Australian Bureau of Statistics
3228.0 - Demographic Estimates and Projections: Concepts, Sources and Methods, 1999
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 30/08/1999
|Page tools: Print Page Print All RSS Search this Product|
3.45. The preliminary estimated population at 30 June 1996 which was derived by updating the previous census fell short of the 1996 Census-based population by 21,572 persons. In other words, the preliminary intercensal error was -21,572. Despite this, as can be seen in Table 3.1, a larger number of SLA totals across Australia were over-estimated (positive intercensal error) than were under-estimated (negative intercensal error). The number of SLAs where the population was over-estimated was 651, while 569 SLAs were under-estimated (in 4 SLAs, estimated population exactly matched census population). As noted earlier in 3.41, the preliminary figure used to calculate the total Australia intercensal error quoted above is later updated using final 1991-96 births, deaths and category jumping data. Using this updated figure, the overall intercensal error is closer to -27,500. However, since only the national and State population figures were updated in this manner, and this chapter concentrates specifically on SLAs (which were not updated in this manner), preliminary national and State totals have been used in this analysis.
3.48. Further insight into levels of intercensal error is obtained by comparing them for capital cities and the balance of the State.
3.49. The results of this are presented in Table 3.3. Overall, capital city populations were under-estimated by around 96,000 persons (0.8%), while the population residing outside capital cities was over-estimated by almost 75,000 persons (1.1%). This may help to explain why for most States, Table 3.1 showed higher proportions of over-estimated SLAs despite the fact that overall intercensal errors were negative, since in most States the majority of SLAs are located outside capital cities. The cities with the largest errors (in terms of percentage) were Darwin and Sydney, both of which were under-estimated. Outside the capital cities, the remainder of the Northern Territory and the remainder of Western Australia had the highest errors, with the remainder of the Northern Territory being under-estimated, while the remainder of Western Australia was over-estimated.
3.50. Table 3.4 presents a summary of the average absolute SLA and LGA intercensal error for each State, for both 1991 and 1996.
3.51. Overall, the average absolute intercensal error for SLA totals was 4.6% in 1991 and 4.8% in 1996. In both years, South Australia was the State with the lowest error in percentage terms, while the Northern Territory was the highest. The errors for LGA totals were, in percentage terms, lower than those for SLAs. It can be assumed that this is partly due to LGAs having higher average population sizes. Despite this, errors for SLAs and LGAs follow generally the same pattern in that States with larger SLA errors, generally have larger errors for LGAs, and vice versa. Comparing 1991 and 1996, it can be seen that percentage errors for SLAs were fairly similar for New South Wales, South Australia, Western Australia, and the Australian Capital Territory, were lower for Tasmania and Queensland, but tended to be higher in 1996 for Victoria and the Northern Territory.
3.52. Between 1991 and 1996, SLAs in all States were affected by boundary adjustments. SLA boundaries in Victoria and Tasmania in particular underwent a series of major adjustments, while some significant boundary restructuring also took place in Queensland. This impacts on the continuity of the symptomatic indicators used in the regression phase and subsequently can be expected to lead to higher 1996 errors in these States, LGAs and SLAs than might otherwise have been the case. Another point to note when comparing State intercensal errors is that differences in factors such as the average population size, growth rates, state intercensal error and population distribution should also be taken into account, since all of these influence the degree of accuracy of population estimates (Demography Working Paper 98/1: Issues in Estimating Small Area Populations).
3.53. Table 3.5 presents a comparison of intercensal errors in a number of countries. As noted previously, the average population size of the areas being estimated has considerable effect on the accuracy of the estimates subsequently produced. For this reason, intercensal error figures for both SLAs and Statistical Subdivisions (SSDs) have been included for Australia. While SLAs are the basic units of estimation in Australia, SSDs, which are an amalgamation of SLAs, are closer in size, on average, to 'local areas' in other countries. Consequently, it is perhaps more meaningful, for comparative purposes, to use the intercensal error for SSDs in this type of analysis. It can be seen from Table 3.5 that average absolute percentage errors for Australian SSDs compare favourably with those for 'local areas' in other countries.
This page last updated 12 March 2007
Unless otherwise noted, content on this website is licensed under a Creative Commons Attribution 2.5 Australia Licence together with any terms, conditions and exclusions as set out in the website Copyright notice. For permission to do anything beyond the scope of this licence and copyright terms contact us.