and 45,4% in rural areas. The population in metropolitan settlements is growing at over 4% a year, significantly faster than the formally settled population, and is projected to increase by over three million people from 1992 to 2020. The population of rural settlements is growing more slowly but from a high base, with the most rapid growth of 2,8% occurring in dense rural settlements.

Consequently, it has been projected that by 2020 informal settlements will constitute 28% of the total population of Region E, while rural settlements will still be relatively sizeable at 38% of the total. The proportion of Region E's urbanised population is thus projected to rise from just over 50% in 1992 to about 62% in 2020.

Table 1 Annual population growth rates and population size by political sub-region and type of settlement, Region E 1992

1 Natal 1,5% 2,0% 1,3% n.a. n.a. n.a, n.a. -0,02%

KwaZulu/ Transkei 3,0% 3,2% 3,7% 4,l% n.a. n , a 2.8% 1.8% n,a, 1 Pop., 1992 ('000) 2 290 4 210 9 270 1 350 1 550 470 400

1 % of total 24,7 3,8 167 5,l 4,3 45,4 100.0 1 Note: a. Settlements in rural areas in transition between rural and urban status.

b. n.a. = not available. Source: Adapted from May (1 993:5-9)

Informal settlements in metropolitan and urban areas, those in transition between rural and urban status, and dense rural settlements are thus destined to continue to expand rapidly in population and area. High growth rates in informal, urbanised settlements are also due to permanent migration from rural to urban areas. The demographic basis for continuing population pressure on rural areas is demonstrated in Table 2, which outlines the age profile of Region E by political and generic sub-region.

It is clear that areas in KwaZulu have more youthful populations, and hence potentially higher fertility rates, than in Natal, and that rural areas have more youthful populations than metropolitan and urban areas. Interestingly, peri-urban areas have a substantially less youthful population than all former homeland areas and the rural areas of Natal. Homeland and rural areas will thus continue to feed migrants into settlements in urban areas.

As May points out, the dynamics of migration in KwaZulu-Natal have become increasingly complex. By the mid-1980s it was clear that rural poverty was undermining the system of oscillating migration, and that people were migrating permanently into urban areas. Migrants appear to follow several routes into urban areas, and once there may move several times from area to area.

In terms of the gender profile of the province, May notes that according to the 199 1 Census 46,7% were male and 53,3% female. Although the

Table 2 Age profile of Black population in Region E by political and generic sub-region, 1 992

/ Sub-region Percentage in each age group 0-1 4 15-64 h5+

1 Metropolitan 40,7 56,9 2,4 I 1 Urban 43,5 54,l 2,3 I I Rural dense 54,O 42,3 3,7 I / Rural dispersed 52,9 43.0 4.1 1

Source: May (1 9935)

gender of' the population varies significantly by area - for example some areas in KwaZulu have a low proportion of males due to out-migration for work while in industrial areas the trend is reversed - informal settlements have an overall gender profile fairly close to the provincial average. This is not surprising since a major factor motivating migration is keeping family members together.

It is also important to differentiate households in KwaZulu-Natal by means of socio-economic characteristics. Access to formal wage earning opportunities plays a determinant role in the ways in which communities develop. A socio-economic classification of black households was suggested by May based on the following seven categories:

= Marginalised: no access to wages or remittances from formal sector opportunities, and no access to welfare transfers (pensions)

Welfare dependent: no wage or remittance received, and there is access to welfare transfers only

= Remittance dependent: no wage but there is access to a remitted income, and welfare transfers may be available

@ Wage committed (average earners): access to wage earnings only, this wage being in the lowest eight deciles of wage earnings

CHAPTER 9

= Wage committed (high earners): access to wage earnings only, this wage being in the top two deciles of wage earnings

Mixed income source (wages secondary): access to a range of income sources, of which wages make up less than a third of total household incomes

= Mixed income source (wages primary): access to a range of income sources, of which wages make up more than a third of total household income.

Table 3 comprises a sample survey of KwaZulu households in each settlement type according to socio-economic category. Peri-urban (largely informal) settlements, mainly those on the periphery of the DFR, include the highest proportion of 'marginalised' and 'welfare dependent' households. Dispersed rural and dense rural settlements also have high proportions of these two categories, and by far the highest proportions of 'remittance dependent' households. It is clear that informal and rural settlements have the highest proportions of poverty stricken households in KwaZulu. -

Table 3 Households in KwaZulu by socio-economic category and settlement type, 1992

0

2,7 2,O 4,O 3,7 Marginalised

Wage-committed (ave, earnings) 29,2 20,9 21,2 18,5 1218 1 1 Wage-committed (high earnings) 25.8 28,6 14,5 6,2 415 I

Mixed income (wages secondary) 8,7 7,O 1 0,l 13,9 1319 1

Mixed income (wages primary) 23,6 24,2 18,9 17,l 1617 I 1 Total 1 00,O 1 00,O 100,O 1 00,O

loo10 I No, households surveyed 520 1303 676 2 706 756

Source: May (1 993: 18)

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Table 4 Socio-demographic characteristics of peri-urban informal households in KwaZulu by socio-economic category, 1992

Marginalised 5 9 5 7 413 1:1,4

I I / Wage-committed (high earnings) 5.8 5,6 42,5 1:1,9 19.4 1 I

I ,

I! I / I

Mixed income (wages secondary) 6,2 5,5 52,9 1:1,6 39,7

Mixed income (wages primary) 7,3 6,8 56,2 1:1,9 45,3

Wage-committed (ave, earnings) 6,6 6,4 46,4 1:1,7 30,l 1

Note: a. Dependency ratio = ratio of those younger than 16 or older than 60 to those aged 16-60. Source: May (1 993: 19)

Peri-urban, largely informal settlements have the third highest proportion of 'remittance dependent' households. May concludes that this indicates longer term migration has been superseded by daily or weekly commuting in many areas, and that there has been a blumng of the once distinctive characteristics of peri-urban and rural areas.

Metropolitan settlements not surprisingly have the highest percentage of average and high 'wage committed' and mixed income households. Peri-urban and urban settlements also have high 'wage-committed' households. 'Mixed income' households with wages as secondary sources were most common in rural areas, in which agricultural and remitted incomes are important, and in informal settlements, in which informal sector earnings and remittances are important income sources.

May differentiates households by income source in the peri-urban informal settlements of KwaZulu (Table 4). The average age of heads of marginalised households is much younger than those of 'welfare dependent' and 'remittance dependent' households, and the percentage of female household heads is much lower for the 'marginalised' group than for the 'welfare dependent' and 'remittance dependent' groups.

It is not surprising that 'welfare dependent' and 'remittance dependent' households should have a higher proportion of female household heads

or that household heads should on average be significantly older than in other socio-economic categories. 'Wage committed' households in peri-urban informal areas have somewhat younger household heads than the other categories, and relatively low dependency ratios and proportion of female household heads. This would fit in with the assumption that formal sector employment is largely dominated by male household heads, and that women are on average paid less than men.

'Mixed income' households typically have a higher proportion of female heads than the 'wage committed' groups, and the average age of household heads is higher. Women household heads are often widows, and reliant on informal sector activity as a survival strategy to supplement low wages in the formal sector, especially in the absence of a male breadwinner.

There is no clear relationship between average household size and socio-economic category. The average size of black households in the DFR in the late 1980s was close to seven but, Cross et al note, has been falling due to a drop in the birth rate rather than an increase in the supply of housing. Low household size is probably due to the simple

* structure of many informal households: a substantial proportion are

z parents without children or just a nuclear family. Cross et al found that

0 z

47% of households in the DFR had four or fewer members, just over 0 19% included members from only one generation, and nearly 79% had 0 not more than two generations present. w

0 - Educational levels of household heads in KwaZulu show a great deal of variation by settlement type. Rural settlements not surprisingly have the

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highest proportions of household heads who are functionally illiterate - 0 cn

having less than seven years of schooling - with women being significantly less well educated than men. Heads of households in formal metropolitan townships have the highest education levels on average, again with men being significantly better off than women.

Interestingly, the education profile of male household heads in informal settlements is similar to that of urban and peri-urban formal settlements, while that of women household heads is second only to metropolitan formal settlements. While roughly similar proportions of male household heads have completed Standard 10 in informal settlements and urban and peri-urban settlements, a far higher proportion of female household heads have reached this level in informal settlements than in all settlement types other than formal metropolitan townships. The educational profile of informal settlements is on the whole slightly better than the average for all settlement types.

!

i CHAPTER 9 k- CHAPTER 9

The proportions of female heads by settlement type are remarkably close: generally around one third of all household heads, and their average age is 40 years. The average age of female household heads is greater or equal to that of male heads, presumably due to longer female life expectancy.

ECONOMIC ACTMTY

There is far more variation in employment patterns across socio-economic categories than across settlement type. Table 5 provides a breakdown of the employment status of people of economically active age in DFR informal settlements grouped by geographical area. While the proportion of adults in formal employment is fairly constant across the settlement groups surveyed, the proportions respectively not economically active, unemployed and employed in the informal sector vary considerably.

Informal settlements in the central DFR, for example, have a remarkably low proportion of economically inactive people, with a concomitantly high percentage of people involved in the informal sector. One of the constituent settlements in this group is Block AK, composed mainly of women informal sector traders with few dependants, located close to Durban's central business district.

Table 5 Employment status of adultsa by settlement, DFR, 1991192 (%)

Employment status lnanda ~ariannhill Central South Tdh~l DFR '4 b 4 &%9 : . ' 8 & ,. 4*/

sample

I Not in the labour force 32,l 45,2 22,6 37,9 36.8 1 / Unemployed, seeking work 29,l 164 20,7 154 20.1 1 I Employed in formal sector 32,l 35,8 29,O 31,5 32.8 ( I Employed in informal sector 51 1,8 16,O 7,7 6.1 1

Self-employed or employed part-time in formal sector 1,6 0,8 6,6 6,l 3,l

Self employed or employed part-time in informal sector 5,l 1,4 1,l

1 Total 1 00,O 1 00,O 100,O 100.0 100.01

Notes: a. Adults are defined as people over 15 years of age. Source: Cross ef a1 (1 994)

CHAPTER 9

The proportions of people unemployed and seeking work varies from a low 15,4% in southern DFR settlements to a high of 29,1% in Inanda settlements. Using this range of unemployment rates and assuming a total adult population of informal settlements in KwaZulu-Natal of roughly 1,5 million, the total number of unemployed in informal settlements in the province can be projected at 225 000 to 440 000 people. The total unemployment figure for DFR settlements is roughly 300 000.

Breakdowns specifically of the unemployed in informal settlements are not available. One relevant analysis is that of Nattrass and Mpanza, who surveyed the settlement of Mgaga, north west of Umlazi, in 1985.

The unemployed in Mgaga were mostly women - 75% - while 82% were between the ages of 15 and 44, and 69% had standard six or a lower level of education. Of the unemployed, 67% had worked before, but 43% of those had been farm labourers and were thus unlikely to find work in the industrial sector. It is probable that the average education of the unemployed will have improved somewhat by now, and that the work experience of those previously employed will tend to be dominated less by farm labour.

z The proportion of people engaged in informal sector activity is generally 0 small, particularly in metropolitan townships where less than 10% of 0 women and less than 5% of men participate - although in a survey of w black micro-enterprises last year Latt found that 17% of households in Pietermaritzburg townships were involved in informal sector activity.

0 i5

In informal settlements proportions are higher, especially among female 0 0)

household heads, 19% of whom are involved in informal sector activity. The most popular informal sector occupations in informal settlements among women household heads are retail activities such as 'spaza' shops, shebeens and street hawking, with soft goods production (probably clothing) another choice. Retail trading was also popular among the few men involved in the informal sector.

A similar picture emerges in Table 6, which details the distribution of formal and informal sector jobs in DFR informal settlements. Retail trading dominates informal sector jobs, although construction involves nearly 10%. Formal sector job types are not surprisingly dominated by labourers, factory and domestic workers, with artisans constituting only 7%.

In most income categories, informal settlements fall between rural areas and metropolitan and urban formal areas. Informal settlement incomes

CHAPTER 9

Table 6 Distribution of formal and informal sector job types in DFR informal settlements, 1 991 192

Formal sector job type % of total Informal sector job Type % of total

Labourer Factory worker Domestic worker Artisan Driver Shop assistant Clerical worker Hotel worker Security worker Professional Mine worker Civil servant Gardener Farm worker Other

Total

Hawking - small commodities Selling bought goods Construction Informal sector employees Spaza (informal) Shebeen (small) Craft and home industries Spaza salesperson Local casual labour Taxi driver Selling home produce Small repair work Shebeen (large, furnished) Informal medicine Crechelchild minding Taxi-owner Local political work Other Total

1 Source: Cross et a1 (1 994) I

are close to the overall average: 17,6% of informal households receive income in the same range as the lowest 20% of all households.

Table 7 presents average monthly income to household heads broken down by source, gender and years of schooling. The returns of education are immediately apparent, with average wage income increasing with years of schooling in nearly every case. Also clearly evident are the serious disparities between average wage incomes of male and female household heads of the same education levels in every settlement type, especially at lower levels of education.

Table 8 provides an interesting partial distribution of earnings from the most popular informal sector activities undertaken in DFR informal settlements. Construction is evidently not as well paying an activity as retailing trades such as running a spaza or shebeen and hawking.

O Transport Patterns

Christensen and Gumede point out that roads in DFR settlements are in an extremely poor condition. In 53 of 56 settlements surveyed internal

I Table 7 Average monthly wage, transfer and remittance income to (and average age of) household heads in KwaZulu by sex and years of schooling, 1992

All < 7 51 185 66 84 335 . 50,9 Male 7-9 45 442 79 4 1 562 22,8 head 10-1 1 42 620 82 23 7 24 12,3

12 39 1 244 86 8 1 338 13,9 Total 47 444 74 56 574 1 00,O

All < 7 59 55 7 165 227 ' 60,8 Female 7-9 50 1 89 13 90 29 1 20,O head 10-1 1 44 446 13 59 51 7 8,l

12 4 1 1 177 39 30 1 246 11,l Total 54 238 12 127 376 1 00,O

All < 7 54 139 45 113 297 54,O (All 7-9 47 370 60 55 485 22,O heads 10-1 1 43 580 66 3 1 677 1 1,0

12 40 1 226 73 14 1313 13,O Total 49 380 54 78 51 3 100,O

I Source: Calculated from DRA (1 992) I

routes were predominantly very narrow, potholed and sometimes impassable roads and footpaths. Only 11 settlements had tarred roads.

Three modes of transport are used by inhabitants of the settlements surveyed by Christensen and Gumede: buses, taxis and trains. Buses and taxis are the most popular mode, serving 51 and 50 of the settlements respectively. Inhabitants generally favour taxis to buses, since they are generally more plentiful, less expensive and far quicker. In most cases buses and taxis do not enter settlements, largely due to the poor and limited roads, forcing the inhabitants to walk on average 10 to 20 minutes to public transport stops. Trains are used by inhabitants of 1 1 settlements, mainly in the south and west of the DFR. Inhabitants who catch trains often use taxis to take them to the railway stations.

O Perceived Needs and Infrastructural Shortcomings

The needs perceived by informally settled communities to be most urgent are impressionistic, but it is clear that water supply, housing, sanitation,

CHAPTER 9 CHAPTER 9

Table 8 lnformal sector job earnings in DFR informal settlements, 1991 192: partial distribution

Informal sector job type % operators with earnings % operators with earnings < R400 per month > R1000 per mon~h

Hawking - small commodities Selling bought goods Construction Informal sector employees Spaza (informal) Shebeen (small) Craft and home industries Spaza salesperson Local casual labour

I Source: Cross ef a1 (1 994) I

roads, electricity, schools, clinics, and urban amenities such as shops and post offices are keenly felt community needs. Another major priority is, of course, employment. It is clear that most of the infrastructural needs concern the construction of buildings and other physical assets.

Table 9 Greatest perceived needs of residents in lnanda informal settlements, 1991

Need " Ranking No, of responses Percentage of total t *

I

Water and water supply 1 Housing 2 Toilets and sewerage 3 Better roads 4 Schools and education 5 Electricity/lights 6 Total

1 Source: Cross et a1 (1 992b:70) I

1 CONCLUSION

It would be difficult to define an 'average' or 'typical' informal settlement in socio-economic terms. In aggregate, however, the informally settled population of KwaZulu-Natal bears characteristics placing it midway between the populations of rural settlements on the one hand and metropolitan and urban formal settlements on the other. Informal

settlements have an older age profile than that of rural settlements, but a younger one than metropolitan and urban settlements, with roughly 60% of people being of economically active age in 1992.

Informal settlements have the highest proportions of the lower income 'marginalised' and 'welfare dependent' households in KwaZulu, but also feature strongly in the higher income 'wage-committed', average earnings and 'mixed income' categories.

The gender composition of household heads in KwaZulu informal settlements varies greatly by socio-economic category, with the smallest proportion of female heads (14,8%), occurring in the 'marginal' group and the highest (60,6%) in the 'welfare dependent' group. In addition, the lowest and highest average ages of household heads - 41,5 years and 65,5 years - occur respectively in these two groups.

This correlation between the extreme values of age and gender of household heads is explainable in terms of the lower earning power and high unemployment rate of young male heads of households, and the longer

I

! life expectancy of women which leads to a large number of remittance dependent widows at the head of families. Interestingly, the percentage of female household heads does not vary significantly by settlement type.

I

In terms of the education levels of household heads in KwaZulu, informal settlements once again fall between rural and metropolitan and urban settlements. The educational profile of male heads of households is

I similar to that of urban formal settlements. Women household heads are significantly worse off than males in all other settlement types, but are closer to the educational profile of male heads in informal settlements.

The proportion of people of economically active age in informal settlements in KwaZulu varies greatly by socio-economic category of household, and again there is far more variation across household category than across settlement type. More than a third of people of economically active age in informal settlements in the DFR are not in the labour force, while another third are employed in the formal sector.

The unemployment rate varies considerably in DFR informal settlements, from 15,4% in the southern settlements to 29,1% in Inanda. According to sample surveys, only 3,4% of male household heads in informal

I settlements in KwaZulu are involved in informal sector activity, compared with 19% of women household heads.

CHAPTER R 1 CHAPTER 9

I 1

I

Regarding average household incomes in KwaZulu settlements, it is again evident that there is more variation across socio-economic household 1 categories than across settlement types. In KwaZulu informal settlements 17,6% of households have an average income lower than R250 per month, and 22,9% from R251 to R500 per month. Only 40,4% of households have an average monthly income over R825, with 18,8% falling into the top quintile of R1 441 per month and above. Both the mean and median incomes of informally settled households in KwaZulu are closer to those of the rural settlements than the metropolitan and urban settlements, at R946 and R648 per month respectively. I

I

It is clear that wage income increases strongly with education level. While male heads of informal settlement households with less than seven years of schooling earn an average monthly wage income of R451, this increase to ~ 6 4 8 for those with seven to nine years of schooling, R620 for those with 10 to 11 years education, and R1 181 for those with matric or higher. There is a serious disparity between the household income received by male and female household heads of the same education level: the corresponding average monthly wage incomes to women heads are respectively R86, R160, R560 and R773.

Remittance income and transfers are not very significant sources of income for informal settlement households in KwaZulu. It is interesting that higher total remittances accrue to male household heads than to female heads, while female household heads receive more transfer income than male heads, presumably because there are more female than male pensioners as family heads.

In the informal sector, retail activities such as running a spaza are more profitable t h a n construction. Of the operators of construction micro-enterprises, 60% earned less than R400 a month in 1991/92: by contrast, 22,7% of spaza shop operators earned over R1 000 a month. Informal sector employees and local casual labourers appear to earn the lowest informal sector incomes, with over 90% of them earning less than R400 per month in 1991/92.

It appears that the members of roughly 17% of households in DFR informal settlements earned less than R2,OO per capita per day during 199 1 /92, while the members of just over 40% of households earned less than R5,00 per capita per day.

Modes of transport differ considerably between groups of DFR settlements. Whereas buses and walking are the most popular modes in Inanda

CHAPTER 9

communities, taxis are the most widely used in Mariannhill. All three of these modes together with train travel are heavily used in the southern DFR informal settlements.

But while transport patterns vary between settlements, nearly all informal settlements are in need of properly constructed and well maintained internal roads. With respect to perceived needs and infrastructural shortcomings in general, water supply, housing, sanitation, roads, electricity, schools, clinics and urban amenities such as shops and post offices are sorely needed in informal settlements. All of these needs could be delivered by means of a PWP.

E F E R E N C E S

Christensen F and Gumede A (1993) 'Informal Settlements within the Durban Functional Region', The Inkatha Institute, Durban.

Cobbledick J and Sharratt M (1993) 'A Profile of Poverty in the Durban Region', report commissioned by the Project for Statistics on Living Standards and Development of

).

SALDRU, Economic Research Unit, University of Natal, Durban. E

Cross C, Bekker S and Clark C (1992a) 'Fresh Starts: Migration Streams in the Southern 0

Informal Settlements of the DFR', Natal Town and Regional Planning Supplementary z

Report Vol 40, Natal Town and Regional Planning Commission, Pietermaritzburg. 0 C)

Cross C, Bekker S, Clark C and Richards R (1992b) 'Moving On: Migration Streams Into and Out of Inanda', Natal Town and Regional Planning Supplementary Report Vol 38, Natal Town and Regional Planning Commission, Pietermaritzburg.

Cross C, Bekker S , Clark C and Richards R (1992~) 'New People: The Younger Informal 0 Settlements in Central Durban', report commissioned by the Department of Local Government and National Housing, Rural-Urban Studies Unit (RUSU), Centre for

0 cn Social and Development Studies (CSDS), University of Natal, Durban.

Cross C, Bekker S , Clark C and Wilson C (1992d) 'Searching for Stability: Residential Migration and Community Control in Mariannhill', report commissioned by the Department of Planning, Provincial Affairs and National Housing of the House of Assembly, Rural Urban Working Paper No 23, RUSU, CSDS, University of Natal, Durban.

Cross C, Clark C, Bromberger N, Bekker S and Christiansen P (1994) 'The Informal Population of the Durban Functional Region: An Overview', mirneo, RUSU, CSDS, University of Natal, Durban.

La t t EA (1993) 'Repor t o n Self-employment Survey Conducted i n Grea te r Edendale/Sweetwaters Region, 1992- 1993', Careers Resource Centre, Pietermaritzburg.

Maasdorp GG (1983a) 'Some Thoughts and Evidence on the Informal Sector', Development Studies Southern Afica, Vol 5 No 2, p 197 to 204.

Maasdorp GG and Pillay N (1983) 'Informal Settlements: Socio-economic Profiles', Low-income Housing in the Durban Metropolitan Region: Project Report No 2 , Economic Research Unit/School of Architecture, University of Natal, Durban.

CHAPTER 9

May J (1993) 'Demography a n d Social Concerns i n Region E', mimeo, Data Research Africa, Durban.

May J a n d Rankin S (199 1) 'The Differentiation of the Urbanisation Process Under Apartheid', World Development, Vol 19 No 10, p 1351 to 1365.

May J a n d Stavrou S (1988) 'The Informal Sector: Socio-economic Dynamics a n d Growth i n the Greater Durban Metropolitan Region', Rural Urban Working Paper No 18, RUSU, CSDS, University of Natal, Durban.

Mmller V (1990) 'Research Into Community Needs a n d Priorities: An Overview', Rural Urban Working Paper No 21, RUSU, CSDS, University of Natal, Durban.

Nattrass N a n d Mpanza Z (1988) 'Mgaga: A Socio-economic Profile', Working Paper No 17, RUSU, CSDS, University of Natal, Durban.

Stavrou SE, Mbona DZ, Yokwe XS a n d Mbona CF (1987) 'K5 - A Preliminary Study of a n Informal Rural Settlement', Working Paper No 12, RUSU, CSDS, University of Natal, Durban.