This hidden flaw can lead to serious errors in economic forecasting
Daniel Kahneman, Emeritus Professor of Psychology and Economics at Princeton University and Nobel Prize-winning author of “Think fast and slow“, Now warns that” noise “- a variability of judgments that should be identical – leads to costly errors.
In “Noise: a flaw in human judgment(Little, Brown Spark – May 16), Kahneman and his co-authors, Olivier Sibony and Cass R. Sunstein, explore how harmful noise can be in many areas, including economic forecasting, and suggest remedies to reduce it.
“Contrary to popular belief, noise is not intuitive, which is why we think we have discovered a new continent,” Sunstein says of the book’s new perspectives and ideas, in an interview with ThinkAdvisor.
A law professor on leave from Harvard University, Sunstein co-authored, with behavioral economist Richard Thaler, the bestseller “Nudge: Improving Decisions About Health, Wealth, and Happiness. Sibony is professor of strategy at HEC Paris and associate researcher at Oxford.
Financial advisers are loud, doctors are loud, judges are loud – no one is immune, says Sunstein, who notes that “Noise” was written over five years ago. This includes Zoom meetings with Kahneman, who received a Nobel in economics in 2002 and the Presidential Medal of Freedom in 2013.
In the interview, Sunstein discusses how financial advisers can be quieter – which is significant since decisions of all kinds involve predictive judgment, in which noise causes errors.
It also reveals the name of the eminent professor who helped him choose between two investment advisers to manage his portfolio of stocks and bonds and that of his wife.
Sunstein is married to Samantha Power, who was recently confirmed as head of the US Agency for International Development and was a former US ambassador for the Obama administration to the UN.
In February, Sunstein was appointed senior adviser and head of regulatory policy at the Department of Homeland Security. He was head of the Bureau of Information and Regulatory Affairs during Obama’s presidency.
In our interview, he emphasizes the need to reduce noise, which, the authors point out, can cause “serious damage”. One method is to think probabilistically – “a good thing to find in a counselor,” he remarks.
Sunstein, a former Apple consultant years ago, also points to the “decision hygiene” remedy, which can also help advisors cope with an expected increase in digital financial advice.
Even mood affects noise generation or sensitivity to it, Sunstein maintains on a brief foray into what in psychology circles is known as “bull-receptivity.”
ThinkAdvisor recently interviewed Sunstein, who spoke by phone from Washington, DC. In April, he published “Avoiding Disasters: Decision Theory for COVID-19, Climate Change, and Potential Disasters of All Kinds(NYU Press).
“There’s some overlap with ‘noise’ because if you’re trying to reduce risk, you want to have some decision hygiene so that your decisions aren’t loud or biased,” he notes.
Here are the highlights of our interview:
THINKADVISOR: Why is it important to be aware of noise? You write that it’s “rarely mentioned” and “goes unnoticed”; yet “it can cause serious damage.”
CASS SUNSTEIN: Noise is an unwanted variability. Each of us is loud, some more than others. We learn that noise is often the most important “character” in human life. Unlike bias, noise is not intuitive, which is why we believe we have discovered a new continent. Noise is like the character in the background of a movie that you don’t pay much attention to but turns out to be the most important, as you will learn at the end.
“Disagreement between traders creates markets,” you write. Is this an example of noise?
In the markets, some people think that a certain stock will increase; others think this is not the case – and this is part of the [process]. In terms of noise, we are concerned about unwanted variability [judgments that should be identical], which is not good.
“We are really focused on reducing bias. Let us also be concerned with reducing noise, ”the three of you write. What’s the difference between bias and noise, besides what you just mentioned?
With prejudice, there is a tendency to go one way or another that is really predictable. But when you step into a noisy system, you are entered into a lottery. Bias overvalues the present and undervalues the future. If a person is overly optimistic about how the economy is going to develop, that is a bias.
If you work in a company where some people discriminate against men and others discriminate against women, these different biases will result in noise, where “different” people will be. treated differently.
Where else is the noise occurring?
In a hospital, if some doctors say, “Let’s wait and see if it gets better” and others say, “You need surgery.” Or if a doctor concludes in the morning that a person has a serious illness and probably should undergo extensive testing, but in the afternoon, if tired, decides to suspend testing for six months, that’s a noisy doctor. In a system where the judges are very variable and one says “five years in prison” and the other says “probation”, it is a noisy legal system.
Does this type of noise also apply to inanimate objects?
Yes. A scale that is sometimes five pounds too high and sometimes five pounds too low is noisy. If you believe in this scale, you will be extremely confused about your weight. A noisy scale can mess up your consumption pattern, even if the average is accurate.
Your book focuses a bit on forecasting. Research by psychologist Philip Tetlock suggests that “detailed long-term predictions of specific events are simply impossible”, but “super-predictors” can predict short-term events of less than a year, you write. . Please discuss their superior talent for thinking analytically and probabilistically.
Superforecasters are quieter – they don’t show the variability the rest of us do. They are very intelligent; but also, very importantly, they do not think in terms of “yes” or “no” but in terms of probability. They break problems down into their components and don’t think holistically.