I’ve been reading Nate Silver’s “The Signal and the Noise” recently, and pretty much every chapter seems to lend itself to a contingency matrix. Each chapter is focused around a different prediction issue, and Chapter 1 is around the housing bubble and the incorrect valuation of the CDO market.
I wasn’t going to get in to CDO ratings, but here’s the housing bubble:
It should be noted that swapping the word “home” in the title for any other product describes pretty much every market bubble ever. Color scheme taken from the cover art of the hardcover version, or maybe the Simpsons.
See all The Signal and the Noise posts here, or go to Chapter 2 here.
I find it really hard to even comment on economic data on this blog. It’s based on so many assumptions and there are so many different numbers that can be included or excluded that critiquing it is a combination of trying to shoot fish in a barrel and trying to catch a greased pig.
Not my idea of a good time.
Anyway, BD Keller linked to an excellent post today that is way more articulate than I about why evidence based monetary policy is so hard to come by.
On economic experimental models:
Think of a good experimental design: randomised control variables, holding everything else constant, etc. Now think of the worst possible experimental design. Imagine something that engineers or psychologists might dream up over beers for a laugh, or to illustrate what not to do. That’s what economists face. It’s as if our lab assistants (the fiscal and monetary authorities) were deliberately trying to make our (economists’) lives as hard as possible. They do this, of course, not to spite us, but to try to make everyone else’s lives as easy as possible. To get a good experimental design for economists, both the fiscal and monetary authorities would need to be malevolent.
Makes sense, but given this, I do wish they’d stop saying their predictions with such authority.
My tax return showed up in my bank account this weekend, which is always nice (even if it was my money to begin with). It brought to mind a few months back when people were big on the “50% of American households don’t pay any federal income tax” statistic.
Now, that was an interesting statistic, and one that no doubt caused a lot of emotion. I mean, heck, this is my percent breakdown of taxes paid for 2011 (excluding sales-linked taxes…that retrospective would have taken all week):
Edit: My labels got a little hinky, so assume federal tax = federal income tax and state tax = state income tax. So yes, life would have been a great deal cheaper if I could have avoided federal income tax.
Anyway, I was thinking about this when I stumbled across this chart:
Along with this post
explaining that many of the households not paying taxes were actually older workers. Interesting, but economic data is so easily manipulated it doesn’t normally catch my attention (example: no where on this graph does it indicate how large each population slice is…I’m sure there are far fewer people represented at the end of the graph than at the middle).
Anyway, what this jogged my memory about was how this statistic got quoted by many at the time. Rick Warren was one of the more notable examples, but many people made the mistake of stating “half of all Americans pay no taxes”. The “Federal Income” part of that phrase makes a huge difference.
I’m certainly not saying that everyone who misquotes a stat does so intentionally. Many times it’s innocent, and thus it’s something to keep in mind when you hear a crazy statistic from anything but the source. Politicians and other public speakers do just flat out miss words sometimes. There are some pretty horrifying stats out there that become much more reasonable when the correct modifiers are put back in their place.