3418.0 - Personal Income of Migrants, Australia, 2011-12 Quality Declaration 
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 27/10/2016   
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IN THIS ISSUE

The 2011-12 Personal Income Tax and Migrants Integrated Dataset (PITMID) provides estimates of the personal income of migrants and improves and expands the range of official statistics to support government policy making, program management and service delivery.

It does this by integrating migrant data from two non-ABS datasets, the Australian Taxation Office (ATO) Personal Income Tax (PIT) records and the Department of Social Services (DSS) Settlement Database (SDB) to create a new dataset for statistical and research purposes. This enables the ABS to enhance the value of Australian Government administrative data and leverage more information from the combination of individual dataset than is available from the separate datasets.

The ABS partners in this project (ATO, DSS and Department of Immigration and Border Protection (DIBP)) recognise the value of the PITMID and support the continuation of this project. It is expected that the broad approach used here will be adopted to enable future data linkage on an annual basis.

Information about this project is included on the Project Register of Data Integration Projects on the National Statistical Service (NSS) website.

Estimates on the personal income of migrants have previously been output for the 2009-10 and 2010-11 financial years. A detailed assessment regarding the quality of the linkage can be found in Research Paper: Feasibility Study of Linking Migrant Settlement Records to Personal Income Tax Data, Aug 2014 (cat. no. 1351.0.55.051).

The linkage process used for the 2011-12 PITMID was modified from the previous approach and has been outlined in the Research Paper: Personal Income Tax and Migrants Integrated Dataset (PITMID) 2011-12 Quality Assessment, Oct 2016 (cat. no. 1351.0.55.060). The new linking methodology utilises a Statistical Analysis Software (SAS) macro known as the Deterministic linking Macro (D-MAC) for a purely deterministic approach. The D-MAC links two datasets using a simple set of rules and then outputs linked record pairs with a calculated measure of accuracy. The linking results generated by D-MAC showed almost 95% of the SDB records either linked to the same PIT record (as the previous linking) or did not link to a PIT record. D-MAC was found to be much quicker to administer and produced high quality results, while enabling comparison between the annual series. The study describes the project, the linking methodology and evaluates the results. It provides a good background and context for the statistical information provided in this publication.


INQUIRIES

For further information about these and related statistics, contact the National Information and Referral Service on 1300 135 070.