Australian Bureau of Statistics
5216.0 - Australian National Accounts: Concepts, Sources and Methods, 2000
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 15/11/2000
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The concept of quality
29.1 Given the importance of the national accounts for economic policy formulation and for monitoring the impact of economic policy, it is important that they are of a high quality. The quality of a particular statistic is determined by its 'fitness' for whatever purposes users have for the statistics. As different users use national accounts statistics for different purposes, views on what aspects of quality are most important will vary from user to user. Nonetheless, there are a number of aspects of quality that are relevant in most circumstances. These are:
29.2 This chapter describes each of these aspects of quality, and assesses the national accounts against them. Compilation of the national accounts is a complex task involving many diverse data sources. It is not possible to provide a single, comprehensive measure of the quality of the estimates. Nonetheless, it is possible to gain an insight into their quality by analysing each of the aspects of quality. To obtain an overall picture, all aspects need to be considered together. However, different users may weight each of the aspects differently, and within each aspect what satisfies one user may not satisfy another. Thus, two users may look at the same set of statistics, with one considering them to be of good quality while the other may think that there are quality deficiencies.
29.3 In understanding quality, it is also important to recognise that there are often trade-offs across the aspects of quality. For example, statistics that are very timely are often less accurate than those that are less timely. To overcome this, a sequence of estimates for a particular period of time may be released, with each estimate considered to be more accurate than the one that preceded it. However, the disturbance in estimates that this induces affects the reliability of the statistics. Trade-offs can also occur between accuracy and relevance. It may be more difficult to measure exactly what users require than something that approximates their requirements. It is also important to recognise that, in general, the higher the quality that an estimate is, the more costly it is to compile it. This is particularly so for the accuracy aspect of quality. Nonetheless, with improvements in technology and other aspects of the compilation process it may be possible to improve the quality of statistics without increasing costs. Another important issue that must be considered in assessing quality is the complexity of what is being measured. As complexity increases, as has been the case with the Australian economy, it becomes more difficult to maintain quality, all other things being equal. Again, improvements in the compilation process can have a mitigating impact on this.
29.4 In compiling the national accounts the ABS is mindful of all of these issues. The ABS maintains regular contact with key users and their views on what aspects of quality are most important to determine how the quality trade-offs are dealt with. User views on quality are also given prominence in developing work programs for improving the quality of the national accounts.
29.5 Accuracy can be defined as the proximity of an estimate to its notional true value. The true value is considered notional because, in practice, most statistics cannot be measured with perfect accuracy. Also, as this true value is generally unknown, it is generally impossible to quantify exactly how far an estimate deviates from its true value. Nonetheless, by being aware of the factors that influence accuracy, judgements can be made as to the extent of error likely to be associated with an estimate. These judgements can be enhanced by comparing estimates that conceptually should be identical, or by comparing estimates where a particular relationship between the estimates could be expected. In other words, the extent to which a set of statistics are coherent can provide a guide to the accuracy of the statistics. However, it should be noted that a coherent set of statistics is not necessarily an accurate set, as the statistics that are being compared may suffer from similar magnitudes of error with the errors being in the same direction.
29.7 The national accounts are compiled within a comprehensive framework, and so it is possible to reduce the impact of these data errors through the confrontation of the various estimates in the national accounts. Data confrontation is built around the conceptual relationships that exist between data items. The best known data confrontation exercise is the compilation of the annual supply and use tables. In the compilation of these tables, estimates of the supply (production) and use (demand) for commodities are compared, with differences in the initial estimates being eliminated. At the same time estimates of the value of production are compared with estimates of incomes attributable to production and differences are eliminated.
Data collection errors
29.8 The most likely source of data collection error, from a national accounts perspective, would result from the inability of data providers to report on the correct basis. The data requirements underlying the national accounts are complex and, although every effort is made to match survey data items with business accounting practices, it is inevitable that some data providers will include in their survey responses items that should not be included, and exclude items that should be included. Sophisticated techniques are used to edit provider responses but not all errors will be recognised and rectified. If patterns of misreporting are identified, steps will be taken to reduce the incidence of misreporting, either by specifically drawing to the attention of data providers what should be included or excluded, or by changing the reporting requirements to better align with business accounting practices. The problem with the latter approach, though, is that some adjustment will be needed to reported data to place it on the correct basis for national accounts compilation. This adjustment process is another source of error for the national accounts estimates themselves.
29.11 Statistical collections have a cost both to the organisation undertaking the collection and the respondents. The more frequent the collection, the greater the number of respondents or the greater the number of questions then the greater is the cost to both the statistical organisation and respondents. It is therefore necessary to adopt a strategy that makes the best possible use of data available from administrative and other sources and that structures statistical collections around these data such that they maximise the benefits for a given cost. This inevitably means that for many areas of economic activity accurate and detailed data are only available annually or less frequently. In these cases, annual or less-frequent benchmarks are established, with more frequent estimates derived using extrapolation and interpolation techniques. For the most part, indicator series are used for this purpose. The indicators vary in the closeness of their relationship to the concept being measured. For example, annual benchmark estimates of private gross fixed capital formation on machinery and equipment, which are derived from the annual Economy Activity Survey and taxation statistics from 1994-95 (and exclusively from taxation statistics for years prior to 1994-95), are projected using indicators from the quarterly Survey of Private New Capital Expenditure. These indicators are considered to be very good for this purpose, although they do have their deficiencies, such as the lack of coverage of non-employing businesses. In the case of the quarterly chain volume estimates of gross value added by industry, with the exception of agriculture, the quarterly indicators are either output or input measures rather than value added itself. In the short term, output measures are likely to be reasonable indicators of changes in value added in volume terms, but input measures preclude changes in productivity. The quarterly estimates for non-farm gross mixed income are not very satisfactory, as they are derived using broad activity indicators such as retail turnover and capital formation on dwellings. For some relatively minor series where no suitable quarterly information is available, annual estimates are extrapolated and interpolated using mathematical techniques.
Errors in coverage
29.13 Most of the ABS data sources used in the compilation of the national accounts are taken from the ABS's business register. As this register generally only contains businesses that employ staff, the estimates from these data sources generally exclude the economic activity of non-employing businesses.
29.16 Many of the data sources used to compile the national accounts, particularly those from the ABS, are based on sample surveys, rather than complete collections. Sample surveys are subject to a particular type of error, known as sample error. Unlike most other forms of error, the likelihood of sample error can be quantified using mathematical techniques. The most common measure of sample error is the relative standard error (RSE). The true value of any estimate lies within one RSE of the sample estimate about two-thirds of the time, and within two RSEs about nineteen times in twenty. For example, if a sample estimate of $100 million has an RSE of 3%, then there are about two chances in three that the true value lies in the range $97 million to $103 million, and nineteen chances in twenty that it lies in the range $94 million to $106 million.
Some assessments of the accuracy of quarterly national accounts estimates
29.18 While it is generally not possible to provide exact information on the accuracy of national accounts estimates, intuitive assessments of the accuracy of the estimates can be made, based on knowledge of data sources used. The tables below contain such assessments for the initial quarterly estimates of movement for key components of the accounts. Initial quarterly estimates of movement have been chosen as they are generally the most anticipated of the national accounts estimates. Each component is assigned one of the following grades:
29.19 As well as providing an indication of the accuracy for particular components, the tables can be used to assess the relative accuracy across the components of the national accounts.
29.20 In using the tables, it should be noted that the assessments of accuracy relate to the time this publication was printed. Estimates for prior or future periods may vary as the quality of data sources, compilation techniques, etc can change over time.
29.21 The following table contains accuracy ratings for the current price income and expenditure components of GDP, and for the chain volume measures of the expenditure components of GDP. The accuracy of the expenditure chain volume measures is generally a function of the accuracy of the current price estimates and the accuracy of the price indexes that are used to deflate the current price estimates.
Accuracy Ratings -- Expenditure and Income Components of GDP -- Initial Quarterly Estimates of Movement
29.22 The following table contains accuracy ratings for the industry value added chain volume measures. The accuracy of these estimates reflects both the appropriateness of the indicators used and the accuracy of the indicator estimates themselves.
Accuracy Ratings -- Industry Value Added, Chain Volume Measures -- Initial Quarterly Estimates of Movement
29.23 More objective, but limited, measures of accuracy are provided by the various statistical discrepancies contained in the national accounts. The table below shows estimates of the average absolute values of the statistical discrepancies in the three estimates of GDP. As explained in Chapter 4, there are three approaches that can be used to measure GDP: the income, expenditure and production approaches. In concept, each approach should deliver the same estimate; however if the measures are compiled independently using different data sources then different estimates will result. In Australia's national accounts, a single quarterly estimate of GDP is obtained by averaging the three measures, and statistical discrepancies are inserted to 'balance' each measure of GDP to the average.
Average quarterly statistical discrepancy(a) as a percentage of GDP
29.24 For years in which the national accounts are benchmarked to supply and use tables, there are no annual statistical discrepancies in the estimates of GDP as these are eliminated in the balancing process. However, for these years there are still quarterly statistical discrepancies as the sources and methods used to interpolate the annual benchmarks are generally independent.
29.25 Statistical discrepancies are also shown in the capital and financial accounts. The former is equal to the difference between the GDP expenditure and income statistical discrepancies. In the financial accounts, a 'net errors and omissions' item is included to reconcile the conceptually identical but in practice divergent estimates of net lending/borrowing and net change in financial position.
29.26 Small or zero statistical discrepancies do not necessarily mean that the aggregates to which they relate are of higher quality than those subject to larger statistical discrepancies. It is possible that there may be offsetting errors, or, in the case of the GDP statistical discrepancies, similar magnitudes of overstatement/understatement in each measure of GDP. It is for these reasons that statistical discrepancies, while they are useful indicators of quality, need to be interpreted with caution.
29.27 Economic analysts and policy makers not only require accurate and timely information on the movements in and magnitude of the principal national accounts aggregates, but they must also have confidence that these indicators are unlikely to change significantly as more complete data become available.
29.36 For a comprehensive analysis of national accounts revisions, see the article "Revisions to Quarterly Economic Growth Rates 1984 to 1993", published in the July 1998 issue of Australian Economic Indicators (Cat. no. 1350.0).
29.37 Timeliness refers to the lag between the end of a reference period and the publication of statistics for that period. There is an important trade-off between accuracy and detail on the one hand and timeliness of the release of statistics on the other. The source data that are used to compile the national accounts are available with varying degrees of timeliness, frequency, accuracy and detail. The data sources providing more detailed and accurate (from a national accounts perspective) data tend to be those that are less frequent and/or less timely. Because of this, within a given level of resources, improvements in timeliness can generally only be made at the expense of accuracy and detail. Different users react to this trade-off in different ways. A user interested in undertaking in-depth, long-term, analysis may prefer detailed statistics that are only availably annually. On the other hand, a user interested in understanding current economic conditions may prefer very timely and frequent estimates that are less detailed.
29.40 An important aspect of the quality of national accounts statistics is that the concepts, definitions and classifications should be relevant to, and understandable, by users.
29.44 It is important that statistics are accessible to those who need to use them. A highly accurate, relevant and timely set of statistics is useless to someone who cannot obtain them.
29.48 Users interested in understanding economic developments rarely rely solely on the national accounts. They supplement the information contained within the accounts with information from other ABS sources and from non-ABS sources. Therefore, it is important that the national accounts be as comparable with these other statistics as possible.
This page first published 15 November 2000, last updated 29 June 2012
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