This Basic Confidentialised Unit Record File (CURF) provides information from both the monthly Labour Force Survey and the related Employee Earnings, Benefits and Trade Union Membership supplementary survey.

Detailed labour force and demographic characteristics for the civilian population aged 15 years and over are included. In addition, for employees, data is provided on earnings, leave entitlements, superannuation, entitlement to other benefits and trade union membership.

This CURF is available on CD-ROM and via the Australian Bureau of Statistics (ABS) Remote Access Data Laboratory (RADL). The CD-ROM allows users to tabulate, manipulate and analyse data to their individual specifications. The RADL is accessible for authorised users via the ABS web site and enables the ABS to make more detailed microdata available than on CD-ROM, while still maintaining the confidentiality of ABS data providers.

Steps to confidentialise the dataset are taken to ensure the integrity of data, optimise its content and maintain confidentiality of respondents. They include removing any information that might uniquely identify an individual, reducing the level of detail for some items and collapsing some categories.

This Expanded Confidentialised Unit Record File (CURF) provides information from both the monthly Labour Force Survey and the related Employee Earnings, Benefits and Trade Union Membership supplementary survey in more detail.

Detailed labour force and demographic characteristics for the civilian population aged 15 years and over are included. In addition, for employees, data is provided on earnings, leave entitlements, superannuation, entitlement to other benefits and trade union membership.

The Expanded CURF is available via RADL only. The RADL is accessible for authorised users via the ABS web site and enables the ABS to make more detailed microdata available than on CD-ROM, while still maintaining the confidentiality of ABS data providers.

Steps to confidentialise the dataset are taken to ensure the integrity of data, optimise its content and maintain confidentiality of respondents. They include removing any information that might uniquely identify an individual, reducing the level of detail for some items and collapsing some categories.