Statistics measure more than a single point in time. For example, when Statistics SA releases the monthly consumer price index, it is the rate of change - month on month, or year on year - that is presented, rather than a static indicator of inflation.
This is the case for most economic data, regardless of whether they are designed to measure activity in a particular sector or total economic growth (gross domestic product).
Data from population censuses can, like information gathered through economic surveys, be used to measure the change in a country over time. In general, this sort of comparison can only be undertaken with accuracy and confidence if successive population censuses are conducted with high levels of consistency in terms of methodology (including standards, classifications and definitions) and data items on which information is gathered.
In South Africa, population censuses prior to 1996 did not profile the entire population, largely as a consequence of the apartheid policies and practices that official statistics were designed to support. However, a project is under way that attempts to compare data collected in previous population censuses.
This is linked to the African Census Analysis Project, a collaborative initiative between the University of Pennsylvania and African institutions specialising in demographic research and training.
As part of the project, a dedicated system, the Pan-African Census Explorer, is being developed, which aims to archive microcensus data and make them accessible.
In South Africa, this system aims to archive census data and metadata so that, wherever possible, information from censuses held in 1970, 1980, 1985, 1991, 1996 and 2001, as well as censuses held in former homelands (Bophuthatswana in 1980 and 1991, and the Ciskei and Venda in 1991) can be compared.
In a pilot project, Stats SA is attempting to use data from the 1991, 1996 and 2001 population censuses to measure change in a number of areas of Pretoria.
This is a complex exercise. In order to select areas for comparison, a common geography for Pretoria across 10 years had to be created. This involved linking enumerator areas - small parcels of land demarcated as a basis for organising the 2001 census - so as to create comparable geographical regions.
In the Pretoria pilot, Stats SA's geographical information system has been used to construct boundaries for areas that include previously middle- and upper-class white suburbs such as Sunnyside and Waterkloof; historically African townships including Mamelodi, Atteridgeville and Soshanguve; and areas of mainly Indian (Laudium) and coloured (Eersterus) residence.
Data from the three censuses have to be attached to each of these geographical areas. Data items to be compared for these areas, across the decade from 1991 to 2001, include age, gender, population group, language, level of education, work status, and industry (if employed).
The geographical areas have been designed to profile the nature of socioeconomic change over 10 years. It can be anticipated that some areas will reflect rapid change in the population group profile of residents (Sunnyside, for example). Other areas might reflect a change in socioeconomic or class characteristics, particularly where people of colour aspiring to middle-class status have moved into historically white areas that were the preserve of a white working class economically protected through apartheid.
The changing socioeconomic composition of areas that have remained largely constant in terms of population group (such as Mamelodi, Atteridgeville, Laudium and Eersterus) will also be examined carefully.
This exercise entails complex mobilisation of geographical information systems; and data harmonisation exercises where methodologies, data items, standards and classifications across censuses were inconsistent and incompatible.
Where the outcomes prove credible and useful, they will form the basis for similar profiling projects across South Africa.