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4648.0.55.001 - Detailed Energy Statistics, Australia, 2001-02  
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 24/03/2004   
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INTRODUCTION

1. This publication presents results from the ABS Energy Survey 2001-02, and replaces the original publication, Energy Statistics, Australia (cat. no. 4649.0.55.001) which was released on 19 December 2003. This information will be reconciled and balanced by the Australian Bureau of Agricultural and Resource Economics (ABARE) and the ABS and published by ABARE in the form of energy balances and by ABS in the form of energy accounts (ABS catalogue no. 4604.0).


SCOPE AND COVERAGE

2. The scope of the ABS Energy Survey 2001-02 collection:

Includes:

  • entities with an Australian business number (ABN)
  • employing and non-employing businesses

Excludes:
  • agriculture (ANZSIC Subdivision 01)
  • water, air and space transport (ANZSIC Subdivisions 63 and 64)
  • private households employing staff (ANZSIC Subdivision 97)
  • foreign government representation (ANZSIC Class 8130)

3. Smaller businesses believed to be insignificant energy users, particularly in industries dominated by very large energy users, were excluded from coverage. Contributions to estimates at all levels from these businesses are not believed to be statistically significant.

4. Data at national and state levels as well as both industry (ANZSIC classification) and selected activity basis (International Energy Agency (IEA) classification) were collected.


METHODOLOGY

5. The collection consisted of seven tailored mail-out questionnaires. These forms were designed to be industry specific in order to help data providers provide the information in an accurate and timely fashion. Data for central government administration, commonwealth justice and defence (ANZSIC Classes 8111, parts of 8120 and 8200), were collected from an administrative by-product source (the Department of Industry, Tourism and Resources EDGAR database).

6. A census (of approximately 600 businesses) was considered the best means of collecting accurate data from:
  • petroleum refineries (ANZSIC Class 2510)
  • electricity generators, transmitters and distributors (ANZSIC Class 3610)
  • gas producers and pipeline operators (ANZSIC Classes 1200, 3620 and parts of 6501).

7. A sample of approximately 14,800 businesses was drawn from the remaining in-scope industries and weighted to produce fuel and energy use estimates for those industries.

8. When questionnaires were returned to the ABS they were checked for completeness and accuracy and, where possible, follow-up contact was made with data providers to resolve reporting problems. Where contact with the providers could not be made, missing items on incomplete questionnaires were imputed using average data from like businesses for which data were obtained.

9. Businesses were asked to apportion total fuel use across states for four broad categories of fuels (electricity, natural gas, petroleum products, and other fuels). All fuels reported by the business under each category were assigned to states in the same proportions.


REFERENCE PERIOD

10. Data contained in the tables of this publication relate to in-scope businesses operating in Australia at any time during the 12 month period ended June 2002.


BUSINESSES CEASED DURING THE YEAR

11. Contributions from businesses which ceased operations during the reference period have been included in the statistical output.


SAMPLING ERRORS

12. Since some estimates in this publication are based on information obtained from a sample of businesses drawn from the survey population, the estimates are subject to sampling variability. That is, they may differ from figures that would have been obtained if all businesses had been included in the survey. 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. 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 had been conducted, and approximately 19 chances in 20 that the difference will be less than two SEs.

13. Sampling variability (standard error) can be presented as a 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 potential inaccuracy in estimates due to sampling and avoids the need to refer to the size of the estimate. Note that electricity generation for sale, gas and petroleum production data are not subject to sampling variability as all businesses identified in these industries were surveyed.

14. The following table contains estimates of RSEs for the data in tables 5 and 6 of this publication (RSE annotations are described in 'Abbreviations and Symbols', below). The RSEs can be used to give an indication of the likely range of values around an estimate within which the true value lies. For example, the estimate of the amount of petrol used in the construction industry (table 5) is 794 ML; the corresponding estimated RSE is 9%. There are approximately 2 chances in 3 that the true amount of petrol used lies between 91% and 109% of the estimate (i.e. 723 ML and 865 ML). To increase the likelihood to 95% (or to produce 95% confidence bounds) this range should be expanded to 82% to 118% (i.e. 651 ML and 937 ML). Smaller RSEs will result in narrower bounds.
RSE Estimates for end-use fuel consumption, by industry, Australia and by state and territory 2001-02

Electricity
Natural Gas
Petrol
Diesel
Liquefied petroleum
gas (LPG)
Black coal
Bagasse
Wood, woodwaste
GWh
TJ
ML
ML
ML
kt
kt
kt

Agricultural services, forestry, fishing
17%
38%
21%
15%
33%
-
-
-
Mining
2%
1%
17%
4%
6%
7%
-
-
Manufacturing
3%
4%
7%
11%
6%
3%
6.7%
18%
Electricity, gas and water supply
14%
27%
10%
17%
5%
-
-
>85%
Construction
18%
57%
9%
16%
24%
-
-
>85%
Wholesale and retail trade
5%
34%
7%
13%
15%
-
-
>85%
Transport and storage
5%
1%
8%
6%
19%
36%
-
45%
Communication services
4%
3%
16%
28%
74%
-
-
>85%
Finance, insurance, property and business services
9%
11%
7%
38%
22%
-
-
-
Government administration and defence
3%
3%
2%
2%
5%
49%
-
-
Education
22%
8%
15%
32%
30%
0%
-
>85%
Health and community services
13%
11%
17%
32%
33%
0%
-
-
Other services
19%
22%
8%
13%
21%
-
-
>85%
Australia, All Industries
2.5%
2.7%
3.0%
3.5%
7.4%
2.0%
6.7%
17.6%

New South Wales
4%
12%
5%
9%
11%
9%
-
36%
Victoria
5%
7%
6%
5%
12%
-
-
-
Queensland
7%
6%
9%
8%
22%
4%
6.7%
2%
South Australia
5%
3%
17%
8%
39%
-
-
1%
Western Australia
8%
1%
11%
3%
13%
0%
-
>85%
Tasmania
4%
5%
16%
21%
27%
0%
-
-
Northern Territory
19%
2%
33%
9%
83%
-
-
-
Australian Capital Territory
5%
19%
19%
6%
42%
-
-
-

Note: Very high RSEs are poorly estimated and are denoted >85%


NON-SAMPLING ERRORS

15. Errors other than those due to sampling may occur because of deficiencies in the list of units from which the sample was selected, non-response, and imperfections in reporting by providers. Inaccuracies of this kind are referred to as non-sampling error, which may occur in any collection, whether it be a census or a sample. Every effort has been made to reduce non-sampling error to a minimum by careful design and testing of questionnaires, operating procedures and systems used to compile the statistics.

16. Individual fuel or energy use items were distributed across states based upon fuel categories (as discussed in Explanatory Notes paragraph 9). For businesses where the true distribution of use across states for a fuel differs greatly from the rest of the item's category, this method may have resulted in some misallocation of the fuel's use to states. Where this phenomenon has been identified in large contributing businesses, direct correction of state splits for specific items has been carried out. Care should be taken in interpreting state tables, particularly for the less commonly used fuels.


CAUTIONARY NOTE

17. Caution should be taken when comparing end-use and supply data as presented in this publication. No attempt has been made to balance the figures and scope and coverage issues will only partially explain the discrepancies. Fully balanced supply and use estimates will be published by ABARE and ABS during 2004.


RELATED PUBLICATIONS

18. ABS publications which may be of interest are outlined below. Please note, older publications may no longer be available through ABS bookshops but are available through ABS libraries. All publications released from 1998 onwards are available on this web site (charges apply).

Energy and Greenhouse Gas Emissions Accounts, Australia 1992-93 to 1997-98 (cat. no. 4604.0) - May 2001.

1986-87 National Energy Survey - Energy Consumption in Industry, Australia (cat. no. 8217.0) - June 1989.


RELEASE OF INFORMATION

19. As well as the statistics included in this publication, other additional unpublished data from the energy survey are available on request. For information on the provision of unpublished data please contact Bob Harrison on 02 6252 7369.


ACKNOWLEDGMENT

20. ABS publications 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.


ABBREVIATIONS AND SYMBOLS

ABAREAustralian Bureau of Agricultural and Resource Economics
ABSAustralian Bureau of Statistics
ANZSICAustralian and New Zealand Standard Industrial Classification, 1993 Edition (ABS cat. no. 1292.0)
ttonne
Llitre
WhWatt-hour, the basic measurement unit of electrical energy. Driving a car one kilometre uses around 1.2 kWh.
JJoule, a unit of work. Used to measure energy content. 3.6 MJ is equivalent to 1 kWh.
kkilo (103) or 1,000.
Mmega (106) or 1,000,000.
Gmega (109) or 1,000,000,000.
Ttera (1012) or 1,000,000,000,000.
Ppeta (1015) or 1,000,000,000,000,000.
^estimate has a relative standard error of between 10% and 25% and should be used with caution.
*estimate has a relative standard error of between 25% and 50% and should be used with caution. Data are subject to sampling variability too high for most practical purposes.
**estimate has a relative standard error greater than 50% and is considered too unreliable for general use.
..not applicable.
npnot available for publication, but included in totals.
_nil or rounded to zero (including null cells).
n.e.c.not elsewhere classified


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