{"id":8214,"date":"2020-06-03T00:00:00","date_gmt":"2020-06-02T23:00:00","guid":{"rendered":"http:\/\/www.economicsobservatory.com\/question\/risk-time-covid-19-what-do-we-know-and-not-know"},"modified":"2022-11-08T14:12:34","modified_gmt":"2022-11-08T14:12:34","slug":"risk-time-covid-19-what-do-we-know-and-not-know","status":"publish","type":"question","link":"https:\/\/www.economicsobservatory.com\/test\/risk-time-covid-19-what-do-we-know-and-not-know","title":{"rendered":"Risk in the time of Covid-19: what do we know and not know?"},"content":{"rendered":"

Our experience of \u2018risk\u2019 is changing dramatically. Decisions that we never considered risky before the coronavirus have suddenly entered the forefront of our daily lives: If my mask is in the wash, should I still go to the supermarket? Should I take a crowded bus or pay extra for an Uber? Should I still look to buy a house if I may face redundancy?<\/em><\/p>\n

The novel conditions under which people are now weighing decisions make predicting behaviour particularly challenging, but we are not starting from scratch. Risk has intrigued economists and psychologists for decades \u2013 and we can learn from past crises to help us understand and, in some cases, approximate the impact of choices that people will make today.<\/p>\n

Unprecedented times<\/h3>\n

While Covid-19 has introduced uncertainty in nearly all dimensions of our lives, this is not the first time in human history that we have faced (and adapted to) exceptional circumstances of risk and uncertainty. Economists crucially distinguish between the two: risk is the measure for an event for which we know <\/em>the probability associated with the outcomes; and uncertainty relates to those events for which we do not<\/em> know the probabilities of the risky outcomes.<\/p>\n

For example, when throwing fair dice, we know the probability of any number coming up is one in six. In the case of Covid-19, in contrast, we do not know the probabilities of the possible outcomes and, as a result, we are living under several sources of major uncertainty. Simply put, we don\u2019t know whether the changes we are experiencing are temporary or an intractable start of a new world.<\/p>\n

This is compounded by the fact that we also find ourselves traversing unfamiliar conditions of social isolation and living in fear of an invisible force that may make us sick. Even more pressingly, we are facing these conditions at the same time<\/em>. What does this mean for decision-making in today\u2019s world?<\/p>\n

At this stage, \u2018unprecedented\u2019 is the only apparent way to describe the current environment and its effects. But to navigate these compounding factors of uncertainty and risk, we must ask: what other types of risk are similar to those we are experiencing; and does history provide clues to navigating the current global uncertainty?<\/p>\n

Many <\/a>have made comparisons <\/a>to historical examples of global pandemics, such as the Spanish flu in 1918, which killed approximately 50 million people worldwide. Unfortunately, there are no reliable data for the impact on risk-taking at that time and, given that the Spanish flu occurred at the end of the First World War, today\u2019s choices are wildly different. Where we can draw lessons are the effects of other, more widely understood decisions made under uncertainty.<\/p>\n

\n

Related question:<\/strong>\u00a0Does the Spanish flu\u00a0offer lessons in how to tackle a pandemic?<\/a><\/p>\n<\/blockquote>\n

What can research tell us?<\/h3>\n

A stream of economic research looks at a type of uncertainty known as \u2018background risk\u2019 that cannot be avoided, insured against or diversified away (Eeckhoudt et al<\/a>, 1996; Harrison et al<\/a>, 2007).<\/p>\n

For many, a sudden change in income is a prime example, but Covid-19 also falls into this category. Background uncertainty is out of our immediate control, so it differs from risk experienced in \u2018normal\u2019 situations where we have a degree of active choice<\/em> (\u2018foreground risk\u2019) such as selecting one option over another in playing a lottery or choosing a financial product.<\/p>\n

In the financial domain, these two forms of risk are sometimes also referred to either as endogenous <\/em>(that is, interactions of options within a set of choices) or exogenous <\/em>(that is, external shocks: Kimball<\/a>, 1990; Guiso and Paiella<\/a>, 2008).<\/p>\n

For example, research suggests that financial background uncertainty may result in a reduction in risky asset allocation in order to reduce overall risk exposure (Kimball<\/a>, 1990). This is in line with what is sometimes called \u2018countercyclical risk aversion\u2019 (Guiso et a<\/a>l, 2013; Cohn et al<\/a>, 2015). Covid-19 has proved devastating to financial markets worldwide and these types of exogenous shocks may currently be at play.<\/p>\n

\n

Related question: <\/strong>What explains stock market reactions to the pandemic?<\/a><\/p>\n<\/blockquote>\n

How does this generalise to non-financial risk-taking?<\/h3>\n

While background uncertainty is most commonly cited in financial contexts, we may look to understand how background uncertainty can affect other risk-taking domains. More general examples of effects of non-financial exogenous shocks can be found in situations such as natural disasters, wars and terrorist attacks.<\/p>\n

Some studies have measured risk-taking after a natural disaster or under exposure to a major life threat by looking at individual choices in lottery games with real monetary wins. Some of the evidence is seemingly counterintuitive. Certain studies suggest an increase <\/em>in risk-taking after a natural disaster. For example, evacuees from Hurricane Katrina (Eckel et al<\/a>, 2009), below-poverty-line households in Peru exposed to volcanic threat (Bchir and Willinger<\/a>, 2013) and flooded households in Pakistan and Australia (Page et al<\/a>, 2014; Said et al<\/a>, 2015) all appeared to be more risk-seeking in lottery gambles.<\/p>\n

The behavioural mechanism underlying such reactions is unclear and, to the best of our knowledge, has never been fully tested. One potential hypothesis, however, is that the presence of massive uncertainty (the disaster) \u2018trumps\u2019 seemingly smaller, more familiar sources of risk (the lottery), which become less salient, less relevant and are perceived as less risky.<\/p>\n

Examples of seemingly counterintuitive reactions can be found in non-financial domains: soldiers in a war possibly don\u2019t perceive the risks of smoking, taking drugs or having unprotected sex in the face of great harm or death. Israeli adolescents exposed to continuous threats of terrorist attacks, for example, reported higher <\/em>levels of risk-taking behaviours such as drinking alcohol or being involved in a fight (Pat-Horenczyk et al<\/a>, 2007).<\/p>\n

This line of inquiry suggests that greater uncertainty diminishes the perceived smaller risk in comparison. It suggests that risk-taking behaviour may actually increase <\/em>in the period of and following Covid-19.<\/p>\n

Other studies of non-financial exogenous shocks come to conclusions more aligned with exogenous financial risks. Reduced risk-taking in lottery gambles was observed following a tsunami in Thailand (Cassar et al<\/a>, 2017) and an earthquake or flood in Indonesia (Cameron and Shah<\/a>, 2015).<\/p>\n

This has been interpreted to mean that major background uncertainty induces compensatory behaviour, leading to a reduction <\/em>in non-essential risk-taking activities, perhaps in an increased effort to protect ourselves. This hypothesis assumes \u2018risk homeostasis\u2019 where, being already exposed to the major Covid-19 uncertainty, we reduce our other risk-taking activities, such as smoking or climbing, in order to protect ourselves.<\/p>\n

In principle, risk homeostasis or \u2018risk compensation\u2019 can also \u2018swing\u2019 our behaviour in the opposite direction: for example, taking our multivitamins warrants us having a rich dessert, and wearing a seatbelt means that we can drive faster. More currently, wearing a face mask may make us feel safe to see friends, and without our weekly recreational climb, dark web purchasing may seem all the more attractive.<\/p>\n

Although both these hypotheses are plausible \u2013 and the idea of risk compensation has often been proposed in economics and psychology \u2013 evidence to date is mixed, to say the least (Houston and Richardson<\/a>, 2007). Similarly, the \u2018large uncertainty trumps small risks\u2019 hypothesis has not yet been systematically validated. This makes offering any more than theorised speculation on the direction of behaviour in times of Covid-19 uncertainty difficult.<\/p>\n

How reliable is the evidence?<\/h3>\n

Generally, we should not forget that most of the above studies rely on evidence from risk-taking tasks in the form of lottery games with real monetary payments, which have limitations. These games typically have very small stakes, and we know that risk-taking in the face of larger stakes can differ significantly (Holt and Laury<\/a>, 2002; Fehr-Duda et al<\/a>, 2010).<\/p>\n

Other limitations include the fact that pre-registration and replication is still uncommon in (behavioural and experimental) economics, which makes the reproducibility of these studies in the same or other settings hard to assess. Because systematic research in this area is thus far lacking, systematic reviews or meta-analyses must be conducted to gain a better understanding of these phenomena, and pave a clearer path to predict the impact of current and future shocks to our global risk-taking behaviour.<\/p>\n

Experts are also split on the stability of risk-taking (Frey et al<\/a>, 2017; Harrison et al<\/a>, 2019). While both economics and psychology acknowledge the wide heterogeneity in individual risk-taking, there is currently debate on whether risk-taking is a stable trait or one that fluctuates over time and across contexts (Loomes and Pogrebna<\/a>, 2014; Sanders and Jenkins<\/a>, 2016).<\/p>\n

Evidence is also growing that risk-taking is largely \u2018domain-specific\u2019 (Barseghyan et al<\/a>, 2011; Riddel<\/a>, 2012; Galizzi et al<\/a>, 2016). This has a number of plausible implications:<\/p>\n