TECHNICAL NOTE - DATA QUALITY

RELIABILITY

1 The estimates in this release are based on information obtained from a sample survey, the Energy, Water and Environment Survey (EWES), and from the National Greenhouse and Energy Reporting Scheme (NGERS) conducted by the Clean Energy Regulator (CER). Any collection of data may encounter factors that impact the reliability of the resulting statistics, regardless of the methodology used. These factors result in non-sampling error. In addition to non-sampling error, sample surveys are also subject to inaccuracies that arise from selecting a sample rather than conducting a census. This type of error is called sampling error.

Sampling error

2 The majority of data contained in this publication have been obtained from a sample of businesses. As such, these data are subject to sampling variability; that is, they may differ from the figures that would have been produced if the data had been obtained from all businesses in the population. One measure of the likely difference is given by the standard error, which indicates the extent to which an estimate might have varied by chance because the data were obtained from only a sample of units. There are about two chances in three that a sample estimate will differ by less than one standard error from the figure that would have been obtained if all units had been included in the collection, and about nineteen chances in twenty that the difference will be less than two standard errors.

3 Sampling variability can also be measured by the relative standard error (RSE), which is obtained by expressing the standard error 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 percentage errors likely to have occurred due to the effects of random sampling, and this avoids the need to refer also to the size of the estimate. Selected data item RSEs at the industry division level for Australia are shown in the table below. Detailed relative standard errors are available on request.

4 To illustrate, the estimate of electricity expenditure for the Mining industry in 2014–15 is $1,981m. The RSE of this estimate as shown is 1.2%, giving a standard error of approximately $23.8m. Therefore, there are two chances in three that, if all units had been included in the survey, a figure in the range of $1,957.2m to $2,004.8m would have been obtained, and nineteen chances in twenty (i.e. a confidence interval of 95%) that the figure would have been within the range of $1,933.4m to $2,028.6m.

5 Since RSEs are obtained by expressing the standard error as a percentage of the estimate, where estimates are small, this will result in a much larger relative standard error when compared with similar standard errors against another estimate. As a result, for small estimates the size of the RSE may be a misleading indicator of the reliability of the estimate.

Non-sampling error

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 record keeping practices across businesses and industries can also lead to some inconsistencies in the data provided to compile the estimates. Although much of this process is subject to standards, there remains a great deal of flexibility available to individual businesses in the record keeping 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. 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.

REFERENCE PERIOD

10 The period covered by the collection is, in general, the 12 months ended 30 June. Where businesses are unable to supply information on this basis, an accounting period for which data can be provided is used. Such businesses make a substantial contribution to some of the estimates presented in this publication. As a result, the estimates can reflect trading conditions that prevailed in periods outside the twelve months ended June in the relevant year.

QUALITY INDICATORS

11 In the 2014–15 EWES, there was an 84.6% response rate from all businesses that were surveyed and found to be operating during the reference period. Data were imputed for the remaining 15.4% of operating businesses. This imputation contributed 7.4 % to the total purchases of energy and fuels for all selected industries.

Data comparability

12 This section discusses the comparability of estimates with other ABS sources.

Comparison with other ABS statistics

13 The energy consumption figures presented in this publication may not be directly comparable with energy consumption statistics appearing in other publications. The main reason is due to differing scope and coverage (see Explanatory Notes for more detail). In addition the following points also lead to inconsistencies.

14 The consumption figures presented in this publication represent the cost and quantity of electricity and natural gas purchased by businesses. However, these figures do not reflect total energy consumed by the business, as described in the following.

15 These figures may exclude the value and quantity of energy produced and consumed in the intermediate steps of a businesses' production process. For example, when a business purchases black coal to produce coke, and then uses the coke to produce another product, the value and quantity of the intermediate fuel product (coke) is not reflected in the energy consumption figures for that particular business.

16 Energy end-use (final consumption) covers deliveries of commodities to consumers for activities that are not fuel conversion or transformation activities. Other publications may compile estimates on this basis, such as Energy Account, Australia, 2013–14 (cat. no. 4604.0). By contrast, the figures presented in this publication include commodities which are converted into other fuel types or products.

17 Amounts of electricity and natural gas purchased may not equal total amounts used. For example, the use of energy products sourced from a subsidiary business or from other businesses, where no corresponding financial transaction has taken place (non-monetary transaction).

18 The estimates for energy consumption do not include fuels, which were self generated by the business.

19 Businesses that had a rent or lease agreement (lessees) did not report their electricity and natural gas expenditure and consumption. However, the lessor included the costs and usage of these fuels even though they were incurred by a separate business through a rent or lease arrangement.