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Procedural Rationality in the Time of COVID-19

Utteeyo Dasgupta (utteeyodasgupta@gmail.com) is a faculty member in economics at Wagner College, United States. Chandan Kumar Jha (chandangipe@gmail.com) is a faculty member in finance at the Madden School of Business at Le Moyne College, US. Sudipta Sarangi (ssarangi@vt.edu) is a faculty member in economics at Virginia Polytechnic Institute and State University, US.

Homo economicus, the typical economic man, is a rational agent whose goal is to find the optimal solution to any problem. However, this may not be feasible in complex situations like the current global pandemic. We argue that in such environments where Knightian uncertainty plays a big role, the behaviour of countries, sectors of the economy, and individuals may be characterised by procedural rationality. Instead of focusing on the outcome, it is argued that the decision-maker draws upon similar experiences and follows a consistent procedure. 

The ongoing COVID-19 pandemic is without a parallel in the last 100 years of human history. The closest comparison is probably the gargantuan calamity-ridden 1918 flu pandemic of which there are hardly any survivors remaining to tell tales of. The last few months have witnessed countries going from total denial about the impact of the severe acute respiratory syndrome-coronavirus-2 (Sars-Cov-2) to complete lockdown ­orders. Life has been at a standstill and economic activities have been frozen. We are now entering a transition phase where different countries, perhaps resig­ned to their fate, are contemplating reopening their economies partially, fully or in stages. India, for example, has introduced nationwide colour-coded activity zones, where red zones are extre­mely restrictive and green zones are attempting a return to normalcy. The United States (US) instead, keeping with its federalist foundation, has different states taking their own measures to ­restore economic activities without ­adhering to a single coordinated nationwide criterion. South Korea, relying on intrusive citizen monitoring policies, has voluntarily resorted to life as normal. However, without an antidote, or the promise of a vaccine in the immediate future, these steps are all analogous to driving through a dense fog to a necessary destination.

As with any global catastrophe, the pandemic has created systemic uncertainty. Idiosyncratic or individual-­specific uncertainty that is always present is still there, but its magnitude has increased manifold. The policymakers currently face three levels of uncertainty. First, is the “biological uncertainty” stemming from the fact that we are unsure of treatment drugs and do not have a clear timespan for a vaccine. Moreover, our knowledge of Sars-Cov-2 and Covid-19 remain limited. Although social distancing has provided partial respite by “flattening the curve of new infections,” reopening might trigger a relapse. Ultimately, most countries still do not have a systematic way of monito­ring asymptomatic patients and lack adequate reserves of protection equipment for front-line workers, doctors and nurses, as well as medical necessities like hospital beds and ventilators for the sickly.

Keeping the economy frozen without a clear reopening date creates a second source of uncertainty and problems that we call “economic uncertainty.” As of now, nobody can predict with any reasonable accuracy the end date for the pandemic, making planning and ­decision-making very difficult. For ins­tance, without a termination point, it is simply not possible to do dynamic optimisation, that is, optimal decisions over multiple time periods are not feasible. This means businesses, large and small, will defer investment decisions no ­matter how cheap loans become (remember Keynes’ liquidity trap). Production planning is also made difficult by the fact that supply chains are now global, subject to vulnerabilities outside a firm’s control (see, for instance, Luo and Tsang 2020). Add to that the substantial uncertainty on the demand side, which is harder to predict even under normal circumstances. Job loss, falling wages and movement of labour across regions are going to affect demand on an unprecedented global scale. In the midst of all this, the US stock market has been beha­ving almost like a Foucault’s pendulum, with little connection to happenings in the real economy where all economic ­activity is at a standstill (Krugman 2020).

Finally, a third source of uncertainty arises from the interaction between the biological and economic uncertainty. Coupled with idiosyncratic uncertainty, it will produce a variety of individual-level responses making it almost impossible to offer clear solutions. 

Concept of Procedural Rationality 

Economists as decision scientists play a vital role in providing a framework for dealing with uncertainty, the main weapon in their arsenal being the expected utility theory (EUT). In this approach, every uncertain situation is quantified by identifying all possible outcomes or things that can happen in an uncertain event, along with the probability of each outcome. Consider Savage’s example of making an omelet with six eggs (1954: 13–15), five of them already cracked and poured into a bowl while the sixth one is yet to be cracked. If it were a good egg, cracking and pouring it into the bowl with the other eggs would save the hassle of cleaning a new bowl; however, if it turns out to be rotten, then you lose five fresh eggs. The outcomes in this decision problem are clear—an egg can either be fresh or rotten. Since we know how long each egg has been in our refrigerator, we can attach probabilities to each of the two outcomes. Then Homo economicus can step in and make an ­optimal decision about the sixth egg ­using some version of the EUT framework by taking into account the costs and benefits of cracking and not cracking. Following Frank Knight (1921), economists have called this “risk” and distinguished it from the notion of ­“uncertainty.”

Knightian uncertainty describes situations where the odds for the event cannot be computed because we have no way of knowing the probabilities associated with each outcome (formally a situation of “ambiguity”) and at times may not even know all the possible states (formally a situation of “unawareness”). The current coronavirus crisis is an ­excellent case in point. The difficulty lies in the fact that for the three sources of uncertainty mentioned above, it is not always possible to know what the different states of the world might be and/or their associated probability distribution. In other words, Homo economicus cannot do the cost–benefit calculus that was possible in the egg-breaking example. However, in this “fight against the gods,” as Bernstein (1996) put it, not all hopes of a “rational” way forward might be lost.

Herbert Simon (1957) had in fact suggested a solution when he argued that finding the optimal outcome might not always be possible, especially when we have to contend with complex problems and/or situations involving Knightian uncertainty. He suggested that in such situations, “we should shift our focus from the outcome of the decision-making process to the process itself.” In general, he observed that people follow heuristics and engage in practices like satisficing when they operate in complex environments. Thus, our goal should be to have a method for making decisions that satisfy consistency in a way that micro­economic theory typically suggests and leads to “reasonably good” outcomes. He termed this as “procedural rationality.” We now have irrefutable experimental and empirical evidence that human beings do not always engage in “optimal beha­viour” in the classical sense and might indeed be making choices in a boundedly rational way.

Decision-makers, whether they are heads of states or of households, are precisely in this situation in the current pandemic. Without adequate knowledge or information about myriad things, the best they can hope for is to follow some “rational” procedure in making decisions. One version of procedural rationality that seems to find support in current behaviour is the notion of “case-based decision theory” introduced by Gilboa and Schmeidler (1996). The basic idea goes back to Hume (1748) who ­argued that, “From causes which appear similar we expect similar effects. This is the sum of all our experimental conclusions.” The intuition is that in situations of Knightian uncertainty, decision-makers draw on their experiences from “similar” problems in the past and imitate a successful solution and/or avoid choices that lead to unsuccessful outcomes. By its very nature, then, if a decision-maker ends up with the optimal solution for a problem it is pure coincidence.

Procedural Rationality at Work 

To see how the evidence stacks up in ­favour of procedural rationality in the current crisis, let us start with the following question: Why has the response to COVID-19 been dramatically different across different countries? Ultimately, they all face the same level of virologic uncertainty. One possibility is to exa­mine their pandemic responses in light of their exposure to other such phenomena in the past, particularly exposure to SARS.

Country-wise performance: SARS cases were first found in the Guangdong province of China in Nove­mber 2002. The disease spread to 26 countries over the next several months causing 774 deaths. Countries with the highest deaths from SARS were: China (349), Hong Kong (299), Taiwan (37), Canada (43), and Singapore (33). With the exception of Canada and France (1 death each), the Western world did not suffer any causalities.

Consider Taiwan’s response to the current pandemic. It established the ­National Health Command Center in 2004 with an objective to prevent the outbreak of infectious disease pande­mics and started screening all passengers from Wuhan the same day it learned of the virus. Moreover, Taiwan integrated its national health insurance and immigration and customs databases, and used travel history and clinical symptoms to identify the cases of coronavirus infections (Wang et al 2020). Messaging services were used to disseminate information and mobile phones were used to monitor those in quarantine. Services like production and allocation of masks were centralised and ­important health-related information was communicated to the public through daily press briefings. Singapore placed travel restrictions on people coming from China, against the World Health Organization’s advice, along with aggressive testing and tracking right away. Additionally, it provided free testing and treatment, as well as a quarantine allo­wance. Hong Kong sealed borders with mainland China almost immediately, made 14-day quarantines mandatory for people arriving from China, closed schools, universities, and other public facilities, such as museums, encouraged people to work from home, all in an ­effort to contain the spread.

This is in stark contrast to the happenings in the US and many European countries. It is obvious these countries did not take the pandemic seriously in the early stages. For instance, even though the US government was warned about the pandemic in January, no measures were taken until the third week of March when guidelines were finally issued urging people to stay at home to the ­extent possible, avoid discretionary travel and public places, including restaurants and bars and gatherings of more than 10 people. By comparison, Canada tested people more aggressively, emphasised social distancing more stro­ngly, managed personal protective equipments (PPEs) more effectively, and due to the SARS experience, its health agencies at different levels were able to coordinate better.

In Europe, Italy, once the epicentre of COVID-19, refused to take strict measures until the situation got out of hand. Initially, the Italian government imposed partial lockdown only in certain “red zones.” The United Kingdom’s story is no different. Instead of taking serious measures after the first case of the coronavirus on 31 January, it was not until the third week of March that social-distancing measures were advised, and lockdown put in place prohibiting all non-essential businesses and travel. The late action has been true for most European nations and some countries have still not imposed a lockdown. One explanation for such a response could be that the Western world in general has not faced catastrophic events of such propor­tions since World War II. Barring Canada, the Western world cumulatively had fewer than 100 SARS cases. It is therefore not surprising that many deve­loping countries like India, which are constantly facing some sort of threat or the other, have responded better, especially when one takes resources into account. 

Sectoral performance: Next, let us consider different sectors of the economy and see why some of them may be able to fare better than others. At first cut, one may attribute this to exogenous factors, and to a certain extent this is true. But there does seem to be a pattern. Sectors of industry that are constantly innovating or face more competition and adversity seem to be doing better and preparing better. The hotel industry in the US, which survives to a large extent on business travel, cannot do anything about current predicament. Yet, it claim that its recovery is faster than airlines because the franchise model in the hotel industry relies on the experience of a diverse set of owners. Within the airline industry, it is generally believed that low-cost airlines in the US will do better than their counterparts in Europe because of tougher competition. The entertainment industry, which includes movies and concerts, has been quickly able to borrow from its techno­logy expertise to offer online shows. The education sector, which has a significant proportion of people with higher education, was almost instantly able to adapt itself to online teaching, simply because it is constantly dealing with new forms of technology.

Agriculture is probably the sector that is always dealing with some type of ­uncertainty. It is subject to economic ­uncertainty because an individual far­mer or country has little control over the global output or agricultural policies ­followed in other countries. Additionally, it has to contend with the vagaries of nature, and farmers have to carry out all their work in the narrow window of ­opportunity provided by nature regardless of the presence or absence of additional labour. The Indian agricultural sector is a wonderful case in point. In the recent years, this sector has weathered several adversarial situations akin to the current pandemic, ranging from demonetisation to several droughts to even anti-inflationary policies. Yet, thanks to the resilience of this sector, efficiency of our much-maligned public distribution system, and pro-poor food distribution ­related efforts in different states, India is witnessing hunger but not starvation deathsat least not for the time being. In other words, its experience with adver­sity enables the agricultural sector to make decisions and adapt faster than other sectors of the economy. 

Risk-taking behaviour: Finally, procedural rationality suggests that the experience of this pandemic is likely to influence future beha­viour as well, and these changes could persist long after the pandemic is over. The occurrence of a major event—­economic or non-economicthat leads to traumatic or catastrophic experience has long-lasting impact on the beha­viours of those that experience it. The experience of a large macroeconomic shock, such as the Great Depression, ­exposure to war during childhood, and the experience of a natural disaster can cause people to become more risk averse. Malmendier and Nagel (2011), for example, find that individuals who experienced the Great Depression tend to be less ­active in the stock market. The opposite is true for those who had positive experiences with the stock market. Similar ­effects on risk-taking behaviour have been observed for individuals who were exposed to wars. For instance, adults who were exposed to World War II as children show greater risk aversion, are less likely to invest in stocks and more likely to have life insurance (Bellucci et al 2019). Likewise, exposure to the Korean War has been found to have a persistent negative effect on financial risk-taking (Kim and Lee 2014). And, those who have suffered a natural disaster, such as a flood or earthquake, exhibit a greater degree of risk aversion (Cameron and Shah 2015).

Possibly, exposure to the war might affect the preferences for risk-taking by increasing the subjective perception of risk in financial investments, and the experience of a natural disaster might alter the individual’s beliefs about a recurrence. Ultimately, individual behaviour tends to encompass a wide variety of ­experiences and can therefore be more idiosyncratic. It would not be surprising to see people maintaining social distan­cing, washing hands, wearing masks in public places, and taking other precautionary measures long after this pandemic is over. Their risk attitudes and their beliefs about the recurrence of a pandemic are likely to reduce activities that might expose them to strangers, such as travelling by plane, eating out at restaurants, or shopping at malls, affec­ting such sectors more adversely than others.

We are neither soothsayers nor do we have a crystal ball with which to foretell the future. We do, however, believe in procedural rationality, and in keeping with that mode of boundedly rational behaviour without asserting more, we hope that things will get better sooner than later. In the meantime, the outcomes for countries, sectors of the economy and individuals will vary based on their experiences and decision criteria.

References 

Bellucci, D, C Fuochi and P Conzo (2019): “Childhood Exposure to the Second World War and Financial Risk Taking in Adult Life,” Journal of Economic Psychology, doi: 10.1016/j.joep.2019.

Bernstein, P A (1996): Against the Gods: The ­Remarkable Story of Risk, New York: John Wiley & Sons.

Cameron, L and M Shah (2015): “Risk-taking Beh­aviour in the Wake of Natural Disasters,” Journal of Human Resources, Vol 50, No 2, pp 484–515. 

Gilboa, I and D Schmeidler (1996): “Case-based Optimisation,” Games and Economic Behaviour, Vol 15, No 1, pp 1–26.

Hume, D [1748] (1966): Enquiry into the Human ­Understanding, second ed, Oxford: Clarendon. 

Kim, Y I and J Lee (2014): The Long-run Impact of a Traumatic Experience on Risk Aversion,” Journal of Economic Behaviour & Organisation, Vol 108, pp 174–86. 

Knight, F H (1921): Risk, Uncertainty and Profit, Boston: Houghton Mifflin. 

Krugman, Paul (2020): “Crashing Economy, Rising Stocks: What’s Going On?” New York Times, 3o April, https://www.nytimes.com/2020/04/30/opinion/economy-stock-market-coronavi...

Luo, Shaowen and Kwok Ping Tsang (2020): “China and World Output Impact of the Hubei Lockdown during the Coronavirus Outbreak,” Contem­porary Economic Policy, forthcoming. 

Malmendier, U and S Nagel (2011): “Depression Babies: Do Macroeconomic Experiences Affect Risk Taking?” Quarterly Journal of Economics, Vol 126, No 1, pp 373–416.  

Savage, L J (1954): The Foundations of Statistics. New York, NY: John Wiley & Sons Inc. 

Simon, A H (1957): Models of Man, New York: Wiley.

Wang, C Jason, Chun Y Ng and Robert H Brook (2020): “Response to COVID-19 in Taiwan: Big Data Analytics, New Technology and Proactive Testing,” Journal of American Medical Associ­ation, Vol 323, No 14, pp 1341–42.

 

Updated On : 23rd Jun, 2020

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