Energy Use and Electricity Generation, Australia methodology

Latest release
Reference period
2017-18 financial year
Released
11/07/2019
Next release Unknown
First release

Explanatory notes

Introduction

This publication presents estimates of energy consumption and electricity generation by selected Australian industries in 2017-18. The estimates are produced by directly collected data from the Energy, Water and Environment Survey (EWES), conducted by the Australian Bureau of Statistics (ABS).

Reference period

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

The data incorporates all business units in scope of the EWES that were in operation at any time during the year. They also include any temporarily inactive units, i.e. those units which were in the development stage or were not in operation, but still existed and held or acquired assets and liabilities and/or incurred some non-operating expenses (e.g. depreciation, administration costs).

Classifications

The businesses that contribute to the statistics in this release are classified:

Scope

The scope of the collection consisted of all business entities operating in the Australian economy during 2017-18 and classified to:

  • Division B Mining
     
  • Division C Manufacturing
     
  • Division D Electricity, gas, water and waste services
     
  • Division E Construction
     
  • Division I Transport, postal and warehousing


Government owned or controlled Public non-financial corporations were included.

Micro non-employing units were excluded from the survey.

Coverage

This section discusses frame, statistical units, coverage issues and improvements to coverage.

Frame

Businesses contributing to the estimates in this release are sourced from the ABS Business Register (ABSBR), which has two components as described below.

Statistical units

The ABS uses an economic statistics units model on the ABSBR to describe the characteristics of businesses and the structural relationships between related businesses. Within large and diverse business groups, the units model is used to define reporting units that can provide data to the ABS at suitable levels of detail.

The ABSBR sources its register information from the Australian Business Register (ABR) and uses a two population model. The two populations comprise what is called the Profiled Population and the Non-Profiled Population. The main distinction between businesses in the two populations relates to the complexity of the business structure and the degree of intervention required to reflect the business structure for statistical purposes.

Non-profiled population

The majority of businesses included on the ABSBR are in the Non-Profiled Population. Most of these businesses are understood to have simple structures. For these businesses, the ABS is able to use the Australian Business Number (ABN) as the basis for a statistical unit. One ABN equates to one statistical unit.

Profiled population

For a small number of businesses, the ABN unit is not suitable for ABS economic statistics purposes and the ABS maintains its own units structure through direct contact with businesses. These businesses constitute the Profiled Population. This population consists typically of large or complex groups of businesses. The statistical units model below caters for such businesses:

  • Enterprise group: This is a unit covering all the operations in Australia of one or more legal entities under common ownership and/or control. It covers all the operations in Australia of legal entities which are related in terms of the current Corporations Law (as amended by the Corporations Legislation Amendment Act 1991), including legal entities such as companies, trusts and partnerships. Majority ownership is not required for control to be exercised.
     
  • Enterprise: The enterprise is an institutional unit comprising:
     
    • a single legal entity or business entity, or
       
    • more than one legal entity or business entity within the same enterprise group and in the same institutional subsector (i.e. they are all classified to a single SISCA subsector).
       
  • Type of activity unit (TAU): The TAU is comprised of one or more business entities, sub-entities or branches of a business entity within an enterprise group that can report production and employment data for similar economic activities. When a minimum set of data items is available, a TAU is created which covers all the operations within an industry subdivision (and the TAU is classified to the relevant subdivision of the ANZSIC). Where a business cannot supply adequate data for each industry, a TAU is formed which contains activity in more than one industry subdivision.
     

Coverage issues

The ANZSIC based industry statistics presented in this release were compiled differently from activity statistics. Each ABN unit or TAU on the ABSBR has been classified (by the ATO and the ABS respectively) to its single predominant industry class, irrespective of any diversity of activities undertaken.

Some businesses engage, to a significant extent, in activities which are normally carried out by different industries. For example, a predominantly mining business may also undertake significant amounts of manufacturing. Similarly, a mining business may produce significant volumes of goods which are normally produced in different mining industries. Where a business makes a significant economic contribution to industries classified to different ANZSIC subdivisions, the ABS includes the business in the Profiled Population, and 'splits' the TAU's reported data between the industries involved. Significance is determined using total income.

A TAU's reported data are split if the inclusion of data relating to the secondary activity, in the statistics of the industry of the primary activity, distorts (by overstating or understating) either the primary or secondary industry statistics at the ANZSIC subdivision level by:

  • 3% or more, where the industries of the primary and secondary activities are in the same ANZSIC division.
     
  • 2% or more, where the industries of the primary and secondary activities are in different ANZSIC divisions.
     

The ABS attempts to maintain a current understanding of the structure of the large, complex and diverse business groups that form the Profiled Population on the ABSBR through direct contact with those businesses. Resultant changes in their structures on the ABSBR can affect:

  • the availability of such businesses (or units within them) for inclusion in ABS collections.
     
  • the delineation of the units, within those groups, for which data are to be reported.
     

The ABS attempts to obtain data for those businesses selected for direct collection and which ceased operation during the year, but it is not possible to obtain data for all such businesses.

Improvements to coverage

Data in this release were adjusted to allow for lags in processing new businesses to the ABSBR, and the omission of some businesses from the register. The majority of businesses affected, and to which the adjustments apply, are small in size. As an example, the effect of these adjustments is generally 4% or less for most ANZSIC industry divisions.

Adjustments were made to include new businesses in the estimates for the period in which they commenced operation, rather than when they were processed to the ABSBR.

For more information on these adjustments, please refer to the ABS publication Information Paper: Improvements to ABS Economic Statistics, 1997 (cat. no. 1357.0).

Definition of key terms

Definitions for the data presented can be found in the Glossary.

Survey design

The frame (from which the direct collect sample was selected) was stratified using information held on the ABSBR. Businesses eligible for selection in the direct collect sample were then selected from the frame using stratified random sampling techniques.

Businesses were only eligible for selection in the survey (the direct collect sample) if their turnover exceeded a threshold level, or the business was identified as being an employing business (based on ATO information), as at the end of the reference period.

Businesses which met neither of these criteria are referred to as 'micro non-employing businesses'. These businesses were not eligible for selection in the sample.

A sample of 10,038 businesses was selected for the directly collected part of the 2017-18 EWES. Each business was asked to provide a range of key energy and water consumption and expenditure figures via an online survey questionnaire.

Effects of rounding

Where figures have been rounded, discrepancies may occur between totals and the sums of the component items. Proportions, ratios and other calculated figures shown in this release have been calculated using unrounded estimates and may be different from, but more accurate than, calculations based on the rounded estimates.

Data comparability

In some cases estimates in this release may differ from those collected from other sources. These differences may be the result of sampling or non-sampling error, or may result from differences in scope, coverage, definitions, data source or methodology.

Estimates on energy use and electricity generation have been produced since 2008-09 from the EWES. Given each iteration of the survey has a number of differences, such as changes to the scope, data source, form design and methodology, caution should be exercised when comparing estimates over time.

Energy prices

This release does not support the calculation of an average unit price utilising the monetary estimates and physical estimates in this release. There is a broad range of price indexes published by the ABS for the purpose of measuring price change over time.

Revisions

A select number of revised estimates for the 2014-15 reference year have been included for download to provide users with updated information. For more information on these revised estimates, please refer to the Changes since 2014-15 in this issue.

Further information

A range of further information is available, as described below.

Related publications

The following ABS releases present information on energy, water and the environment: 


In addition, the following releases present economy-wide industry data: 

Other information available

The EWES is a benchmark survey collected triennially since 2008-09. The 2017-18 results present the fourth iteration of EWES following the 2014-15, 2011-12 and 2008-09 releases. The next EWES will be conducted in respect of the 2020-21 financial year. In the interim years the Environment Indicators Survey (EIS) will be conducted in respect of the 2018-19 and 2019-20 reference periods. Data from this survey will be published in Energy Account, Australia (cat. no. 4604.0) and Water Account, Australia (cat. no. 4610.0).

The ABS issues a daily Release Advice on its web site which details products to be released in the week ahead.

Inquiries about this or other ABS releases should be made to the National Information and Referral Service on 1300 135 070.

Acknowledgement

ABS releases draw extensively on information provided freely by individuals, businesses, governments and other organisations. 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.

Use of Australian Taxation Office (ATO) data in this publication

The results of these statistics are based, in part, on tax data supplied by the ATO to the ABS under the Income Tax Assessment Act 1936, which requires that such data are only used for statistical purposes. No individual information collected under the Census and Statistics Act 1905 is provided back to the ATO for administrative or regulatory purposes. Any discussion of data limitations or weaknesses is in the context of using the data for statistical purposes, and is not related to the ability of the data to support the ATO's core operational requirements.

Data confidentiality

Legislative requirements to ensure privacy and secrecy of these data have been followed. Only people authorised under the Australian Bureau of Statistics Act 1975 have been permitted to view data about any particular organisation and/or person in conducting these analyses. No information about individual taxpayers (persons) has been released to the ABS. Aggregated personal income tax data are confidentialised by the ATO before release to the ABS. In accordance with the Census and Statistics Act 1905, results have been confidentialised to ensure that they are not likely to enable identification of a particular person or organisation.

Comments

ABS is currently looking for ways to improve the type and format of information we provide to users, and would welcome any comments or suggestions regarding future releases of Energy Use and Electricity Generation, Australia.

Comments should be sent to australian.industry.statistics@abs.gov.au, or addressed to the Director, Annual Industry Statistics Business Statistics Centre, Australian Bureau of Statistics, GPO Box 2796, Melbourne, VIC 3001.

Technical note - estimation methodology

Introduction

The availability of Business Activity Statement (BAS) data collected by the Australian Taxation Office (ATO) has provided the Australian Bureau of Statistics (ABS) with opportunities to improve the efficiency of collection design and estimation for its business surveys, while at the same time reducing the reporting burden placed on businesses. Under taxation law data may be passed by the Commissioner for Taxation to the ABS for specified statistical purposes.

Estimation methodology

The 2017-18 Energy, Water and Environment Survey (EWES) uses number raised estimation. Number raised weights are given by N/n (where N is the total number of units in the population for the stratum, and n is the number of responding units in the sample for that stratum). The weight assigned to each survey unit indicates the number of units in the target population that the survey unit is meant to represent. For example, a survey unit with a weight of 100 represents 100 units in the population. Using number raised weights, each survey unit in a stratum is given the same weight. Number raised weights can only be used to weight simple random samples.

Producing estimates

The following table illustrates the ways in which Australian businesses contribute to the estimates in this release.

Summary of data sources 2017-18
Type of businessCompletely Enumerated (CE) StreamNumber Raised Estimation Stream
Sources of data*ABS SurveyABS Survey
The number of businesses1,462429,252
The number of businesses that are selected to provide data1,4628,576

*ABS Business Register used to identify businesses of each type
 

Completely Enumerated (CE) stream

The CE stream consisted of directly collected survey data for those units recorded on the ABS Business Register (ABSBR) as being economically significant units. 

Number raised estimation stream

The number raised estimation stream comprises directly collected data for those sampled units which are not in the CE stream and have turnover, in aggregate, above the bottom 2.5 percentile of BAS sales for that subdivision, or are identified as employing businesses (based on ATO information).

Estimates for each of the selected industries were produced by aggregating the contributing data streams.

Technical note - data quality

Reliability

The estimates in this release are based on information obtained from a sample survey, the Energy, Water and Environment Survey (EWES). 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

The majority of data contained in this release 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.

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 RSEs are available on request.

To illustrate, the estimate of electricity expenditure for Mining in 2017–18 is $2,638.1m. The RSE of this estimate as shown is 0.8%, giving a standard error of approximately $21.1m. Therefore, there are two chances in three that if all units had been included in the survey, a figure in the range of $2,617.0m to $2,659.2m 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 $2,595.9m to $2,680.3m. 

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 RSE 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. 

Relative Standard Errors

IndustryElectricityNatural gas
ExpenditureConsumptionExpenditureConsumption
%%%%
BMining0.80.70.60.5
CManufacturing1.61.11.21.2
DElectricity, gas, water and waste services1.81.52.22.7
EConstruction6.46.08.84.6
ITransport, postal and warehousing1.91.46.20.8

 

 

Non-sampling error

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 release 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.

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.

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.

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 release 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

Where businesses are unable to supply data for the 12 months ended 30 June 2018, an accounting period for which data can be provided is used. 

Businesses reporting for an accounting period other than the year ended 30 June can result in estimates different from what they would have been, had the business reported for an accounting period ended 30 June. 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

In the 2017–18 EWES, there was an 82.9% response rate from all businesses that were surveyed and found to be operating during the reference period. Data were imputed for the remaining surveyed businesses (17.1%). This imputation contributed 6.3% to the total purchases of energy and fuels for all selected industries.

Glossary

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Quality declaration

Institutional environment

Relevance

Timeliness

Accuracy

Coherence

Interpretability

Accessibility

Abbreviations

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