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TECHNICAL NOTE 2 DATA QUALITY
5 The size of the RSE may be a misleading indicator of the reliability of the estimates for (a) operating profit before tax, (b) earnings before interest, tax, depreciation and amortisation and (c) industry value added. It is possible for an estimate legitimately to include positive and negative values, reflecting the financial performance of individual businesses. In this case, the aggregated estimate can be small relative to the contribution of individual businesses, resulting in a standard error which is large relative to the estimate.
6 Error other than that due to sampling may occur in any type of collection, whether a full census or a sample, and is referred to as non-sampling error. All data presented in this publication are subject to non-sampling error. Non-sampling error can arise from inadequacies in available sources from which the population frame was compiled, imperfections in reporting by providers, errors made in collection such as in recording and coding data and errors made in processing data. It also occurs when information cannot be obtained from all businesses selected. The imprecision due to non-sampling variability cannot be quantified and should not be confused with sampling variability, which is measured by the standard error.
7 Although it is not possible to quantify non-sampling error, every effort is made to minimise it. Collection forms are designed to be easy to complete and assist businesses to report accurately. Efficient and effective operating procedures and systems are used to compile the statistics. The ABS compares data from different ABS (and non-ABS) sources relating to the one industry, to ensure consistency and coherence.
8 Differences in accounting policy and practices across businesses and industries can also lead to some inconsistencies in the data used to compile the estimates. Although much of the accounting process is subject to standards, there remains a great deal of flexibility available to individual businesses in the accounting policies and practices they adopt.
9 The above limitations are not meant to imply that analysis based on these data should be avoided, only that the limitations should be considered when interpreting the data presented in this publication. This publication presents a wide range of data that can be used to analyse business and industry performance. It is important that any analysis be based upon the range of data presented rather than focusing on one variable.
10 Where businesses were unable to supply data for the 12 months ended 30 June, an accounting period for which data can be provided is used for data other than those relating to employment.
11 Estimates of financial data in some industries are heavily impacted by fluctuating commodity prices. In these industries the reporting by businesses for an accounting period that is not for the period ended 30 June can result in different estimates compared with what they would have been, had the businesses reported for an accounting period ended 30 June.
12 In November 2011, the ABS released an information paper on the impact that businesses reporting for accounting periods other than those ended 30 June had on the estimates present in past versions of this release. In the second half of 2013, the ABS will release this paper updated to show the impact of off-June reporters on estimates presented in this release.
13 Non-sampling error also occurs when information cannot be obtained from all businesses selected in the survey. For the 2011-12 survey of the Construction industry, there was an 80.3% response rate from all businesses that were surveyed and found to be operating during the reference period. Data were imputed for the remaining 19.7% of operating businesses. This imputation contributed 17.3% to the estimate of total income for the Construction industry.
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