When it comes to prognosticating economic events, for example, individuals are especially unreliable.
"Economic forecasts are blunt instruments at best, rarely being able to anticipate economic turning points more than a few months in advance," he writes. "Economists' predictions have not just been overconfident but also quite poor in a real-world sense, often missing the actual GDP figure by a very large and economically meaningful margin."
Take the Obama Administration's prediction three years ago that the national unemployment rate would fall below 8% after the president signed the $787 billion stimulus bill in early 2009. The economy, even with that massive monetary injection, ended up getting worse. The unemployment rate went from 7.6% to 10% before settling in the 8% range where it has been for more than a year.
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Economists in the George W. Bush Administration had their share of flawed calls too. The government originally reported that GDP growth fell 3.8% in the fourth quarter of 2008. In reality, the economy contracted by nearly 9% that quarter, a much steeper drop than the original prediction.
Silver says economists have "fewer excuses" than other professionals for making mistakes. Their predictions are often too sanguine and economic experts "aren't very good at providing an honest description of the uncertainty in their forecasts."
As for President Obama's economics team, the incorrect suppositions resulted in a stimulus package that was too myopic, Silver says in an interview with The Daily Ticker. "That's a case where you do have to think through the problem and work through the details and acknowledge some humility," he adds.
Related: U.S. Economy Needs More Stimulus: Christina Romer Defends Keynesian Economics
The general track record for economists could be viewed as embarrassingly poor. Silver cites one study that found economists in the 1990s accurately predicted only two of the 60 recessions around the world a year ahead of time.
Economists may be the most egregious example of when forecasting goes wrong, but Silver says even the best prognosticators are not striving for perfection.
"We want to get 80%-85% of predictions right, not 100%," he says. "Or else we calibrated our estimates in the wrong way."
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