We’re just moving into the Second Great Depression courtesy of our bosom buddy covid-19. But how bad is it going to be? Globally we’ve had prior experiences such as the 1918 pandemic, but we don’t have any formal models to inform us of the likely outcome and how bad it will be. We’re all flying by the seat of our collective pants. How much money should the central banks all print anyway? No-one has an earthly, central bankers in particular.
It’s not just covid-19 to think about anyway. We are already facing other pandemics, even though we’re not through this one yet, maybe nowhere near the end. How about bubonic plague, zika virus not to mention swine flu and – late-breaking news - Ebola, the worst of them all.
Globally we are knee deep in economists, but we still couldn’t predict the current market bubble amidst a looming depression. So, it goes with the economic effects of global pathogens.
Here’s the issue: current approaches to economics assume that the pathogenic environment is fixed, that on average it doesn’t change. That’s our basic assumption behind it all. But what the covid-19 situation shows us is that the pathogenic environment is a variable, and a huge one at that. You can’t really predict the direction of the world economy if you don’t understand those pesky varmints.
With every different pathogen there’s a huge range of factors that impact the economic situation. How about the fatality rate, the infection rate, the incubation period, the rate of asymptomaticity, initial health condition, age of greatest impact, blood type and so on, blah blah de blah? What we have seen is that no-one has a clue, not just for covid-19 but for all the other viruses out there. So natch, we have no idea of the likely economic impact.
I’m sure you’ve heard of behavioral economics. There the problem is that traditional economics takes no account of our cognitive biases, conscious or otherwise. Traditional economics assumes we all make rational decisions all the time. Behavioral economics was invented to explore what happens if we are not rational; like most of the time right? So, economics grew a big new branch to address this huge gap in the discipline.
I think we need to do the same thing with economics to deal with pathogens. You might say that we already have health economics, but no, that doesn’t come within a parsec of what’s happening and is needed. Health economics deals with things like the economics of hospitals, of health care delivery and so on. But it has resolutely steered clear of the pathogens; that has been a step too far. So how about someone invents nucleic economics to fill the void?
The More the Merrier
Here’s my guess. We’re entering a new world of many more epidemics and pandemics. They might well happen all the time. Some of them will happen simultaneously, like covid-19 and flu, maybe even others like swine fever and Ebola. So, the economic impact will be compounded.
Instead of one depression’s worth of adverse economic effects, we will get several depressions’ worth, all at the same time! That’s something new, right? That’s when we’re going to need nucleic economics!
That’s as in DNA, RNA (deoxyribonucleic acid, ribonucleic acid), nucleotides and the alphabet soup that makes up modern genomics and proteomics. We need to figure out how they all impact everyday economics. We’re clearly not there yet.
When we have several pandemics going on simultaneously, with much of the world locked down and not working, we will want to know how much it’s all going to cost and how best to mitigate these impacts. Currently we have no idea. That’s one of the reasons so many of our leaders have been caught napping. Next time we’ve got to do better.
Desperate times need desperate measures. We badly need to develop a rational economics of desperation that enables us to look at death in the face and figure out how to beat it instead. Otherwise we’re going to be trapped in the same unconstructive arguments next time on the so-called binary choices of lockdown or not, face masks or not, social distancing or not.
Time for us to set the stage for real data and decisions next time.