This statistical release presents a selection of indicative findings and tables from Stats SA’s 1997 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, including the detailed official measurement of the unemployment rate according to standard definitions of the International Labour Organisation (ILO).

The sample size, sampling and weighting procedures for the 1997 OHS are different from those used in 1996. Details of the various OHS sample sizes, sampling and weighting procedures are given in Notes 2, 3 and 4 on page 11. In 1997, the survey gathered information on about 150 000 people of all population groups, living in 30 000 households across the country.

 The next section of the report, "Key comparisons", indicates key similarities and differences in the recently released 1996 OHS findings as against 1997. The release examines living in urban and non-urban environments, access to infrastructure and facilities in these two different types of milieu, and in unemployment according to both the official and the expanded definition. It also contains graphs of urban/non-urban breakdowns for 1997 by province, type of dwelling in which households lived, and individuals’ education in relation to their employment status. Other breakdowns, and several other development-related variables, are covered in the later section of "Tables".

Both the 1996 and 1997 OHS data sets, weighted to the 1996 population census (adjusted upwards to take population growth into account in 1997) are available on CD-ROM from User enquiries. The 1996 OHS statistical release can also be obtained from them (See the section on "For more information" (page 14)).

A fuller comparison of the five most recent OHSs, from 1994 to 1998, will follow after the release of OHS ’98 data set. Findings regarding 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). These publications are available from users’ enquiries. 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.

 Certain changes are difficult to detect over a one-year period, since they become measurable only in the longer term. For example patterns regarding changes in the level of education of the population aged 20 years or more are difficult to isolate in one year. On the other hand, some changes, for example access to jobs and to formal housing, are easier to detect during a shorter time period.

 This summary focuses on those possible short-term changes between 1996 and 1997, which may be easier to detect, as shown in the two successive OHSs. But these findings need to be viewed with extreme caution, since they are based on two cross-sectional samples. Although Stats SA has calculated standard errors and confidence intervals for certain variables to take sampling errors into account, and to make the comparisons possible, a longer time series is required to examine these changes more thoroughly and with less tentativeness.

 Urbanisation, population group, age and gender

• The majority of Africans continued to live in non-urban areas in both 1996 and 1997. Among the 32,1 million Africans who were estimated to be living in South Africa in October 1997, 13,9 million (43,3%) were estimated to be living in urban, and 18,2 million (56,7%) in non-urban areas. In October 1996 a similar estimate was made: 31,3 million Africans were found to be living in South Africa, of whom 13,6 million (43,3%) were estimated to be living in urban areas.
• Of the estimated population of 3,8 million coloureds in 1997, 3,2 million (85,0%) were living in urban, and only 563 000 (15,0%) in non-urban areas. In 1996, however, it was estimated that 83,5%of coloureds were living in urban, and 16,5% in non-urban areas. This indicates a possible, but not significant, trend of movement among coloureds from non-urban to urban areas.
• As many as 98,8% of the Indian population of 1,1 million were estimated to be living in urban areas in 1997. It is, however, difficult to compare 1996 and 1997 data to determine the extent of movement to urban areas among Indians, because of the small sample size of Indians in both years in non-urban areas.
• Among whites, 4,3 million (95,4%) of the estimated total of 4,5 million were in urban areas in 1997. It is again difficult to compare 1996 and 1997 data to determine the extent of movements into urban areas among whites, because of the small sample size of whites in both years in non-urban areas.

 Table A below shows the relationships between population group, age, gender and place of residence in 1996 and 1997.

* Each percentage is a percentage of all people in that particular category. For example, in column (iv), second row of the block
    labelled (a),   45,2% of all males and females aged 0 - 14 years lived in urban areas in October 1996. It follows that the remainder
    (54,8%) lived in non-urban areas.
** Number of responses were too few for this analysis.
*** These percentages should be treated with extreme caution, bearing in mind the small number of respondents in non-urban
        areas in the samples.

The table shows the following patterns:

• Among African males, a relatively small proportion of children aged 0 - 14 years (36,5% in 1996; 34,8% in 1997) were living in urban areas, as against slightly more than half of those aged 15 - 65 years (51,3% in 1996; 51,4% in 1997). But amongst those aged 66 years or more, a relatively small proportion (33,2% in 1996; 35,1% in 1997) were again found to be living in urban areas. This suggests that a large portion of African males of working age migrated to urban areas in search of work, but children and older people tend to live in or return to non-urban areas.
• Among African females, a similar pattern emerges, but it is less pronounced than the one found among African males. In both 1996 and 1997, in all age categories, fewer than half of the African females were living in urban areas. African women of working age tend to move to urban areas in search of work to a lesser extent than do African men.
• This pattern is not so easily found among males and females in the other population groups, since the vast majority of people in these groups were already living in urban areas.

 Urban and non-urban population in each province

Figure 1 indicates the proportion of people living in urban and non-urban areas in each province in 1997. It shows that Gauteng had the largest percentage of people living in urban areas, followed by the Western Cape. The Free State and Northern Cape had relatively high proportions of people living in urban areas, but they consist largely of small towns. The province with the smallest proportion living in urban areas was the Northern Province, followed by Eastern Cape with the second smallest proportion, and then North West.

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

Access to infrastructure varied, not only by whether the household lived in an urban or non-urban area in October 1996 and 1997, but also by the population group of the household head.

 Table B below indicates these findings. Only the total numbers and percentages of households with access to infrastructure in the country as a whole, and those households headed by Africans are shown in this table, since relatively few coloured-, Indian- and white-headed households did not have access to these facilities.

 The table indicates the following:

• The access of African-headed households to infrastructure in general, as well as in urban and non-urban areas, had improved in October 1997 compared with October 1996. For example, in 1996, 48% of African-headed households had access to running water in the dwelling or on site. This proportion had increased to 52% in 1997.
• African-headed households in non-urban areas were the least likely group, overall, to have access to infrastructure, in both 1996 and 1997. For example, in 1996 only 21% of non-urban African-headed households had access to running water inside the dwelling or on site, compared with 78% of African-headed households in urban areas.
• In 1997 however, the proportion of African-headed households in non-urban areas with access to running water in the dwelling or on site had increased to 23%. In urban areas it had also increased to 82%.

* Each percentage is a percentage of all people in that particular category. For example, in second column of the second row of the block labelled (c) we read in column (ii) that in non-urban areas 923 households altogether had running water inside the dwelling, in the back yard or on the site where they lived in 1996. This means that 25,4% of all households (column iv) had running water in the dwelling or on site in 1996.

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

Figure 2 shows that approximately three quarters of the households (74%) 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 1997. In urban areas, this proportion was higher, but it was lower in non-urban areas. Approximately one in every seven households in urban areas (15%) were living in informal housing or shacks, either in informal settlements or in back yards. In non-urban areas, approximately one in every three households (33%) were living in traditional dwellings.

Figure 2: Types of dwellings in which households live in urban and non-urban areas 

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

Unemployment varied significantly in both 1996 and 1997, not only by urban or non-urban place of residence, but also by gender and population group, using either the official or the expanded definition of unemployment (see Statistical release P0317.10 and the definitions in this release).

 Table C below compares unemployment rates in 1996 and 1997 in terms of the official definition of unemployment, while Table D compares unemployment rates over the two years using the expanded definition. These tables indicate the following differences in unemployment rates by population group, gender and milieu in 1996 and 1997.

• There has been an increase in unemployment between 1996 and 1997. This increase is significant using 95% confidence intervals for the expanded definition, but it is not significant for the official definition (for more details see the section in this release on further analysis). There was thus a significant increase in the number and percentage of people in 1997 who were unemployed, but they had not looked for work in the four weeks prior to the interview, compared with 1996.
• The total unemployment rate for October 1996 was 20,3% using the official definition and 34,4% using the expanded one. In October 1997, however, it rose to 22,0% using the official definition, and to 37,4% using the expanded definition.
• The highest unemployment rates in October 1996 and 1997, using either the official or the expanded definition, were found among African economically active females living in non-urban areas.
• The second highest rate was found amongst African economically active females living in urban areas.
• White economically active males were least likely to be unemployed.

* Each percentage is a percentage of all people in that particular category. For example, in the block labelled (c) in column (ii) we see that in 1996, according to the official definition of unemployment, 11,2% of economically active coloured males living in urban areas were unemployed.
** Number of responses were too few for this analysis.

* Each percentage is a percentage of all people in that particular category. For example, in the block labelled (c) in column (ii) we see that in 1996, according to the expanded definition of unemployment, 16,4% of economically active coloured males living in urban areas were unemployed.
** Number of responses were too few for this analysis.

Unemployment and education

Figure 3 indicates that there is a curvilinear relationship between unemployment and education in 1997. Using the official unemployment rate, unemployment is highest among those economically active people who have completed primary school, but it is lowest for those economically active people with post-school qualifications or with no education. The same pattern was found in 1996

Figure 3: Percentage of the economically active in each education category who are unemployed (official definition) 

Confidence limits

Table E indicates the estimated values, and the lower and upper confidence limits at the 95% level, for both the number and the percentage of certain selected variables from OHS ’96 and OHS ’97, for example unemployment rates, type of housing and access to services. (Information on confidence limits at lower levels of disaggregation, for example by population group and gender, or for provinces or other variables, may be obtained from Stats SA.)

For example, if we look at the 1996 unemployment numbers using the official rate, we see that an estimated 2,22 million people were unemployed. We are 95% confident that the actual value of this estimate falls within the range from 1,99 million and 2,46 million. If we look at the percentages in the same row, the estimated unemployment rate is 20,3%. We are 95% confident that the unemployment rate lies somewhere between 18,5% and 22,2%.

The table indicates that living conditions in the country had improved between 1996 and 1997.

• A significantly larger number and proportion of households had obtained better housing between October 1996 and October 1997,
• Between these two time periods, a significantly larger number and proportion of households had obtained access to piped water on the site of their dwelling.
• Proportionately fewer households were using candles for lighting in 1997 compared to 1996.

 Table E also indicates that there is a possible increase in unemployment over this time period. There was a significant increase in unemployment using the expanded rather than the strict definition, or an increase in the number and proportion of discouraged work-seekers.

NOTES

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 excludes 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 1997 OHS forms part of a series of releases of household survey information.

 Statistics South Africa plans to do further comparisons of 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 1997 OHS

The OHSs of 1994, 1995, 1996 and 1997 were independent surveys, and different samples were designed for each of them.

 The data base of EAs, as established during the demarcation phase of Census ’96, constituted the sampling frame for selecting EAs for the 1997 OHS. The sampling procedure involved explicit stratification by province and transitional metropolitan and district councils. Independent 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, 3 000 EAs were drawn by means of probability proportional to size principles in each stratum. The measure of size was the number of households in each EA. Interviewing for the 1997 OHS took place in these 3 000 EAs, and systematic sampling was applied to select 10 households to visit in each EA. This means that 3 000 EAs were identified as primary sampling units, and 30 000 households were visited as ultimate sampling units.

 4. Weighting the1997 OHS

The 1997 OHS was weighted to estimates of the population size based on the population census of October 1996, as adjusted by a post-enumeration survey (PES), using post-stratification by province, gender and five-year interval age groups. Relative scaling was also done, to cater for population group and urban - non-urban splits.

 The 1996 OHS was also weighted to the PES-adjusted count of Census’96. However, because of the smaller sample size and the more clustered sample of households that was drawn, different weighting procedures were used, as discussed in the 1996 OHS statistical release.

 Prior to 1996, OHS surveys were weighted to reflect estimates of population size using the 1991 population census. The data reported here for 1997 and those recently reported for 1996 are therefore not presently directly comparable with the previously published OHS figures for 1994 and 1995. 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. After this process is complete, comparisons between 1994, 1995, 1996 and 1997 will be possible.

5. Employment in the agricultural sector

The agricultural sector shows a sharp decline between 1995 (re-weighted to Census ’96) and 1996, and no change was noted between 1996 and 1997 for the following reasons.

• The sharp increase between 1995 and 1996 in the "other and unspecified category" indicates that it was difficult to code industrial sector in 1996.
• The identification of non-urban EAs in 1995 was based on the 1991 population census estimates. In both 1996 and 1997, however, the identification of non-urban EAs was based on actual 1996 census demarcations. As a result, relatively more agricultural workers were enumerated in the 1995 OHS than in 1996 or 1997.

6. Symbols used in the tables that follow

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 (*) is shown in the table, the sample size was too small to give reliable estimates.

7. Comparability of results with other Stats SA data sources

The Survey of total employment and earnings (STEE) collects information on formal employment in South Africa. The latest results of the STEE, i.e. for June 1999, were published in September, 1999 in statistical release P0271.These show a steady decline in formal sector employment, from 5,2 million in September 1996 to 4,9 million in June 1999.

Care should be taken when comparing the results of the STEE with results of the annual OHSs, since different target populations, survey designs and methodologies are used. The OHS collects information from households, the STEE collects information from formal sector businesses, excluding the following:

• agriculture, hunting, forestry and fishing,
• restaurants and other eating and drinking places, boarding houses, caravan parks, guest farms,
• water and air transport,
• financial institutions,
• real estate and business services,
• educational services,
• medical, dental and other health services,
• welfare organisations,
• religious organisations,
• recreational and cultural services,
• household services, and
• all informal industries.

In the OHS, however, it is a household, rather than a business in a particular sector, which is sampled. This household selection determines whether or not a person is included in a particular OHS. In a probability sample such as the OHS, households containing people working in each of the above categories have the same chance of being selected in the proportion in which they work in a particular sector as those working in the other formal sectors covered in the STEE. The OHS, through its different methodology, thus covers all sectors.

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.

 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.

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