QUALITY DECLARATION - SUMMARY
The statistics presented in this release were derived using data collected directly by the Australian Bureau of Statistics (ABS) under the authority of the Census and Statistics Act 1905.
Please refer to ABS Institutional Environment for more information about the institutional environment of the ABS, including its legislative obligations, financing and governance arrangements and mechanisms for scrutiny of ABS
operations. For more information about the institutional environment of the ATO, please refer to Part 3 Management and accountability in the Commissioner of Taxation Annual Report 2011–12.
The Construction Industry Survey (CIS) collects data required by both internal (to the ABS) and external parties. Key external users are the Commonwealth and State/Territory government departments, peak bodies and academics/researchers. In particular, information collected under this survey will enable government bodies and industry to support submissions and proposals on a range of policy issues.
Internal users of the data require detailed economic information that can be compared both across time and against industries other than the construction industry. In particular, data from this survey will be used in ABS publications such as the Australian National Accounts (Catalogue No. 5206.0).
The key objectives of the Construction Industry Survey are:
- Measure the size and structure of the industry
- Measure detailed items of income and expense
- Enable comparisons between States/Territories
- Enable comparison of the industry to other industries.
The businesses that contribute to the statistics in this publication are classified:
- by institutional sector, in accordance with the Standard Institutional Sector Classification of Australia (SISCA), which is detailed in Standard Economic Sector Classifications of Australia (SESCA), 2008 (cat. no. 1218.0)
- by industry, in accordance with the Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006 edition (cat. no. 1292.0).
The scope for the survey is all operating employing and non-employing private and public trading sector businesses classified to ANZSIC 2006 Division E (Construction). The scope excluded activity undertaken by private individuals for their own use and general government organisations.
Although the period covered by the estimates was, in general, the twelve months ended 30 June, some businesses were unable to supply information on this basis. In such cases an accounting period for which data could be provided was used for data other than employment.
The collection is conducted on an irregular basis with estimates generally available within twelve months of the reference period to which they relate. For the 2011–12 reference period, questionnaires were despatched by ABS in August 2012. The estimates are scheduled for release in June 2013, twelve months after the end of the reference period.
|The ABS aims to produce high quality data from its industry collections while minimising the reporting burden on businesses. To achieve this, extensive effort is put into survey and questionnaire design, collection procedures and processing. The 2011–12 survey used generalised regression estimation. Generalised regression estimation is a form of ratio estimation which makes use of auxiliary data items which are strongly correlated with key data items directly collected by the ABS from businesses. The auxiliary variables used in this survey were turnover and wages from data sourced from the ATO. Use of this methodology allowed high quality statistics to be produced from a sample of 3,524 businesses classified to the Construction Industry.|
Two types of error can occur in estimates that are based on a sample survey: sampling error and non-sampling error.
Sampling error occurs when a sample, rather than the entire population, is surveyed. It reflects the difference between estimates based on a sample and those that would have been obtained had a census been conducted. One measure of this difference is the standard error. 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 businesses had been included in the survey, and about nineteen chances in twenty that the difference will be less than two standard errors.
Another measure of sampling error is the relative standard error, which is obtained by expressing the standard error as a percentage of the estimate to which it refers. The relative standard error is a useful measure in that it provides an immediate indication of the sampling error in percentage terms, and this avoids the need to refer also to the size of the estimate. Relative standard errors of key estimates are available in a Technical Note on Data quality in Private Sector Construction Industry, Australia, 2011–12 (cat no. 8772.0).
Non-sampling error arises from inaccuracies in collecting, recording and processing the data. Every effort was made to minimise reporting error, by the careful design of questionnaires, intensive training of survey analysts and efficient data processing procedures. 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.
Previous Private Sector Construction Industry Surveys were conducted by the ABS for the 1996–97 and 2002–03 reference periods. While the ABS seeks to maximise consistency and comparability over time by minimising changes to the survey, sound survey practice requires ongoing development to maintain the integrity of the data, their relevance to the changing needs of users and the efficiency of the survey. There have been substantial changes in scope and methodology between the surveys, so users should exercise caution when making historical comparisons.
These changes include:
- major changes between the 1993 and 2006 editions of ANZSIC which affected construction sectors.
- the introduction of an improved survey methodology, that made far greater use of Australian Taxation Office data in the survey design for Construction Industry.
Key annual industry data for ANZSIC 2006 Subdivisions 30 Building Construction, 31 Heavy and Civil Engineering Construction and 32 Construction Services are published in Australian Industry
(cat. no. 8155.0). There are important differences between statistics published in Australian Industry
and Private Sector Construction Industry
publications. Construction Industry Survey was partially integrated with Division E (Construction) in Australian Industry for 2011-12. Partial integration means that the different sample sizes have been used for producing the Construction Survey and Australian Industry estimates. Different sample sizes have resulted in minor variations between estimates due to presence of sampling error. Users should exercise caution when making comparisons between the two sets of estimates.
Estimates released in Private Sector Construction Industry, Australia, 2011–12
are available as original series only,
and are neither seasonally nor trend adjusted.
Although financial estimates in this release relate to the full twelve months, employment estimates relate to the last pay period ending in June of the given year.
Further information about terminology and other technical aspects associated with these statistics can be found in the publication Private Sector Construction Industry, Australia, 2011–12
(cat. no. 8772.0), which contains detailed Explanatory Notes
, a Technical Note
on Estimation methodology, a Technical Note
on Data quality and
Data from the 2011–12 Private Sector Construction Industry Survey are available in a variety of formats. The formats available free of charge on the ABS website are:
- main features, which include key findings commentary
- a PDF version of the publication
- spreadsheets which contain all the tables presented in the pdf version of the publication, together with additional tables.
This page last updated 26 June 2013