Comparison between Census and WIPR data Date: 21 September 2004.

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Presentation transcript:

Comparison between Census and WIPR data Date: 21 September 2004

To provide some background to the projections To illustrate why an evaluation of the Markdata projections and the Census is necessary To provide a summary of the challenges and the methodology To report on progress thus far To sketch a possible way forward Objectives

Background? The Department needs to plan water resources and water consumption is partly depend on population growth. Markdata was commissioned in 1995 to undertake a set of projections to establish potential water demand over time. Geographical areas covered – Magisterial Districts – Water Consumption Centres At that time census 1996 data were unavailable. Base data for this set of projections consisted of “triangulation” between various sources (1991 census data, projected data and Markdata Surveys). The 1970 census was also used to inform the base data as this was the last census that covered the whole of South Africa.

Background? Various population and economic variables: –Population growth for the period –Major indicators of economic growth –Net migration during 1996 –Indicators of employment and –Household income during 1996 and –Gross Geographic Product informed future growth potential and individual forecasts was undertaken for each Magisterial District and Consumption Centre up to The purpose of this project would therefore be to assess whether these projections compare favourably to the 2001 census results. Boundary changes and migration result in differences at smaller geographical levels especially magisterial district and placenames

Why ?

Why do we need to compare the projections to the census data ? –Change over time in demographic trends and in the structure of the economy. –Most projections rest on assumptions and these assumptions may not hold true for long periods of time. Recent trends are, for instance: –Any uncertainties associated with an illness such as HIV/AIDS and interventions such as the use of ART - impact difficult to assess. –Slight errors in the data may be compounded and could deviate majorly in twenty years time Why ? Number of households m 11.8 m Average household size

The latter could also be illustrated by the following: Why ? Census extrapolated to 2000Number of People 1950Prof. Jan Sadie26,3 1955Tomlinson Commission 28,7 1973Prof. Jan Sadie49,1 1980JL van Tonder & Willie Mostert 39,4 1988Prof. Jan Sadie47,5 1989Bureau for Market Research 47,6 1995Prof Charles Simkins45,4 At national and provincial level the IWRP data did not differ significantly, but the question remained whether there would be significant differences at magisterial level.

Data Challenges ?

–Differences in the coding system between the 1996 and 2001 census –Differences in the 2001 Spatial data and the 2001 Alpha- numeric data because of cross- boundary demarcation Data Challenges ?

–Code and name differences worse at the placename level Data Challenges ?

–Three data sets were integrated into one: Population census1996 Population census 2001 IWRP Data –Sorted coding and naming problems and performed data checks –IWRP data projections obtained for 1995, 2005 and –Projected estimates derived for 1996 and 2001 by interpolating. –Preliminary comparisons performed using adjusted estimates –Difference measured using the numbers and ratios Aggregated to National level Provincial level and Magisterial District Methodology

Difference per province (2001) ProvinceIWRP-CIWRP/C% C/IWRP Eastern Cape Free State Gauteng Kwazulu-Natal Limpopo Mpumalanga Northern Cape North West Western Cape RSA –Larger differences possibly mainly attributable to migration

Preliminary Results –Preliminary analysis indicate a relatively small difference in population size. –Deviations in 15% of the cases probably still need to be determined since likelihood for larger or smaller population has not yet been established. –In approximately 5% of the magisterial districts differences would be as a result of the boundary problems. Ratio IWRP/CFrequencyValid Percent <= Total353100

Way Forward –Investigate the reasons for differences. –Refine the analysis. –The census has not been tested for undercount yet. –This analysis will inform the next steps where the various components for a changing population need to be investigated looking at fertility, migration, mortality and other factors, etc. –The placename data need to be integrated to enable a comparison between urban population in the IWRP data. –Household growth expected to play a significant role in water consumption.

Sample table slide Thank you