Yesterday, I wrote about a brain teaser in probability and statistics that shows how we are not well-equipped as humans to intuitively grasp probabilities in a realistic setting. The example I used was two experts making two different point forecasts for inflation and then the Minister of Finance combining these two forecasts to make a forecast that was higher than all the existing forecasts.
I agree that assigning probabilities to particular scenarios is an improvement, but it is far from being a panacea. It can give an impression of faux certainty, that all possible outcomes are knowable in advance and have been captured by the forecast. The danger with faux certainty is that it might lead market participants to believe something is more likely than it actually is.
One of the biggest problems with point estimates is too many significant digits - using precision to give the appearance of accuracy.
At least one more question for the Finance Minster to ask the two economic experts - are their estimates based on a uniform distribution or a normal distribution? Lots of followup questions: mean, median, skew, kurtosis…?
Probability by itself is hard and not intuitive. But probability, statistics, economics and politics mixed together is a very complex cocktail. Many of those (USA, Europe, etc.) that help with the economic forecast, influence policy and thus always have a political angle (do not let the truth get in the way).
In 1990, a (simple bayesian) problem was presented in a Sunday supplement Parade magazine. It was presented as a Monty Hall "Let's Make a Deal" TV contest wherein the contestant must guess which of the 3 doors had a car prize behind it. If the contestant selected door A at first, and the host opens door C to reveal a goat, should the contestant switch to door B given the chance?
The column was written by a beautiful, stylish woman Marilyn vos Savant (at the time she was the Guiness world's smartest woman per intelligence tests but had no formal 3 letter hangups after her name). She wrote that the contestant should always switch.
Guess how many donkeys (from Paul Erdos and other math mainsplainers, including from some respected universities in the USA) wrote to disparage her? Per Parade records, around 10,000 nationwide letters for Marilyn came in with about 1,000 from PhDs in math and statistics!!!
The lizard part of the brain cannot intuitively grasp probabilities even when those who are responding were supposed to know the math. Even if we account for sexism, pride and prejudice, it is way too high a number of mathematicians to reject the higher probability choice.
Now extend that to the scenario of forecasting economic direction to the masses amidst a stressful pile of Covid-19, monkey pox, Ukraine and inflation.
What really happens is that if a charismatic politician (e.g. a believable Minister of Finance) says something, at least half of the audience will not think independently and just take it for what it is and sometimes it becomes self-fullfilling prophecy. So it does not matter much that the forecast is not so accurate, as long as it comes across as believeable, like Hari Seldon's deal on "psychohistory" in Asimov's novels.
Experiments has shown that the functional MRI of the frontal cortex of a congregation listening to a charismatic preacher was basically inactive or at rest. Perhaps it was partly how in the 1940s the "emperor of the sun" from Asia, and a psycho with a funny mustache in Europe, convinced thousands to follow them, without even needing Twitter.
I agree that assigning probabilities to particular scenarios is an improvement, but it is far from being a panacea. It can give an impression of faux certainty, that all possible outcomes are knowable in advance and have been captured by the forecast. The danger with faux certainty is that it might lead market participants to believe something is more likely than it actually is.
So true!!!
One of the biggest problems with point estimates is too many significant digits - using precision to give the appearance of accuracy.
At least one more question for the Finance Minster to ask the two economic experts - are their estimates based on a uniform distribution or a normal distribution? Lots of followup questions: mean, median, skew, kurtosis…?
Probability by itself is hard and not intuitive. But probability, statistics, economics and politics mixed together is a very complex cocktail. Many of those (USA, Europe, etc.) that help with the economic forecast, influence policy and thus always have a political angle (do not let the truth get in the way).
In 1990, a (simple bayesian) problem was presented in a Sunday supplement Parade magazine. It was presented as a Monty Hall "Let's Make a Deal" TV contest wherein the contestant must guess which of the 3 doors had a car prize behind it. If the contestant selected door A at first, and the host opens door C to reveal a goat, should the contestant switch to door B given the chance?
The column was written by a beautiful, stylish woman Marilyn vos Savant (at the time she was the Guiness world's smartest woman per intelligence tests but had no formal 3 letter hangups after her name). She wrote that the contestant should always switch.
Guess how many donkeys (from Paul Erdos and other math mainsplainers, including from some respected universities in the USA) wrote to disparage her? Per Parade records, around 10,000 nationwide letters for Marilyn came in with about 1,000 from PhDs in math and statistics!!!
The lizard part of the brain cannot intuitively grasp probabilities even when those who are responding were supposed to know the math. Even if we account for sexism, pride and prejudice, it is way too high a number of mathematicians to reject the higher probability choice.
Now extend that to the scenario of forecasting economic direction to the masses amidst a stressful pile of Covid-19, monkey pox, Ukraine and inflation.
What really happens is that if a charismatic politician (e.g. a believable Minister of Finance) says something, at least half of the audience will not think independently and just take it for what it is and sometimes it becomes self-fullfilling prophecy. So it does not matter much that the forecast is not so accurate, as long as it comes across as believeable, like Hari Seldon's deal on "psychohistory" in Asimov's novels.
Experiments has shown that the functional MRI of the frontal cortex of a congregation listening to a charismatic preacher was basically inactive or at rest. Perhaps it was partly how in the 1940s the "emperor of the sun" from Asia, and a psycho with a funny mustache in Europe, convinced thousands to follow them, without even needing Twitter.