Why economists are useless at forecasting

4 October, 2016 at 10:08 | Posted in Economics | 4 Comments

We forget – or willfully ignore – that our models are simplifications of the world …

nate silverOne of the pervasive risks that we face in the information age … is that even if the amount of knowledge in the world is increasing, the gap between what we know and what we think we know may be widening. This syndrome is often associated with very precise-seeming predictions that are not at all accurate … This is like claiming you are a good shot because your bullets always end up in about the same place — even though they are nowhere near the target …

Financial crises – and most other failures of prediction – stem from this false sense of confidence. Precise forecasts masquerade as accurate ones, and some of us get fooled and double-down our bets …

Now consider what happened in November 2007. It was just one month before the Great Recession officially began …

Economists in the Survey of Professional Forecasters, a quarterly poll put out by the Federal Reserve Bank of Philadelphia, nevertheless foresaw a recession as relatively unlikely. Intead, they expected the economy to grow at a just slightly below average rate of 2.4 percent in 2008 … This was a very bad forecast: GDP actually shrank by 3.3 percent once the financial crisis hit. What may be worse is that the economists were extremely confident in their prediction. They assigned only a 3 percent chance to the economy’s shrinking by any margin over the whole of 2008 …

Indeed, economists have for a long time been much to confident in their ability to predict the direction of the economy … Their predictions have not just been overconfident but also quite poor in a real-world sense … Economic forecasters get more feedback than people in most other professions, but they haven’t chosen to correct for their bias toward overconfidence.



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  1. Professor Syll,

    Instead of deduction-based forcasting methodology, abduction is often used for diagnosis and prognosis in AI and medical domains. Below is an abduction-based prognosis for capturing causal factors and further effects from symptoms.

    ∀x (Gx => Px => Qx)
    Ga and Qa

    from evidence Pa => best explanation Ga as a cause and possible further effect Qa => inference.

    What is your comment on this from economics perspectives?

  2. Secondary information from systemresponses is not knowledge. Where is the comprehensive study of decisions and the complete papertrail leading up to the financial crisis. Where are the interrogation protocols of a thousand decisionmakers after they created the crisis?

    A science that forbid itself to get at the truth is no science. Doing maths on systemresponses is just a pantomime of science.

  3. “One of the more momentous books of the decade” the blurb says. It’s what, a little bit momentous? That’s like being a little bit pregnant.

    I don’t like the idea that “Financial crises … stem from [a] false sense of confidence.” I think they stem from bad policy, which stems from from misunderstanding the economy. One could attribute the misunderstanding to false confidence, but it would be better to spend the time trying to understand the economy.

  4. Casting it as a “forecasting” failure is to let economists off too lightly. It was a failure to see what was going on in real time. In November 2007, the American economy was heading off a cliff, driven by the deflation of a housing bubble that many economists denied even being able to see; central banks led by the Federal Reserve were “foaming the runway” with liquidity, liquidity that would fuel a speculative frenzy in commodities that was driving up prices for a broad range of basic commodities globally, including wheat and oil.
    Economists allow themselves to “think” about macroeconomics in terms of “shocks” and “frictions” that exempt them from considering what is actually happening. That they cannot predict the future is not the problem; the problem is that they cannot see the present.

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