When behavioural economics meets randomised control trials: Examples from Canadian public policy

Robert French and Philip Oreopoulos have a nice post on the topic.

They point to how Ontario in Canada has started a behavioral unit which is slowly moving along on behavioral insights:

Although initially slow to warm to the trend, Canada is witnessing behavioural economics play an increasingly important role in its policy formulation (French and Oreopoulos, forthcoming). Agencies promoting the application of behavioural economics to public policy have now been established at both the federal and provincial level, covering a broad array of policy issues. A particularly notable feature of these agencies is the emphasis they place on rigorously testing their prospective behavioural interventions through randomised control trials. While not unique to the Canadian agencies, we believe this feature is worth highlighting. Many of the country’s behavioural interventions have occurred within an existing policy framework in which small tweaks to the status quo – influenced by behavioural economics – have had a marked impact on policy outcomes. Using randomised control trials to determine how best to tweak existing policy has been critical to the success of these interventions to date.3

One of the first explicit Canadian behavioural interventions to this effect involved promoting organ donation registration rates in the Province of Ontario. While much has been written about the power of default options affecting organ donation registration rates (e.g. Li et al. 2013, Johnson and Goldstein 2003), changing Ontario’s current opt-out default policy to one of presumed consent remains publicly unappealing.4,5 Instead, the province sought to promote organ donation registration through a behavioural intervention that operated within the province’s opt-out default policy framework. The intervention was designed with assistance from the province’s recently established Behavioural Insights Unit (BIU) – a government agency established to design and test behavioural interventions in the province.

Currently, when conducting a health card, driver’s licence, or photo card transaction at a provincial service-centre, Ontarians are asked by customer service representatives whether they would like to register as a donor and are provided with a registration form. The BIU’s intervention sought to raise registration rates by increasing the salience and simplicity of the registration process through altering the content of the registration form as well as the time at which potential donors received the form during their visit to a provincial service-centre. The intervention also included variations in nudge statements present on the registrations forms.6 This simple trial was considered a remarkable success by the Ontario government, as organ donation registration rates increased by up to 143% during the trial (Treasury Board Secretariat 2016).

In another experiment, they have shifted the signature box in income tax from bottom to top. This is being done in a randomised setting thus mixing the two fields:

The BIU’s attempt to mimic a randomised control trial while testing a behaviourally based intervention within an existing policy framework is emblematic of many other recent initiatives in Canadian public policy. One particularly interesting example involves Canada’s Revenue Agency (CRA) testing the impact of moving the signature box on personal income tax returns – where filers agree in writing that information provided is complete and accurate – to the beginning of the form. This intervention – based upon previous research suggesting that people are more truthful after they have been prompted to think about honesty (e.g. Shu et al. 2012) – was conducted in two Canadian cities wherein paper tax returns containing the altered signature block were distributed among some of its citizens. The CRA is currently comparing the amount of income reported (especially in areas more susceptible to dishonest disclosure) between the treatment and control groups, and pending differences between the two groups may roll out this intervention more extensively in the future. This example is especially interesting since it is a quintessential example of how combining insights from behavioural economics and rigorously testing such insights can affect dramatic change through public policy. Even a marginal difference in reported income across the two groups could garner substantial savings for the government if this costless intervention were implemented nation-wide.

Nice bit.

 

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