Economists, particularly environmental and resource economists, and definitely those that have worked on invasive species and/or climate change, have a lot to say about the COVID-19 virus upending the global economy. Research is moving almost as fast as the virus itself.
The invasive species problems we’ve studied are in many ways slow-moving epidemics. They can create devastation and transformation of systems. The economics of climate change anticipates the same sorts of disruptions (already underway) in slow motion as well. Environmental and resource economists understand the roles of human behavior in preventing, controlling, or adapting to these changing conditions. We’re comfortable with models of this sort of spreading destruction as well as human interventions that can dampen or expand the impacts. We’ve considered tradeoffs between action and inaction, as well as hodge-podge, stop-and-start strategies that may waste more resources than they save, failed timing of interventions, and unintended consequences of addressing only part of the systemic change.
Environmental and resource economists are the pioneers of Value of Statistical Life – the tool that helps us analyze real tradeoffs when human lives and well-being are directly at stake. We understand the benefits of cooperation – and are even trying to apply them to our research agendas as well. That’s a main point of this seminar:
The seminar and slides summarize nicely what environmental and resource economists bring to the table in pondering this complex question. In addition to the above, we’re well-trained in thinking about resilience, compliance with regulations, incentivizing behavior at lowest cost, bad data, missing data, and so on.
We’ve put lots of thought into how to weigh present benefits against future costs or vice versa (known as discounting). Some have already been collaborating with epidemiologists for years and are already publishing results on how to analyze the ways in which school closings may be affecting economic outcomes (see here).
Here’s a summary of what’s out there so far more specifically on COVID-19. Feel free to update in the comments with new or missed material, or send it to me and I’ll add it here.
A team at the University of Wyoming did a quick calculation that social distancing measures may be saving the US around 5 trillion dollars in value: Thunstrom, L. Newbold, S. Finnoff, D, Ashworth, M. and J.F. Shogren (forthcoming). The Benefits and Costs of Using Social Distancing to Flatten the Curve for COVID-19. Journal of Benefit Cost Analysis. Tradeoffs involved in the COVID-19 problem are somewhat stark in large part because there is no vaccine or cure. Dramatic economic consequences can be taken to curtail loss of life, with much uncertainty about the extent of both sets of damages. the paper estimates the lives saved and the economic losses in GDP to show how beneficial our stay-at-home and other social distancing policies can be.
Michael Greenstone and Vishan Nigam take a similar approach with more nuanced weighted inputs for VSL and find similar results here. This is part of the Becker Friedman Institute for economics at The University of Chicago‘s efforts to deploy its significant resources to COVID-19, here.
There are a large number of webinars from economists, many of which ask many questions as yet without answers. Economists are thinking about how to think about the many important dimensions of the problem: inequalities, economic losses, loss of life, threats and co-benefits to successful interventions.
Lots of economists with varying levels of epidemiology and environmental/resource economics experience are also writing about the COVID-19 problem. Most of them are very interesting versions of dynamic optimization models; some address sectoral differences, others incorporate behavioral responses directly. I’ve included resources and links here without much additional annotation for now. Feel free to post questions in the comments if you get to reading and find yourself lost in the weeds.
I do like this webinar it sums up the long run big picture pretty well:
Webinar Series: Leading Through Radically Changing Times
COVID-19, Climate, and the Clean Economy: Gigatrends Changing the World
The Royal Economic Society has been getting heavy hitters (Acemoglu, Tirole) to provide webinars here. Angus Deaton, with insights into deaths from inequality, weighs in with a webinar here. The Barcelona Graduate School of Economics is gathering COVID-19 economics research here.
As of April 22, 2020, the Social Science Research Network (SSRN) paper repository returns 87 articles with the keywords “Coronavirus” and “economy” and the main page has a link to all the Corona-related resources uploaded to SSRN and its companion MedRN site, where there are 474 articles (only 5 of these have economy as keywords).
VoxEU and CEPR (Center for Economic Policy Research) has a new web page for the Economics of COVID-19 here. The focus is Europe, but there are a wide range of resources, including a new rapid-review rapid-dissemination journal “Covid Economics” and other articles, discussions and insights.
Finally, economic historians have a lot of research that can help contextualize both the expectations and the uncertainties. Most of this research is about the Spanish flu of 1918, and the research is being nicely collected here: Collective Bibliography on Pandemics in History.
Cover image credit: Roser, M, Ritchie, H., Ortiz-Ospina, E. and J. Hasell (2020) Statistics and Research: Coronavirus Disease (COVID-19). Our world in Data April 22, 2020.
And don’t forget the spatial dimensions of the problem that are also intensively studied in many invasive species problems, not to mention the weakest link public goods aspects.
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Thanks for pulling all this together. Yes; if you look at a spatial network of confirmed cases, it looks very much like a network of invasive miconia trees. Like miconia, coronavirus spreads within and around each cluster and also jumps by travel (birds spread miconia seeds), establishing new clusters. That gives you two controls—geographically containing the spread with travel restrictions and mitigation. For disease, the latter takes the form of lowering the average number infected by each infectee (known as the reproduction number, R). If done early enough R, can be kept low by surveillance testing, tracing, and isolation. Depending on test/trace capacity, this means becomes less effective at higher levels of infection, and blunter and more economically damaging measures are used (social distancing and banning of selected activities).
A third mode of control—herd resistance—is available for disease, but most covid commentators seems to confine its use to vaccines, immune globulin, and antitoxins. But the Ioannidis/Stanford study of antibodies in Santa Clara Country suggests that resistance could possibly be a control mechanism even before artificial injections. If the vulnerable population can be kept isolated, then total harm (welfare loss) reduction may entail limited opening of the economy and building resistance within the less vulnerable population, in line with the constraint on hospital capacity.