When we look at Federal Budgets, it is hard to not get overwhelmed by the sheer scale of some of the announcements. A few billion dollars for an inland rail project here, a couple of more billion dollars for a new airport and related roads there. That’s not to mention changes to school funding models in the tens of billions or taxes on banks estimated to bring in around $6 billion. The numbers are eye watering.
Often though, it is some of the smaller numbers that have the potential to have the largest long term impacts. In terms of evidence-based policy, there were three items in the recently released 2017/18 Budget that may drastically change the way in which policy is delivered in Australia. The first relates to data access and data sharing; the second to the use of more scientifically sound behavioural models in government decision making, and the third to a greater use of evaluations and evidence in policies related to Aboriginal and Torres Strait Islander Australians.
Beginning with data access and data sharing, it is important to go back in time a little bit, to March 2016. Before his first budget, Treasurer Morrison asked the Productivity Commission to undertake a ‘broad ranging investigation into the benefits and costs of options for improving availability and use of data.’ The Productivity Commission provided a draft report to the Government on the 3 November 2016 and a final report on the 31 March this year. Perhaps not coincidentally, the final report was released to the public just a day before the budget (8 May).
There were many recommendations in the Productivity Commission’s draft and final reports, both small and large. But the key ones related to a new Data Sharing and Release Act, a National Data Custodian to guide and monitor new access and use arrangements, as well as a new Comprehensive Right for consumers that would ‘give individuals and small/medium businesses opportunities for active use of their own data.’
The Budget does not contain a complete response to the Productivity Commission’s final report. However, there is funding in the Budget that goes part of the way, through the funding of the Data Availability and Use Taskforce, as well as the creation of the ‘Data Integration Partnership of Australia.’ This will, according to Finance Minister Mathias Cormann in Budget Paper No. 4 be through ‘integrating data from across government, and providing access via a single entry point [and] will reduce duplication, encourage efficiency, and lead to long-term reform in data collection and use.’
The details, at this stage, are unclear. However, if appropriate privacy controls are in place and researchers from both within and outside of government are substantially better able to access individual-level data created through government activities, then this will help us know how specific groups of the population are faring; whether there are current policies that might be having negative effects on outcomes or are being provided in a non-cost-effective way; and whether there are demonstrably successful programs that could be enhanced or expanded.
Around the same time as the Productivity Commission began its enquiry into data access, a new unit was created within the Department of Prime Minister and Cabinet. Starting in February 2016 and known as the Behavioural Economics Team of the Australian Government (BETA), this is the ‘Australian Government’s first central unit applying behavioural economics to improve public policy.’ It follows similar units around the world (most famously, the Behavioural Insights Team in the UK Cabinet Office) and has a strong focus on using Randomised Controlled Trials (or RCTs) to test small and large changes to public policy that build on principles developed within the fields of Behavioural Economics and Social Psychology.
The Finance Minister stated that funding will be provided to ‘drive further uptake of Behavioural Economics, to improve the development of evidence-based policy, and to support digital skill training for public sector staff.’ We often associate Behavioural Economics with small tweaks to policy or service delivery (like the wording on a form, or the sending of a text message), and these are important. However, if government uses more accurate models of human decision making across all policy decisions, then this has the potential to reduce unintended negative consequences and identify effective policy solutions.
One area of policy where there have been severe negative consequences of many government decisions and a dearth of effective policy solutions is Indigenous policy. The lack of progress in meeting the government’s own Closing the Gap targets has been clear for years and the Productivity Commission highlighted the almost complete lack of quality evaluations of Indigenous-specific policies in their most recent Overcoming Indigenous Disadvantage report.
The 2017-18 Budget Paper 2 announced that ‘Government will provide $52.9 million over four years from 2017-18 to implement a whole-of-government research and evaluation strategy for policies and programs affecting Indigenous Australians, including the establishment of an Indigenous Research Fund.’ In delivering on this, it is important that Indigenous participation and control of data be respected and resourced. Plus, we shouldn’t assume that Indigenous policy is the only area in Australia where programs aren’t effectively evaluated. Nonetheless, there is specific evidence that suggests that progress in this area isn’t anywhere near as fast as it should be, and a greater investment in identifying why that is the case and how that can be changed could only be seen as a good thing.
Full disclosure is important, and as a research organisation it is possible that the ANU may directly benefit from these announcements. Despite being in the hundreds of millions only (and yes, that is still a massive amount of money), what ties these three areas of funding together we might hope is a focus on developing and applying rigorous, empirical evidence to the development of government policy.
A cynic might say that a solid evidence-base does not guarantee evidence-based policy. And that is certainly true. For example, in the same budget that additional funding was announced for evaluating Indigenous policies, a large amount of money was also allocated to extend both the Cashless Debit Card as well as Income Management, despite evaluations of these programs showing very mixed results, at best. For example, the review of the Cashless Debit Card found that ‘three-quarters of all participants said that the CDC has made no positive change to their lives and almost half of all participants said it had made their lives worse; only one-fifth of participants said it had made their lives better.’
The reality is though that research in Australia has been continuously hamstrung by the lack of access to high quality data, and a general unwillingness to rigorously trial and evaluate policy. If done well, the three announcements on data access and sharing, investments in behavioural economics and evaluation of Indigenous policies could significantly change that.
Recent Comments