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CLASSIFICATION OF NOT-FOR-PROFIT ORGANISATIONS
6 The classification system used in this survey was a reduced version of the classification that is recommended in the United Nations' Handbook on Non-Profit Institutions in the Systems of National Accounts, the International Classification of Non-Profit Organisations (ICNPO).
7 ICNPO is fundamentally an activity classification, and it permits a fuller specification of the components of the not-for-profit sector than the industry classification used in Australia, the Australian and New Zealand Standard Industrial Classification (ANZSIC).
8 ICNPO organises not-for-profit organisations into 12 groups:
9 For the purposes of the survey, relevant ANZSIC06 Classes were concorded to ICNPO Groups. There were instances where an ANZSIC06 Class cut across several ICNPO Groups:
10 In keeping with the design and collection constraints of the survey the 12 ICNPO groups listed in paragraph 8 were arranged into the nine groups shown below:
11 See Appendix 1 for a full version of ICNPO and Appendix 2 for the concordance between ICNPO and the ANZSIC06 classification.
STATISTICAL UNITS DEFINED ON THE ABS REGISTER
12 The ABS uses an economic statistics units model on the ABS Business Register to describe the characteristics of businesses/organisations, and the structural relationships between related businesses/organisations. The units model is also used to break groups of related businesses/organisations into relatively homogeneous components that can provide data to the ABS.
13 In mid 2002, to better use the information available as a result of The New Tax System, the ABS changed its economic statistics units model. The new units model allocates businesses/organisations to one of two sub-populations. The vast majority of businesses/organisations are in what is called the ATO Maintained Population, while the remaining businesses/organisations are in the ABS Maintained Population. Together, these two sub-populations make up the ABS Business Register population.
ATO Maintained Population
14 Most businesses/organisations in Australia need to obtain an ABN, and are then included on the ATO Australian Business Register. Most of these businesses/organisations have simple structures; therefore the unit registered for an ABN satisfies ABS statistical requirements. For these businesses/organisations, the ABS has aligned its statistical units structure with the ABN unit. The businesses/organisations with simple structures constitute the ATO Maintained Population, and the ABN unit is used as the economic statistics unit for all economic collections.
ABS Maintained Population
15 For the population of businesses/organisations where the ABN unit is not suitable for ABS statistical requirements, the ABS maintains its own units' structure through direct contact with the business/organisation. These businesses/organisations constitute the ABS Maintained Population. This population consists typically of large, complex and diverse businesses/organisations. The new statistical units model described below has been introduced to cover such businesses/organisations:
16 In the 2006-07 Not-for-profit Organisations Survey, the statistical unit is the ABN or the TAU.
17 For more information on the impacts of the introduction of the new economic statistics units model, refer to Information Paper: Improvements in ABS Economic Statistics [Arising from The New Tax System] (cat. no. 1372.0).
18 The frame used for the 2006-07 Not-for-profit Organisations Survey, like most ABS economic collections, was taken from the ABS Business Register. The frame is updated monthly to take account of new organisations and those which have ceased employing.
IMPROVEMENTS TO COVERAGE
19 Data in this publication have been adjusted to allow for lags in processing new organisations to the ABS Business Register, and the omission of some organisations from the register. The majority of organisations affected, and to which the adjustments apply, are small in size.
20 Adjustments have been made to include new organisations in the estimates in the periods in which they commenced operations, rather than when they were processed to the ABS Business Register. Adjustments of this type will continue to be applied in future periods.
21 For more information on these adjustments, please refer to the ABS publication Information Paper: Improvements to ABS Economic Statistics, 1997 (cat. no. 1357.0).
COMPARISON WITH OTHER ABS STATISTICS
22 Data for not-for-profit organisations are also published in Australian National Accounts: Non-Profit Institutions Satellite Account (cat. no. 5256.0). There are important differences between the statistics published in the Australian National Accounts: Non-Profit Institutions Satellite Account and Not-for-profit Organisations publications and users should exercise caution when making comparisons between the two sets of estimates. The differences are broadly described in paragraphs 23 and 24 below.
23 Australian National Accounts: Non-Profit Institutions Satellite Account presents data for the not-for-profit sector which were compiled from a variety of existing economic and social collections conducted by the ABS and other agencies.
24 Not-for-profit Organisations is a dedicated survey of not-for-profit organisations and supplements Australian National Accounts: Non-Profit Institutions Satellite Account statistics with a detailed examination of the structure and performance of not-for-profit organisations for the reference year of the survey.
25 Historical comparisons cannot be made as this is the first time this survey has been conducted by the ABS.
RELIABILITY OF THE DATA
26 When interpreting the results of a survey it is important to take into account factors that may affect the reliability of estimates. Such factors can be classified as either sampling or non-sampling error.
27 The estimates are based on information obtained from a randomly selected stratified sample of not-for-profit organisations. Consequently, the estimates for the Not-for-profit Organisations Survey are subject to sampling variability, that is, they may differ from the figures that would have been obtained if all units had been included in the survey (that is, if a census had been conducted). One measure of the likely difference is given by the standard error (SE), which indicates the extent to which an estimate might have varied by chance because only a sample of units was included.
28 There are about two chances in three that a sample estimate will differ by less than one SE from the figure that would have been obtained if a census was conducted and approximately 19 chances in 20 that the difference will be less than two SEs.
29 Sampling variability can also be measured by the relative standard error (RSE), which is obtained by expressing the SE as a percentage of the estimate to which it refers. The RSE is a useful measure in that it provides an immediate indication of the sampling error in percentage terms, and this avoids the need to also refer to the size of the estimate.
30 The following table contains estimates of RSEs for a selection of statistics presented in the not-for-profit survey output.
31 As an example of the above, the estimate of total income for not-for-profit organisations in 2006-07 was $75,953.7m and the RSE is 4.4%, giving a SE of approximately $3,342m. Therefore, there would be two chances in three that, if all units had been included in the survey, a figure in the range of $72,611.7m to $79,295.6m would have been obtained, and 19 chances in 20 (i.e. a confidence interval of 95%) that the figure would have been within the range of $69,269.7m to $82,637.6m.
32 The sampling variability for estimates at the activity classification (ICNPO) level and data item level was generally higher than at the total not-for-profit sector level and should therefore be viewed with more caution.
33 Estimates that have an estimated relative standard error between 10% and 25% should be used with caution as they are subject to sampling variability too high for some purposes. Estimates with an RSE between 25% and 50% should be used with caution as they are subject to sampling variability too high for most practical purposes. Estimates with an RSE greater than 50% indicate that the sampling variability causes the estimates to be considered too unreliable for general use. Data with RSEs in these ranges are annotated with a red triangle in the upper right hand corner of the cell in the spreadsheets which contain the survey data.
34 Errors other than those due to sampling may occur in any type of collection and are referred to as non-sampling error. For this survey, non-sampling error may result from such things as deficiencies in the register of organisations from which the sample was drawn, non-response, imperfections in reporting and/or errors made in compiling results. The extent to which non-sampling error affects the results of the survey is not precisely quantifiable. Every effort was made to minimise non-sampling error by careful design and testing of questionnaires, efficient operating procedures and systems and the use of appropriate methodology. Survey estimates subject to a high level of non-sampling error have been suppressed or provided with relevant cautions.
35 Where figures have been rounded, discrepancies may occur between the sum of the components and the total. Similar discrepancies may occur between a proportion or ratio and the ratio of the separate components.
36 Data contained in the tables for this survey relate to the activities of not-for-profit organisations in Australia during the year ended June 2007. Financial estimates include the activity of any organisation that ceased or commenced operations during the year. Counts of organisations include only those that were operating at 30 June 2007. Employment estimates include only those persons working for organisations during the last pay period ending in June 2007. Volunteers include those persons volunteering during the year 2006-07 financial year.
37 ABS publications draw extensively on information provided freely by individuals, organisations and governments. Their continued cooperation is very much appreciated; without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.
38 Inquiries about these statistics should be made by contacting the National Information and Referral Service on 1300 135 070 or Julie Cole on (03) 9615 7562.
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