In the previous blog post, I have discussed (in broad brushstrokes) how our understanding of the rationality and irrationality of human behaviour has changed over time. In this one, I will introduce a variety of regulatory interventions from around the world that build on this changing understanding of predictable (ir)rational behaviour.
Towards behavioural insights informed regulation
Inspired by the insights from the behavioural sciences, governments around the world have begun to incorporate these insights into regulatory interventions. When reading the examples that follow, it is essential to keep a few things in mind. First, that they are bound together by an ambition to address the predictable deviations from the neoclassical economy understanding of rational behaviour.
Second, some of the examples may feel all but novel. Regulatory interventions that are now sometimes branded as ‘behavioural science-informed’ have antecedents that go back in time to well before the rapid growth of the behavioural sciences. The provision of information to help consumers make better choices is one such example: many countries around the world, New Zealand included, have introduced mandatory product information disclosure well before the 1970s.
Third and final, the examples build on various political philosophies. I will discuss a number of these in the blog post on the ethical challenges of the use of behavioural insights in regulatory practice. But to give a few of the flavours available, some of the regulatory interventions seek to enhance people’s reflective decision making and help them make choices that serve their personal well-being but without limiting their options. Others seek to guide individuals towards making decisions that the regulator considers in their best interest, or in the best interest of society as a whole. Yet others seek to shape preferences or bias decisions in a certain direction.
One of the most discussed examples of behavioural insights informed regulation is the use of default rules or changing the workings of default rules. Default rules stipulate the choice outcome in situations where people decide not to actively choose. They are particularly helpful to overcome choice inertia, status quo bias and hyperbolic discounting.
An area where people show choice inertia and status quo bias is retirement savings. Rather than opting-in to a savings scheme or decide to actively and periodically put money on our savings account, we tend to push this decision into the future until it is too late. Seeking to overcome these problems, governments around the world have moved from such opting-in systems for voluntary saving schemes to opting-out systems.
A typical example is KiwiSaver in New Zealand. This is a voluntary long-term saving scheme set up by the New Zealand Government in 2007. In short, anyone aged 64 and under, who is entitled to live in New Zealand and who normally lives there, and who is employed is automatically enrolled in KiwiSaver and will contribute a percentage of their before-tax pay to the scheme. People can opt-out if they desire, however, giving them the freedom to choose another way of long-term saving or not save at all. The default savings are set to 3% of before-tax pay, but people can opt-in to higher levels of savings.
Changing the default from opting-in to opting-out has shown effective in retirements saving, organ donation, and environmental protection. Yet, default rules and changes of them may come with undesired effects also. In the KiwiSaver scheme, for example, it would probably be best for many members to switch their KiwiSaver provider or increase their contribution to the scheme—from 3% to a higher percentage. Yet, once defaulted into a specific setting people tend to stick to it (another example of status quo bias).
Disclosure of factual or comparative information
Another oft-discussed example is information disclosure. Here the idea is that if people are provided with factual or comparative information about the products they buy or use or the behaviour they (seek to) engage in, they will be able to make better-informed choices about these. Typical examples are the user manuals that come with new products, the food labels on produce and electronic equipment, and financial information disclosure. Information disclosure addresses some heuristics and biases we have, but also typical information asymmetries between producers and consumers.
Mandatory disclosure of financial risks (‘financiële bijsluiter’), the Netherlands, introduced in 2002.
Here an illustrative example comes from the Netherlands. As of 2002, providers of financial products there are required to provide consumers with information on the risks of their financial products. In 2006, legislation was changed to reduce the complexity of the information provided and to include a comparative label to give consumers a quick insight in risk of the product becoming a financial burden (see image above). The labels range from indicating very low to very high risk.
Reviews of the scholarly literature on the effectiveness of information disclosure show a bleak picture. There is no evidence that existing on-product warnings have a measurable impact on user behaviour and product safety. People often do not understand the information provided, find the amount of information provided too much to process, or fail to attend to information when it is unpleasant to deal with. It has been suggested that simplification of information, standardisation of information, increasing the saliency of information, and provision of comparative information could provide a solution. 
Yet, a core problem may be that we people are inherently slack when it comes to grasping the opportunity to make informed decisions—roughly 3% of people read privacy disclosures on websites before clicking ‘OK’. And to make things worse, we are more likely to be influenced by information that confirms our beliefs than by information that disconfirms it (confirmation bias).
Reminders and precommitment strategies
The use of reminders to improve regulatory outcomes has recently gained renewed interest from governments around the world. Reminders provide people with a cue to make a choice or complete a task that needs to be finalised. Reminders are particularly helpful to address procrastination. New Zealand citizens are familiar with receiving reminders, for example, to renew their vehicle licences from the New Zealand Transport Authority. Yet, not receiving a reminder does not release them from the responsibility to renew their licence. To prevent such situations to happen, car owners can now sign up for an application that will send a prompt when their licence is due to expire.
In 2017, the United Kingdom Behavioural Insights Team explored whether reminders could also be used to help students in further education to succeed in their courses. This has resulted in Promptable, an application that sends students text messages with helpful reminders, tips and motivation throughout the college year. To further increase their performance, students can nominate a ‘study supporter’ to also receive these messages. This may initiate regulator conservations between the students and their supporter. During the testing of Promptable, a 7% increase in attendance was measured in students who signed up to Promptable compared to those who were not.
Stepping up the idea of reminders another notch are precommitment strategies. A well-documented example is the Save More Tomorrow plan. It builds on the notion that people will find it more attractive to save in the future rather than in the now. To help people increase their savings, it, therefore, lets them precommit to an increase in their pension contributions not in the now, but at the time when they receive a pay-raise. As a result, people will not perceive a loss in because the increased pension contribution is less than their pay-raise. Since it has been rolled out as part of the USA Pension Protection Act in 2006, over 15 million Americans have committed to it.
In sum, precommitment strategies seek to address procrastination, status quo bias and hyperbolic discounting, but do so at a time when these are not at play yet. They are sometimes referred to as Ulysses Strategies, referring to the commitments Homer’s Ulysses made to not be tempted by the sirens.
Social proof heuristics
A final set of regulatory interventions I will discuss today built on social proof heuristics. Social proof heuristics work in, at least, two ways. First is that we humans seek norm conformity to be accepted or liked. Second is that when facing a novel or ambiguous situation, we humans tend to look at others to get cues about how to behave and then replicate the behaviour we see around us. Yet if we cannot see how others behave in a given setting, how can we then know what norm to conform to?
The classic social proof experiment was carried out by Opower, a USA based utility company. In 2008 it ran a randomised control trial to understand what would incentivise their clients most to reduce their energy consumption. The answer was to provide them with an easy to understand comparison of their energy consumption against that of their peers. In this case, their peers are the 100 nearest houses of similar size. This easy to understand information is as simple as printing a ‘smiley face’ on the energy bills of those who have average or below average consumption, and a ‘frowny face’ on the energy bills of those who consume more than average.
This low-cost and low-intrusive intervention resulted in a reduction of energy consumption of 2%, particularly because those who consumed more than their peers on average reduced their consumption. While this does not sound like a lot, it should be stressed that those who reduced their energy consumption did this without being given any signal to do so. Since, governments in collaboration with utilities around the world have replicated this experiment, often receiving related outcomes.
The power of social proof heuristics seems to hold around the globe: no-one likes to be below average. Social proof heuristics may backfire, however. People who do better than average (for example they have lower than average energy consumption) may feel entitled to use their fair share or feel they are doing more than necessary and regress to the average (for example by using more energy than before).
To not make this blog post too lengthy, I had to axe many of the examples I would have liked to discuss. I strongly recommend reading the following OECD reports if you are interested in more examples:
- Behavioural Insights and Public Policy (2017)
- The Use of Behavioural Insights in Consumer Policy (2017)
- The Application of Behavioural Insights into Financial Literacy and Investor Education Programmes and Initiatives (2018)
 Baldwin, R. (2014). From Regulation to Behaviour Change: Giving Nudge the Third Degree. Modern Law Review, 77(6), 831-857.
 Johnson, E., & Goldstein, D. (2003). Do defaults save lives. Science, 302(5649), 1338-1339.
 Willis, L. (2013). When Nudges Fail: Slippery Defaults. University of Chicago Law Review, 80(3), 1155-1229.
 Loewenstein, G., Sunstein, C. R., & Golman, R. (2014). Disclosure: Psychology Changes Everything. Annual Review of Economics, Vol 6, 6, 391-419.
 Benartzi, S. (2012). Save More Tomorrow. New York: Penguin Group.
 Cooney, K. (2011). Evaluation Report: OPOWER SMUD Pilot, Year 2. Chicago: Navigant Consulting.
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