This is Lateral Economics’ third post regarding the Valuing the Census study it is conducting for the ABS.
By combining Census data with Australian government administrative data, the ABS has found more highly educated people have longer working lives and retire later.
This finding may prove useful in projecting future retirement patterns and government payments and revenues, particularly given younger generations have higher levels of educational attainment and may retire later on average than older generations.
In addition to discovering retirement ages are much later for those people with a higher level of education, the ABS has uncovered some other fascinating findings through the Commonwealth government’s Multi-Agency Data Integration Project.
Analysis of data compiled by the ABS has discovered there is much stronger demand for Medicare services among low-income households, as opposed to higher-earners (see figure below).
It has also identified substantial disparities in Medicare benefits paid to aged pensioners in metropolitan areas, compared with their rural and regional counterparts.
Meanwhile, households with lower rates of employment and a greater reliance on government benefits have a higher risk of homelessness for one of their members.
The findings mentioned above were only possible as a result of combining Census data with Australian government administrative data.
The ABS used Census data in combination with administrative data sets together to create an integrated data set incorporating Census, Medicare, social security, and tax data.
The Census has been invaluable in this regard, as it contributes a richness of information not available from other administrative datasets.
It needs to be emphasised that the ABS abides by strict rules to protect people’s privacy and matched data are de-identified, with names removed.
The ABS is using the Five Safes Framework to enable greater use of our valuable microdata, building on the ABS’ strong data secrecy legislative requirements, statistical disclosure controls, and organisational expertise and integrity.
If you are interested in finding out more, have a look at the ABS’s information about privacy, secrecy and information security.
The goal of the Multi-Agency Data Integration Project is ultimately to inform policy advice and development.
This data set has been applied in a variety of research projects. So far, four case studies have been published from the project, on the topics of the findings mentioned above, which are available from the ABS website.
Issues for discussion
The case studies on retirement, Medicare benefits, and homelessness illustrate the wide variety of policy, program and service issues which can be informed by analysis of the Census-enabled integrated data set.
Another example illustrating the insights gained from linking Census data to other key data sets is the Understanding Migrant Outcomes project.
This project contributes significantly to the pool of migrant data available in Australia to assist in the development and evaluation of migrant programs and support services now and into the future.
For example, the integrated dataset enables variations in labour market and other socioeconomic outcomes for different migrant groups to be more readily identified and understood.
The analysis of the Census-enabled integrated data set could significantly improve outcomes, particularly if it can allow better targeting of policies, programs and services to local areas.
That said, the process by which better data generates better policy, programs and services is not guaranteed, which is something we need to consider in estimating the magnitude of expected future benefits.
Finally, we’d be very interested in your views on the issues raised in this post. Please offer any comments you think relevant to our project. But questions we’d love your input on include:
- Are the findings reported so far in the ABS’s case studies relevant and applicable to policy and if so please give us details?
- In what ways does the integrated data set allow analysis which is superior to what could be done with existing survey data?
- What other policy issues could be analysed using the Census-enabled integrated data set?
Please respond by commenting on this post or, if you’d prefer, by emailing us at [email protected] Here are links to our two previous posts on the study: