Why So Many Predictions Fail — but Some Don't
The Signal and the Noise by Nate Silver explores the art of prediction and the challenges that come with it. Using real-world examples, he emphasizes the importance of gathering accurate information and separating signal from noise.
Will you walk to work today or take the bus? Will you take an umbrella or not?
In our everyday lives, we make decisions based on predictions of what will happen in the future, like whether it will rain or shine.
But predictions are also common in the public realm: stock market analysts, meteorologists and sports commentators all make a living out of them.
One area where one might expect particularly good predictions is the economy. After all, it’s of crucial importance for individuals, companies and even nations, and there’s a wealth of data available: some companies track as many as four million economic indicators.
But despite these factors, economists have an atrocious track record in forecasting.
Consider the commonly predicted economic indicator, the gross domestic product (GDP).
The first problem with GDP predictions is that economists often make predictions like “Next year, GDP will increase by 2.7 percent.” In fact, they’ve derived this figure from a broad prediction interval that says something like “It is 90 percent likely that GDP growth will fall somewhere between 1.3 and 4.2 percent.” So an exact number as a prediction is misleading, as it gives a false sense of precision and security.
What’s worse, economists aren’t actually very good at coming up with prediction intervals either. If their 90 percent prediction intervals were roughly accurate, one would expect the actual GDP to only fall outside the prediction interval one out of ten times. However, a poll of professional forecasters shows that, since 1968, they’ve been wrong roughly half the time. Therefore, it seems that economists’ are not only poor predictors but also gravely overestimate their predictions’ certainty.
Besides GDP predictions, economists are also spectacularly bad at forecasting depressions. Consider that, in the 1990s, economists were only able to predict two out of the sixty depressions that had occurred worldwide one year ahead of time.
To put it kindly, economic predictions should be taken with at least a grain of salt.
The Signal and the Noise explains why so many expert predictions today fail spectacularly, and what statistical and probability tools are more up to the task of predicting real-world phenomena.
If political scientists couldnt predict the downfall of the Soviet Union – perhaps the most important event in the latter half of the twentieth century – then what exactly were they good for?
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Blink 3 von 12 - Eine kurze Geschichte der Menschheit
von Yuval Noah Harari
