How can governments mitigate the impact of COVID-19 on human flourishing?

This is an appropriate question for economists with an interest in public policy to be considering. It recognizes a possible role for governments and recognizes that an approach focused on human flourishing is likely to be more appropriate than one focused entirely on reducing the death rate or reducing adverse impacts on GDP.

The possible role for government stems from the perception that people who are most vulnerable would not able be to protect themselves adequately without some government intervention. People who know they are vulnerable have a strong incentive to practice social distancing, but personal circumstances often make that difficult. Without the threat of coercion, it is unlikely that we will see the degree of social distancing necessary to reduce the rate of spread of the virus. In that event, hospital services are likely to be over-whelmed by the number of people requiring treatment. 

As always, with government intervention, there is a risk that the cure will end up worse that the disease, but the risk is probably worth taking in this instance.

What is the appropriate indicator of human flourishing to be used as a policy objective? There isn’t just one! The prime candidates, per capita GDP and average life satisfaction both suffer from the same flaw – they don’t account for the impact of early death on the well-being of the dear departed. We should continue to consider the impacts of policies on death rates as well as their impacts on the well-being of the living.

Per capita GDP was never intended to be a measure of well-being, but it is relevant. Many factors that impinge on well-being – such as the ability of people to afford food, housing and health care – are influenced by per capita GDP levels. However, per capita GDP cannot account for impacts of coercive policy interventions, such as enforced home confinement, on psychological well-being.

Average life satisfaction seems to be a reasonable indicator of the average psychological well-being of groups of people. It is a poor indicator of economic and social progress because it doesn’t account for the extent that members of one generation perceive themselves to be better off, or worse off, than members of preceding generations. Fortunately, that deficiency is not pertinent for present purposes.

There is some evidence that lock-down and GDP decline have potential to have substantial negative impacts on average life satisfaction.

An article entitled ‘Health, distress and life satisfaction of people in China one month into the COVID-19 outbreak’, has recently been published by Stephen X Zhang, Yifei Wang, Andreas Rauch, and Feng Wei. The article is a pre-print and has not been subjected to peer review, but no major flaws are obvious to me. As might be expected, the study suggests that the life satisfaction of people with chronic medical conditions was adversely affected in locations with severe outbreaks of COVID-19.

However, the life satisfaction of people who exercised a lot was also adversely affected in locations with more severe outbreaks, suggesting frustration at restrictions imposed. Those who were able to continue to work had higher life satisfaction than those who had stopped work, with people who were able to work “at the office” having higher life satisfaction than those who worked at home.

The relationship between per capita GDP and average life satisfaction is complicated. Average life satisfaction is relatively high in countries with high per capita GDP, but tends to grow very slowly, if at all, as per capita GDP rises further in such countries.  However, there is some evidence suggesting that when per capita GDP falls in high-income countries, this is likely to be accompanied by substantial declines in average life satisfaction. Austerity in Greece reduced per capita GDP by about 26% over the decade to 2017 and was accompanied by a decline in average life satisfaction of about 20% (GDP data from OECD and life satisfaction data from World Happiness Report, 2020).

Hopefully, COVID-19 will result in much smaller declines in per capita GDP than in Greece. and economic recovery will be much more rapid.

What are the trade-offs involved in shut-down? The human welfare implications of shutting down large parts of an economy for an extended period are enormous. However, a short close-down of all those activities in which social distancing is difficult might be preferable to a less severe and more prolonged lock-down. Tomas Pueyo’s discussion of the hammer and dance (see graphic above) makes sense to me, even if the Hammer needs to last more than 3-7 weeks.

Social distancing and lock-down is an investment in buying time. Buying time for what? It can’t be for development of a vaccine. That will take too long!

It makes sense to buy time to build up the stock of respirators, ICU beds etc. to help cope with an influx of hospital patients needing treatment.

It also makes sense to buy time to obtain testing equipment that can give accurate results within a short time frame. Speedy and accurate testing has potential to enable infectious people to be detected and temporarily taken out of circulation, so that the rest of the population can return to something like normal life.

This post has not yet referred to stimulus packages. I support giving money to people to help them survive a crisis that is likely to depress aggregate demand. Please note, however, that what people can buy depends ultimately on what is produced. When an economy closes down the necessities of life tend to become scarce.

My conclusions:

• Policies to mitigate COVID-19 should be considered from a human flourishing perspective rather than solely in terms of either minimizing deaths or minimizing damage to an economy.

• The best policy seems to be to buy time by enforcing strict social distancing for a relatively short period rather than less strict distancing for a longer period. The policy aim should be to buy enough time to enable hospitals to cope better with an influx of patients and to put in place a testing regime that can enable life to return to something like normal as soon as possible.

Postscript: May 6, 2020

There isn’t a great deal of substance that I would like to change in this article with the benefit of 6 weeks hindsight. The graphs showing possible outcomes in terms of exponential growth and bell curves still look right. Some countries, including Australia, have moved along to the end of “the hammer” phase of the bell curve and are beginning the tricky “dance”. Perhaps infection rates may be greatly under-estimated and there is now considerable herd immunity, but I doubt it.

Although the governments of some countries are behaving abominably, at this stage I am confident that in Australia the intervention ‘cure’ (palliative might be a better word) will not be worse than the disease. To a large degree, the shutdown occurred spontaneously, with governments playing catchup, as large numbers of people stayed home, and businesses shut down. There has been some coercion, e.g. shutting of beaches in metropolitan areas and travel restrictions. Some police have risked public goodwill by excessively diligent (stupid) enforcement, e.g. picking on individuals sunning themselves in parks many metres away from any other human. Most people seem to be following social distancing rules because they accept that it is a sensible precaution to take for their own benefit and/or the benefit of others.

From an analytical perspective, I have been reminded that it is possible to incorporate deaths and economic considerations in a common metric if you try hard enough. Richard Layard, Andrew Clark et. al. have presented a WELLBY analysis that seeks to do that in a paper entitled, ‘When to release the lockdown: A wellbeing framework for analysing costs and benefits’. The authors use estimates of wellbeing-years (based on life satisfaction surveys) to balance the impact of policy decisions upon the number of deaths from COVID-19 against incomes, unemployment, mental health, public confidence and other factors (including CO2 emissions).

Their analytical framework looks elegant, but I am concerned about the implied policy context. It seems to me that this kind of analysis is more relevant to decision-making by a benevolent dictator (one applying utilitarian philosophy) than to a society where government should see its prime responsibility as protecting the lives and liberty of citizens.

Another article that has been brought to my attention is: ‘Some basic economics of COVID-19 policy’, by Casey Mulligan, Kevin Murphy and Robert Topel. This article looks at the trade-offs we face in regulating behavior during the pandemic.  It uses conventional cost benefit analysis to consider several possible policy objectives, including buying time and limiting the cumulative cost of a pandemic that will ultimately run its course. They conclude:

“The key difference in terms of the optimal strategy is whether our focus is on keeping the disease contained. If the objective is to buy time, then our analysis favors early and aggressive intervention. This minimizes the overall impact … . In contrast, limiting the cumulative cost of a pandemic that will ultimately run its course argues for aggressive policies later, when they will have the biggest impact on the peak load problem for the health-care system and when they will have the greatest impact on the ultimate number infected”.

The authors conclude by listing some simple economic principles to guide how public policy should proceed when faced with a new but poorly understood pandemic. Those principles include buying time upfront, and using that time wisely to gather information to implement a screen, test, trace and quarantine (STTQ) policy. They suggest that both the “buy-time” and long-term containment strategies will have to be based on an effective STTQ policy.

The approach adopted by Mulligan et. al. of considering the nature of trade-offs and suggesting policy principles is more to my liking. If these authors had used their conventional cost benefit analyses to provide specific recommendations of the kind provided by Layard et. al. I would raise the same concerns about the implied policy context of advising a benevolent dictator, rather than informing a democratic political process.

I have misgivings about the valuation of life in both studies, but have not considered the relative merits of each approach, and have nothing better to offer other than directly considering the economic cost of saving lives under alternative strategies.