Great Moments In Causal Inference
Great Moments In Causal Inference
A blog about business and economics.
March 1 2012 10:37 AM

Great Moments In Causal Inference


One of my absolutely favorite things about financial journalism is the need to semi-arbitrarily match news events to market fluctuations. The way this works is that every day equity markets are either up or down or flat, and whatever happens it's newsworthy. Meanwhile, a bunch of stuff happens. Journalists and headline writers are thus put under great strain to assign some kind of connection between news events and market fluctuations even though everyone knows that there's a fair amount of random fluctuation in day-to-day equity pricing. Since these are highly trained professionals doing the causal attribution, they usually manage to come up with something that at least sounds plausible. Like if there's a jobs report and shares go up, we'll either hear that shares went up because the jobs report was strong or else that shares went up because the weak jobs report has boosted expectations of monetary stimulus.

Sometimes, though, you get something like the above which I can't even parse at all.

Matthew Yglesias is the executive editor of Vox and author of The Rent Is Too Damn High.