Faith in Untrustworthy Numbers: How Economists Missed the Crisis
Yesterday, we were talking about the only question worth discussing since 2008 — who takes the loss?
Actually, there are several variants of the question…but they all end up in the same place. Mistakes were made; somebody is gonna pay. Who?
Economists are not stupid. Especially those who win Nobel Prizes. They test well. They go to good schools. They can usually do higher math.
Math is important to modern economics. It makes it look like science. So, if you review almost any PhD thesis in economics over the last 20 years, you are bound to find numbers. Lots of numbers. You might find dozens of 9s…or hundreds of 5s…or maybe thousands of 0s.
You’ll also find symbols. Greek symbols. And symbols from the mathematician’s trade. These symbols mean something. So do the numbers.
And you can use these meanings to tease out even more confections. Complex. Sophisticated. Precise. Impressive.
And generally not worth a damn.
We say that after long observation. It is the result of careful reflection and reckless intuition.
The observation has occurred over the last dozen years or so. Despite all their numbers, formulas and Nobel prizes, America’s leading economists, including the lead dog economist himself, Ben Bernanke, were apparently unable to see something so obvious that even we spotted it: the collapse of housing and the blow up of the credit market.
Not that they are dumb. They are just following a different career path. A genuine economist keeps his eyes open. He reads the paper. He reads books. He studies history. He talks to taxi drivers and businessmen. He tries to understand what has gone on in the past…and what might be going on today.
He has no illusions about it. The future will never be like the past. But there will be similarities. And those similarities can be studied…
He has little appreciation for numbers. He knows they can’t be trusted. They are like whores and lobbyists — they will do their work for whomever pays them.
‘You want a 2? I’ll give you a 2. And I’ll throw in a 7. How much can you pay?’
He is especially wary of precise numbers. The GDP rose 2.4% say the economists. Oh…not 2.5%? Not 2.6%? Then, the economist will give a “confidence factor,” to make the numbers even more reliable. He will be 72% confident that his 2.4% figure is correct. And you can be 91% sure that the true number is somewhere between 2.3% and 2.5%.
The greater the precision, the greater the lie.
With the vision obscured by all their precise numbers and enhanced calculations, most economists could not see the crisis coming. On the evidence, their numbers are not very useful.
But now they bring them out again…this time to solve the problem they never saw coming.
Regards,
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