Economists — people biased toward overconfidence

4 Dec, 2022 at 20:50 | Posted in Economics | 2 Comments

nate silverNow 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. Instead, 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 too 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.


  1. “there is also a question of determinism versus probabilistic forecasting. Newton’s math is continuous and his results deterministic. This can make global forecasts which fail to anticipate the end of the Cold War, or overstate the world’s human population (Limits to Growth, Meadows et al. 1972), seem unscientific, especially from the mentality of a sophomore physicist or engineer. This quest for certitude has practical utility for careers. If one’s job is to design the Golden Gate Bridge, one needs to have some extraordinarily high practical level of confidence that the design will be stable. But it is worth pondering a moment the broader question of inherent uncertainty, as Stephen Hawking does in these words from a web-lecture that he has posted under the title “dice 2”:

    It seems Einstein was doubly wrong when he said, God does not play dice. Not only does God definitely play dice, but He sometimes confuses us by throwing them where they can’t be seen. Many scientists are like Einstein, in that they have a deep emotional attachment to determinism. Unlike Einstein, they have accepted the reduction in our ability to predict, that quantum theory brought about. But that was far enough. They didn’t like the further reduction, which
    black holes seemed to imply . . . It is just a pious hope that the universe is deterministic, in the way that Laplace thought. I feel these scientists have not learnt the lesson of history. The universe does not behave according to our pre-conceived ideas. It continues to surprise us. (2007)

    Excerpt from Frank Whelon Wayman, the late Paul R. Williamson, Solomon W. Polachek and Bruce Bueno de Mesquita 2014 “Predicting the Future in Science”

    Here is an excerpt from Mesquita that addresses prediction via his game theory model. Worth a look especially considering his discussions of human motivations.

    “Arthur Andersen was driven out of business by an aggressive Justice Department looking for a big fish to fry for Enron’s bankruptcy. Later, on appeal, the Supreme Court unanimously threw out Andersen’s conviction, but it was too late to save the business. Thousands of innocent people lost their jobs, their pensions, and the pride they had in working for a successful, philanthropic, and innovative company. Andersen’s senior management apparently was entirely innocent of real wrongdoing. Unfortunately, they nevertheless helped foster their own demise by not erecting a good monitoring system to protect their business from the misbehavior of their audit clients. In fact, that was and is a problem with every major accounting firm. In Andersen’s case, I know from painful personal experience how needless their sad end was.”

    “Around the year 2000, the head of Andersen’s risk management group asked me if I could develop a game-theory model that would help them anticipate the risk that some of their audit clients might commit fraud (this is where my“work related to the Sarbanes-Oxley discussion from a few chapters back began). As I have related, three colleagues and I constructed a model to predict the chances that a company would falsely report its performance to shareholders and the SEC. Our game-theory approach, coupled with publicly available data, makes it possible to predict the likelihood of fraud two years in advance of its commission. We worked out a way to identify a detailed forensic accounting that helps assess the likely cause of fraud—if any—as a function of any publicly traded company’s governance structure.”

    Excerpt From
    The Predictioneer’s Game 2009 Bruce Bueno De Mesquita

  2. Why not devise insurance (can I hint at basic income again?) for deviations of 100% or more from model predictions, as bridge builders use safety factors to double (at least) the predicted tolerances of their models before ppl use them?

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