Monday, June 14, 2010

Lies, Damn Lies and Statistics (part ongoing)

Madness to the Method:

At 8:30 a.m. on Friday, June 4, the Bureau of Labor Statistics released its much anticipated monthly jobs report. Expectations were running high that the U.S. job market was finally rebounding. And at first glance, the numbers released looked decent, with 431,000 jobs added and the unemployment rate dropping modestly, to 9.7%. On closer inspection, the report didn't seem as good: more than 400,000 of those new jobs were due to the government's hiring Census workers rather than companies' ramping up for growth. The jobless rate decreased only because hundreds of thousands of people became so discouraged, they dropped out of the workforce.

Financial markets took the report badly. Commentators were equally quick to pounce and warn of a double-dip recession, and the report became another arrow in the quiver of those assailing current economic policy.

There is just one problem: these numbers are wrong.

They always are. The jobs numbers are revised each month and then again in subsequent years. Sometime later this year, we may learn that twice as many jobs were lost in May as we thought or that, actually, hundreds of thousands more were created. The numbers are generated by surveys and then smoothed by complicated statistical formulas, but however sophisticated all that may be, the world is simply more complex than our ability to measure it in real time.

I've noted my problems with the way unemployment is calculated by the Bureau of Labor Statistics (BLS) in the past. Surveying households and asking people if they've lost their job seems antiquated and absurd (why don't we survey major corporations, governments and non-profits and ask how many people they've let go?).

Similarly, their calculations of "underemployment" and "long-term unemployment" make no sense. The effect of extended unemployment benefits on employment discouragement is ignored; most people feel their skills are underutilized; and asking if people "would like to work" a different or better job isn't really a measure of anything (who wouldn't volunteer something? put me down for "Astronaut,").

But this isn't just a BLS problem, as Karabell notes. Everything from the consumer price index, to consumer confidence, to housing sales/foreclosures, to GDP, to inflation are subjected to constantly changing data and interpretation. Just Google "consumer confidence" and you'll get everything from it being on the increase, to holding steady, to declining rapidly, all on one page.

Karabell excuses "human stupidity" as the culprit (I'm less inclined to do so), and says nothing of the fact that recessions are a form of social control. Instead he points his finger at the increasingly complex global economy and the difficulty measuring it.

The flimsiness of statistics and the way we assemble them are not the result of human stupidity. They are the consequence of increasingly complex systems and a globalized economy of supply chains that have evolved more quickly than our ability to measure them.

The problem with our data maps, in short, isn't just that they're inexact. It's that we decide how to spend trillions of dollars, invest trillions more and answer the simple question "How are we doing?" using outmoded methods and questionable figures. We need better models, and we need them urgently. Given the nature of the information we currently use for our collective vital statistics, it's a wonder we still have an economy to argue about.
It certainly doesn't bode well for any sustained recovery if people are bombarded on a daily basis with polls and studies spouting contradicting gibberish. The one thing we can conclude is that the economy is fundamentally driven by consumer spending. And if people don't feel comfortable spending (because of said gibberish above), the economy could stagnate as it is in perpetuity.

Which is probably just fine with the power-elite. Nothing keeps wages low and corporate profits high quite like disciplining the labor force and keeping the people cowed by confusion.

No comments: