In the second part of the Young Fabians Economy & Finance Network Coronavirus Economics blog series, Dom Shaw assesses the impact of behavioural economics throughout the pandemic.
The coronavirus pandemic was an unprecedented challenge for governments across the globe. Conventional thinking alone was not going to be sufficient in dealing with the unparalleled problems of the pandemic. So, step forward behavioural economics.
Let’s first define behavioural economics, and then discuss whether its methods and tools were powerful and effective to help deal with the pandemic. Behavioural economics combines psychology, economics, and neuroscience to better understand why we make the decisions we do and how we can make better, more informed decisions.
During the pandemic, decisions decided lives. So when 681 behavioural scientists penned an open letter to the UK Government questioning its initial coronavirus response, you have to question whether the government were accurately reflecting behavioural insights. On 16th March 2020, when 1400 cases had been detected, the government had still not enacted strict social distancing policies, despite different approaches in other countries. The government’s reason was that starting lockdowns too early would lead to ‘behavioural fatigue’. In other words, people would quickly get bored of being in lockdown and then break the rules before the peak of the pandemic. Behavioural scientists questioned the governments understanding of behavioural economics to justify that decision - there was a lack of justification and a lack of research for it. Should behavioural fatigue have been the key consideration in determining lockdowns anyway? Here, the government rightly tried to use a scientific approach to policy making but got it horribly wrong.
Or perhaps, I am just guilty of hindsight bias. Being aware of biases can help inform policy via nudges. These are eleven key biases and behavioural concepts that were at play during the pandemic:
- Overconfidence and optimism bias – underestimating the risk of the virus, and assuming something risky won't happen to me.
- Zero-risk bias - people want some certainty, despite uncertain times. Hence, people try and reduce risk to zero. For example, when people panic bought toilet roles. You won’t run out of toilet roll if you buy 100 rolls. However, this created ‘tragedy of the commons’ issues, where it may have been good for you personally to have surplus toilet roll, but not good the whole society. However, panic buying may not be irrational if people are very risk averse.
- Default/ status quo bias – it’s hard to change behaviour quickly. For example, people continued to shake hands after it was advised against and were slow to adopt more regular hand-washing.
- Loss aversion - lost freedom of movement.
- Normalcy/ ostrich effect - pretending things haven’t changed.
- One-model thinking bias (particularly relevant for policy making) – policymakers were at times too focused on one solution to a problem (and forgetting other important policy areas). The world is complex. There is rarely one solution to problems - one-shot interventions are often not realistic.
- Herding - for example toilet rolls, but also some vaccine herding - herd immunity.
- Myopia - we were short-sighted & overconfident that crisis would be over quickly!
- Altruism, self-sacrifice & positive reciprocity - everyone in it together. We are willing to give up some of our freedoms for other people’s health.
- Social norms - being pro-social. Going beyond our narrow self-interest and understanding that if society as a whole is doing something (e.g. observing lockdowns) so should you. We are heavily influenced by how other people behave.
- Recency effect – the tendency to remember more clearly views and experiences that occurred more recently than those that came first. People can be absent-minded and need reminders, e.g. TV adverts to stay at home and frequently reminding people what the new lockdown measures are.
These behavioural concepts have been very important. They have combated issues such as vaccine hesitancy, and incentivised people to behave in certain ways. For example, a bar in Tel Aviv offered free drinks to those who came to get vaccinated. Other behavioural insights helped with designing nudges, such as:
- Shops with arrows & floor signs to mark distance between customers
- Placing hand sanitiser visibly in shop entrances
- One-way traffic on pavements to avoid people crossing paths
- Singing Happy Birthday to ensure we wash our hands for long enough
- Some hard nudges (e.g. fines)
To conclude, I’ll finish on a positive note. Or rather, positive messaging. Communication was a vital tool during the pandemic. It was found that during the pandemic positive messaging was a driving factor in increasing mask compliance. People lost interest in overly negative messages and paid more attention to more optimistic news.
We learnt a lot from the pandemic, and we should now be in a better position to deal with future crises of a similar nature. Policy makers and governments are now better equipped and aware of the behavioural insights needed to deal with pandemics but must also ensure conventional thinking is considered alongside it. We should not wait until the next crisis to ensure this thinking is at the forefront of policy makers’ minds.
Dom is the Chair of the Young Fabians Economy and Finance Network. He is an economist and has previously worked at the Bank of England. He tweets at @DomJAShaw.