The study in question is a preprint and by a political scientist. That doesn’t make the conclusions wrong but does raise doubts as to its veracity. It’s rare for someone in one field to have insights into another, unrelated field that turn out to be correct. When the study is published and analyzed by experts is the time to consider this study. Right now it’s too premature to do so.
The article is blatantly toxic in tone, which is an obvious red flag. As to the science, causality is much harder to ascertain than is correlation. In this case it appears to me that the foundational assumptions required by the CausalImpact R package are violated, thus making the conclusions invalid. I wouldn't even blink at a claim of correlation, but causation? This paper doesn't deliver on its claim.
> Effectively, this allows us to look at the past 12-16 months (each country is slightly different) before vaccine administration began, this is called the pre-intervention period, and utilize that data to project where y1 (total deaths per million) and y2 (total cases per million) would have been had the intervention of X (vaccine administration) not occurred
If authors can predict future values based on past time series, why they are not making millions on a stock market?
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[ 54.5 ms ] story [ 541 ms ] thread> Effectively, this allows us to look at the past 12-16 months (each country is slightly different) before vaccine administration began, this is called the pre-intervention period, and utilize that data to project where y1 (total deaths per million) and y2 (total cases per million) would have been had the intervention of X (vaccine administration) not occurred
If authors can predict future values based on past time series, why they are not making millions on a stock market?