The Graph That Proves Economic Forecasters Are Almost Always Wrong

As the saying goes: "It's hard to make predictions. Especially about the future." Thirty years ago, it was obvious to everybody that oil prices would keep going up forever. Twenty years ago, it was obvious that Japan would own the 21st century. Ten years ago, it was obvious that our economic stewards had mastered a kind of thermostatic control over business cycles to prevent great recessions. We were wrong, wrong, and wrong.

So, how wrong are economic forecasters about their big predictions today? Fortunately, we have a way to measure that sort of thing -- the gap between expectations and reality. It's called the Citigroup Economic Surprise Index.

A high Surprise Index indicates that economic figures have been stronger than analysts projected. A low Surprise Index indicates that the economy is doing much worse than analysts predict.

Today, economic data are outperforming predictions by the most in almost a year, Bloomberg reported this week. Compare with this summer, when experts thought the economy should be slowly improving, whereas indicators suggested we were in fact nearing a recession.

Here is your roller coaster on the Surprise Index for the last three years:

There are a few lessons to glean from the Surprise Index, which I was only made aware of this week. First, predictions are often reported as news. They're not. They're predictions, and they're almost always wrong. Full disclosure: I've been as guilty as anyone for breathlessly passing along predictions without the qualifying them as conjecture. Second, to be fair to the analysts, sometimes the first draft of the economic figures aren't any better than the predictions. A great example: We initially estimated GDP falling 3.8% in the last three months of 2008. Instead, it fell nearly 9%. That's a horrible miscalculation that had a real impact on decisions made by Congress and the Federal Reserve to fix the economy. I wonder what the Economic Surprise Index would say about first readings of GDP and unemployment numbers.