INTRODUCTION

This statistical release presents a selection of indicative findings and tables from Stats SA’s 1996 October household survey (OHS). The OHS is an annual survey, based on a probability sample of a large number of households (ranging from 16 000 to 30 000), covering a range of development indicators, as well as a detailed official measurement of the unemployment rate according to standard definitions of the International Labour Organisation (ILO).

The sample and weighting procedures for the 1996 OHS were different from those in the preceding and succeeding year because the survey coincided with the population census that was enumerated in October 1996. Details of the OHS sample are given in Notes 2, 3 and 4 on pages 10 and 11. In 1996, the survey gathered information on about 80 000 people of all population groups, in 16 000 households across the country.

The next section of the report, "Key findings", gives the different distributions of population groups in urban and non-urban environments, variations in access to infrastructure and services by urban and non-urban areas, and unemployment according to both the official and the expanded definition, according to the 1996 OHS. It also contains graphs of urban/non-urban breakdowns by province, type of dwellings in which households live, and individuals’ education in relation to employment status. Other breakdowns, and several other development-related variables, are covered in the later section of "Tables". In the "Definitions" section on page 12, the terms urban and non-urban, as used in this statistical release, are defined.

The 1996 OHS data-set, weighted to the 1996 population census, is available on CD-ROM from users’ enquiries. Details of where to obtain it are contained in the section "For more information" (page 13).

A statistical release on the 1997 OHS will be issued shortly after this one, at the same time as the 1997 data set is issued. This release will contain comparisons between the two data sets. A fuller comparison of the five OHSs from 1994 to 1998 will follow after the release of OHS ’98 data set.

Comparisons between four OHSs (1994 to 1997) in respect of employment and unemployment and the associated breakdowns have already been issued, both as a statistical release (PO317.10) and as an analytical report (Unemployment and Employment in South Africa) during the second half of 1998, in time for the Presidential Job Summit.. Both publications are available from users’ enquiries. Details of where to obtain them are contained in the section "For more information". Because the census results were not yet available to use for weighting, the data in these two publications had to be weighted according to the post-enumeration survey of the census. They differ slightly from those reported here.

Urbanisation, population group, age and gender

In 1996, the life circumstances of South Africans differed markedly by whether they lived in an urban or non-urban environment. The 1996 October household survey (OHS) shows that more than half of the country’s population (54%) lived in urban areas at that time. But this proportion varied significantly by population group (with 43% of Africans living in urban areas in 1996, compared with more than 90% of Indians and whites), age (with Africans of working age, rather than children and the elderly being found in urban areas) and gender (with 55% of males, as against 53% of females being found in urban areas at that time).

• Among the 31,3 million Africans who were living in South Africa in October 1996, only 13,6 million (43%) were living in urban, and 17,8 million (57%) were living in non-urban areas.
• Of the population of 3,7 million coloureds, 3,1 million (84%) were living in urban, and only 609 000 (16%) in non-urban areas.
• As many as 970 000 (94%) of the Indian population of 1,0 million were living in urban areas.
• Among whites, 4,2 million (92%) of the total of 4,5 million were in urban areas.

Table A shows the relationships between population group, age, gender and place of residence.

* Each percentage is a percentage of all people in that particular category. For example, in the second row of the block labelled (a) and the column labelled (iv) 36% of all Africans (males and females) aged 0 - 14 years lived in urban areas in October 1996. It follows that the remainder (64%) lived in non-urban areas.

** Number of responses were too few for this analysis.

Urban and non-urban population in each province

Figure 1 indicates the proportion of people living in urban areas in each province in 1996. It shows that Gauteng had the largest percentage of people living in urban areas (97%), followed by the Western Cape (89%). The Free State (69%) and Northern Cape (70%) had relatively high proportions of people living in urban areas, but these were largely small towns. The province with the smallest proportion living in urban areas is Northern Province (11%), followed by North West (35%) and Eastern Cape (37%).



Access to infrastructure in urban and non-urban areas by population group of household head

Among South African households, type of milieu (urban or non-urban) was directly related to access to various types of infrastructure and services. For example, in urban areas, 87% of households had running water either inside the dwelling or on site, as against 25% in non-urban areas.

Table B, from which unspecified had been excluded, shows these variations.

* Each percentage is a percentage of all people in that particular category. For example, in the second row of the block labelled (c) and in column (ii) we read that in non-urban areas 923 000 households, altogether, had running water inside the dwelling, in the back yard or on the site where they lived. This translates to 25% of all households as indicated in column (iii), but when looking at population group of head of household, the table shows that only 21% of African, as against 75% of coloured and 88% of white households, had running water either inside the dwelling or on site.

** Number of responses were too few for this analysis.

Type of dwelling in which households live in urban and non-urban areas

The type of dwelling in which South African households lived varied by whether the household was situated in an urban or non-urban milieu. The bottom section of the right-hand graph of Figure 2 shows that approximately two thirds of households (68%) were living in formal dwellings such as a house on a separate stand, a flat in a block of flats, a townhouse or a brick room or flatlet in a back yard in October 1996. This percentage excludes those households which did not specify type of dwelling. In urban areas, the bottom section of the left-hand graph shows than this proportion of formal housing was higher (79%) than the overall percentage, but it was lower in non-urban areas (50%), as indicated in the bottom section of the centre graph. Approximately one in every six households in urban areas (17%) were living in informal housing or shacks, either in informal settlements or in back yards. In non-urban areas, more than four in ten households (43%) were living in traditional dwellings.

Unemployment in urban and non-urban areas by gender and race

Amongst individuals who were economically active, population group, gender and living in an urban or non-urban milieu were related to whether or not a person was employed. For example, the official unemployment rate was 20,3% amongst the urban economically active, compared to 26,8% amongst the non-urban economically active. Unemployment varied significantly not only by urban or non-urban place of residence, but also by gender and population group. It was highest amongst African women living in non-urban areas, using either the official or the expanded definition of unemployment (see Statistical release P0317.10 and the notes (on pages 10 to 12).

Table C clearly indicates the differences in unemployment rates by population group, gender and milieu. This table and all the tables on employment and unemployment in the main section of this release exclude the mining and quarrying sector, since mining hostels in which a large portion of workers in the mining sector live, have been difficult to access in the various October household surveys. The data are not comparable across the different years, since access to hostels is more difficult in some years, compared to others. However, Table D (on page 8) has attempted to include the mining and quarrying sector to indicate the pattern of unemployment for 1996. 

Table C indicates the following:

* Each percentage is a percentage of people in that particular category. For example, in block (c) we read in column (ii) that according to the official definition, 11% of economically active coloured males living in urban areas were unemployed, while according to the expanded definition, 16% were unemployed.

** Number of responses were too few for this analysis.

The table shows that unemployment rates are generally slightly lower if the mining and quarrying sector is included.

Unemployment and education

Figure 3 indicates that there is a curvilinear relationship between unemployment rates and education, using the official definition. Unemployment is highest among those economically active people who have completed primary school (29%), but it is lowest for the economically active with post-school qualifications (4%), while it is relatively low for the economically active with no education (20%).

1. Official and expanded unemployment rates

Statistics South Africa (Stats SA) uses the following definition of unemployment as its official definition. The unemployed are those people within the economically active population, who: (a) did not work during the seven days prior to the interview, (b) want to work and are available to start work within a week of the interview, and (c) have taken active steps to look for work or to start some form of self-employment in the four weeks prior to the interview. The expanded unemployment rate does not require criterion (c).

Among those who are included in the expanded but not the official definition of unemployment will be discouraged job seekers (those who said they were unemployed but had not taken active steps to find work in the four weeks prior to the interview). Stats SA research currently being conducted shows that the main reasons cited for having stopped looking for work are: a loss of hope of finding work (33%), a lack of jobs in the area in which respondents live (25%) and a lack of money for transport to look for work (18%).

Stats SA will continue to report on the situation of the unemployed using both the official and the expanded definition, since in the present economic climate, there is a large group of discouraged work seekers whose life circumstances need to be taken into account.

2. Sampling of the successive OHS surveys

Altogether, six October household surveys have been conducted. The first OHS was undertaken in October 1993, but this survey is not comparable with the other later surveys, since it excluded the former Transkei, Bophuthatswana, Venda and Ciskei (TBVC states).

• The 1994 OHS was the first household survey to be conducted in South Africa that covered the entire country, including the former TBVC states. Interviews were conducted with respondents in 30 000 households in 1 000 enumeration areas (EAs). Thirty households were visited in each EA.
• In 1995, the OHS was also conducted among 30 000 households. However, the sample was more widely dispersed throughout the country. Three thousand, rather than 1 000 EAs were sampled, and interviews were conducted in 10 households in each EA.
• In 1996, the survey was conducted in November, rather than in October, since enumeration for the 1996 population census took place during that time. Due to time and financial constraints, 16 000 households were visited in 1 600 EAs.
• In 1997, the sample size was once again increased to 30 000 households, selected from 3 000 sampled EAs.
• In 1998, due to budget constraints, the sample size was reduced to 20 000 in 2 000 EAs

This release of the 1996 OHS forms part of a series of releases of household survey information. The release of 1997 OHS information should follow shortly.

Statistics South Africa plans to compare the data across these surveys in a variety of its future publications. It has already compared employment and unemployment situation in the country in 1994, 1995, 1996 and 1997 using the October household surveys in its Statistical release P0317.10.

3. Sample design for the 1996 OHS

The preliminary data base of EAs, as established during the demarcation phase of Census ’96, constituted the sampling frame for selecting EAs for the 1996 OHS. Stats SA took advantage of the fact that the fieldwork for the survey took place at the same time as the post-enumeration survey for Census ’96 (PES). In order to save transport, field worker and other costs, the sample of EAs drawn for the PES formed the basis of the sample for the 1996 OHS.

The sampling procedure involved stratification by province and EA type (formal and informal urban areas, commercial farms, traditional, and other non-urban areas). Independent, systematic samples of EAs were drawn for each stratum within each province. The smaller provinces were given a disproportionately larger number of EAs than the bigger provinces. Altogether, 800 EAs were drawn.

Interviewing for the PES took place in these 800 EAs, but for the 1996 OHS, the EA to the east and to the west of the sampled EA was visited. Within each of these EAs, systematic sampling was applied to select 10 households to visit. Altogether, 1 600 EAs were identified, and 16 000 households were visited.

The 1996 OHS was weighted to the population census of October 1996, as adjusted by the PES. To calculate weights, a generalised ranking with a linear distance function was used to implement a population control adjustment. The marginal population frequencies of the variables sex and age group (0 - 4, 5 - 14, 15 - 19, 20 - 29, 30 - 39, 40 - 64 and 65 + years) were used within each province and each population group.

Previously, OHS surveys were weighted to reflect estimates of population size using the 1991 population census, and not the one of 1996. The data reported here for 1996 are thus not presently directly comparable with the previously published OHS figures. Statistics South Africa is in a process of re-weighting the earlier surveys to reflect estimates of the population size based on the 1996 population census.

This data set is also not directly comparable with the 1996 OHS data contained in Statistical release P0317.10. The data of the post-enumeration survey (PES), conducted just after the October 1996 population census, were used for weighting purposes for that release.

The results reported here may differ slightly from those reported for Census ’96, since the 1996 OHS is based on a sample, while the census covers the entire population. Where these have been tested, the slight differences in data between the 1996 population census and the 1996 OHS fall within 95% confidence intervals.

6. Symbols used in the tables

When a zero (0) is shown in a table, there were fewer than 500 respondents, after weighting, in this category. When a dash (-) is shown there were no respondents in the category.

When a single asterisk (*) has been used in the table, the sample was too small to give reliable estimates. 

DEFINITIONS OF TERMS

A household consists of a single person or a group of people who live together for at least four nights a week, who eat together and who share resources.

Population group describes the racial classification of a particular group of South African citizens. The previous government used this type of classification to divide the South African population into distinct groupings on which to base apartheid policies. It is now important for Stats SA continue to use this classification wherever possible, since it clearly indicates the effects of discrimination of the past, and permits monitoring of policies to alleviate discrimination. In the past, population group was based on a legal definition, but it is now based on self-perceptions and self-classification. An African/black person is someone who classifies him/herself as such. The same applies to a coloured, Indian/Asian or white person.

A hostel is a communal living quarter for workers, provided by a public organisation such as a local authority, or a private organisation, such as a mining company. These were residential dormitories established for migrant workers during the apartheid era, and they continue to house people working in certain industries, such as the mining industry.

Institutions are communal temporary, semi-permanent or permanent living arrangements for people in special circumstances, for example prisons, police cells, school boarding facilities, homes for the aged or the disabled, hotels and hospitals.

The working age population includes all those aged between 15 and 65 years.

The economically active population consists of both those who are employed and those who are unemployed.

The employed are those who performed work for pay, profit or family gain in the seven days prior to the household survey interview, or who were absent from work during these seven days, but they did have some form of paid work during this time.

The official unemployment rate: see Note 1.

The expanded unemployment rate: see Note 1.

The people who are out of the labour market or who are not economically active are those who are not available for work. This category includes full-time scholars and students, full-time homemakers, those who are retired, and those who are unable or unwilling to work.

The formal sector includes all businesses which are registered for tax purposes, and which have a VAT number.

The informal sector consists of those businesses which are unregistered and do not have a VAT number. They are generally small in nature, and are seldom run from business premises. Instead, they are run from homes, street pavements or other informal arrangements.

Primary industries include agriculture, forestry and fishing, and mining and quarrying.

Secondary industries include manufacturing, electricity and other utilities, and construction.

Tertiary industries include trade, transport, financial and business services, and social, personal and community services.

Type of employment refers to whether or not the person is self-employed, or works as an employee, or both, or else works as a domestic worker in a household.

Location refers to whether the person lives in an urban or non-urban area.

• An urban area is one which has been legally proclaimed as being urban. These include towns, cities and metropolitan areas.
• A semi-urban area is not part of a legally proclaimed urban area, but adjoins it. Informal settlements are examples of these types of areas. In this publication semi-urban areas have been included with non-urban areas.
• All other areas are classified as non-urban, including commercial farms, small settlements, rural villages and other areas which are further away from towns and cities.

• Workers include the self-employed, employers and employees.

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