The Beijing Platform for Action which emerged from the 1995 Fourth United Nations World Conference on Women called for the development of 'suitable statistical means to recognise and make visible the full extent of the work of women and all their contributions to the national economy, including their contribution in the unremunerated and domestic sectors'. During 2000, Statistics South Africa (Stats SA) conducted the fieldwork for the first national time use study in the country. The aim of the survey was to provide information on the way in which different individuals in South Africa spend their time. Such information contributes to greater understanding of policymakers on the economic and social well-being of different societal groups. In particular, the study was intended to provide new information on the division of both paid and unpaid labour between women and men, and greater insight into less well understood productive activities such as subsistence work,casual work and work in the informal sector.
The survey thus had dual objectives: (1) improvement of concepts, methodology and measurement of all types of work and work-related activity, and (2) the feeding of information into better policy-making, with a particular focus on gender equity.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Units of analysis for the survey include households and individuals
v1: Edited, anonymised dataset for licensed distribution
The Time Use Survey covered details of the household and demographic details of the two people selected as respondents in that household. The questionnaire also consisted of a diary in which to record activities performed by the respondents.
The survey covered household members in South Africa, ten years old and above
Producers and sponsors
Statistics South Africa
Norwegian Agency for Development Cooperation
The time use study sample frame was based on the frame prepared for the 1999 Survey of activities of young people (SAYP). This sample frame was based on the 1996 population census enumerator areas (EAs) and the number of households counted in the 1996 population census. The sampled population excluded all prisoners in prison, patients in hospital, people residing in boarding houses and hotels (whether temporary or semi-permanent), and boarding schools. The 16 EA types from the 1996 Population Census were condensed into four area types, or strata. The four strata were formal urban, informal urban, non-commercial farming rural, and commercial farming areas. Institution type EAs were excluded from the sample.
The EAs were explicitly stratified by province, and within a province by the four strata. The sample size (10 800 dwelling units, with 3 600 units in each of the three tranches) was disproportionately allocated to the explicit strata using the square root method. Within the strata, the EAs were ordered by magisterial district and the EA-types included in the area type (implicit stratification). Primary sampling units (PSUs) consisted of an EA of at least 100 dwelling units. Where an EA contained less than 100 dwelling units, EAs were pooled (using Kish's method of pooling) to meet this requirement. Most EAs had fewer than 100 dwelling units. The dwelling unit was taken as the ultimate sampling unit (USU).
Firstly, a two stage sampling procedure was applied. The allocated number of PSUs was systematically selected with probability proportional to size in each explicit stratum (with the measure of size being the number of dwelling units in a PSU). In each PSU, a systematic sample of 12 households was drawn.
The sample was based on the 1996 Population Census enumerator areas and the estimated number of households from the 1996 Population Census. The initial weights (household weight), based on the sample design, were equal to the inverse of the probability of selection. Further adjustment factors were then calculated to account for non-response.
To adjust for under-enumeration and to align survey estimates with independent population estimates, the weights were calibrated against person benchmarks. A software package called CALMAR was used to perform this calibration. Using an iterative procedure, CALMAR adjusted the weights so that person estimates conformed as closely as possible with external person benchmarks.
Dates of Data Collection
Data Collection Mode
Data Collection Notes
The fieldwork for the study was conducted in three tranches - February, June, and October 2000 - so as to catch possible seasonal variations in time use. The questionnaire was administered face-to-face to the respondent through an interview rather than the respondent completing the questionnaire themselves as is done in most European countries. This methodology was necessary because of the high levels of illiteracy in the country. For example, the census of 1996 found that a full 20% of all South Africans aged 20 or more had not received any formal education. To promote comparability, the diary was administered even where the person was literate and numerate. Questionnaires were also administered in the language chosen by the respondent.
Over 100 temporary fieldworkers were employed for each tranche of the survey. Where possible, the same fieldworkers were employed in later tranches. Fieldworkers worked in teams of three or four, with one person in each team serving as a supervisor. Each provincial office of Stats SA allocated one of their full-time staff to serve as a coordinator for the duration of the survey.
The questionnaire for the time use survey was comprised of three sections. Section one covered details of the household. Section two covered demographic details of the first person selected as a respondent in that household. Section three consisted of a Background and methodology diary in which to record the activities performed by the first person selected during the 24 hours between 4 am on the day preceding the interview and 4 am on the day of the interview. Sections four and five were for the second selected person in the household but were otherwise identical to sections two and three respectively.
The household and demographic sections of the questionnaire contained many of the standard questions of Stats SA household surveys. This was done so as to facilitate comparison across surveys. These sections also contained some additional questions on issues that would be likely to affect time use. For the household section, for example, there were questions on access to household aids such as washing machines and vacuum cleaners. In the demographic section there were questions about the presence of the respondent's young children in the household.
The diary, which forms the core instrument of a time use study, was divided into half-hour slots. Respondents were asked an open-ended question as to the activities performed during a given half-hour. These activities were then post-coded by the fieldworker according to the activity classification system (see below). The respondent could report up to three activities for each time slot. Where there was more than one activity reported for a half hour, the respondent was asked whether these activities were conducted simultaneously, or one after the other. For each recorded activity, the questionnaire also included two location codes. The first code provides for eight broadly defined locations plus the mobile activity of travel. Where the location of a particular activity could be classified as more than one of the given options, the option highest on the list took precedence. For example, a domestic worker was classified as working in someone else's dwelling rather than in a workplace. The second code distinguished between interior (inside) and exterior (outside) for the eight broadly-defined locations, and distinguished the mode of travel for all travel activity.
The data from the diary were captured in Sybase at Stats SA head office through a custom-designed data capture programme. The programme contained some in-built checks. Further checks were done manually prior to and after capture. The data were subsequently downloaded into SAS format, and the SAS programme was used for analysis.
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DDI Document ID
University of Cape Town
Date of Metadata Production
DDI Document version
Version 01: Adopted from "ddi-zaf-datafirst-tus-2000-v1" DDI that was done by metadata producer mentioned in "Metadata Production" section.