My starting point was based on the efficient markets hypothesis. I figured that it would be hard to come to correctly calibrated confidence about the economic consequences of a pandemic faster than the market. So I tried to integrate the most relevant-seeming information we had just prior to the market crash of 2020, and see if it was possible to do a little bit better. Predicting the outcome with correctly calibrated confidence in early February, mid-January, or early January would have been progressively more impressive, but I wanted to set myself an easier task.
Hopefully, this checklist retains utility as a tool for earlier warning, as it can serve as a sort of dashboard for monitoring a developing outbreak. For example, as an increasing number of checklist items move from “no” to “yes,” or as they become closer to “yes,” we become increasingly concerned. There’s tons of room for improvement in this checklist!
For sure!
My starting point was based on the efficient markets hypothesis. I figured that it would be hard to come to correctly calibrated confidence about the economic consequences of a pandemic faster than the market. So I tried to integrate the most relevant-seeming information we had just prior to the market crash of 2020, and see if it was possible to do a little bit better. Predicting the outcome with correctly calibrated confidence in early February, mid-January, or early January would have been progressively more impressive, but I wanted to set myself an easier task.
Hopefully, this checklist retains utility as a tool for earlier warning, as it can serve as a sort of dashboard for monitoring a developing outbreak. For example, as an increasing number of checklist items move from “no” to “yes,” or as they become closer to “yes,” we become increasingly concerned. There’s tons of room for improvement in this checklist!