Why do economists have an abysmally poor prediction record?

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Its true that economists have an abysmally poor prediction record. Before explaining why lets have a quick look at how abysmal.

The Economist magazine have a database of projections by banks and consultancies for annual GDP growth. It stretches back 20 years and now contains 100,000 forecasts across 15 rich countries.

Unsurprisingly they found that forecasts tend to fare well over brief time periods, but got worse the further analysts peered into the future. If a recession lurks beyond 2019, economists are unlikely to foresee it this far in advance.

Projections made in early September for the year ending four months later missed the actual figure by an average of just 0.4 percentage points. Errors rose to 0.8 points when predicting one year out. But over longer horizons forecasts performed far worse. With 22 months of lead time, they misfired by 1.3 points on average—no better than repeating the previous year’s growth rate.

The most likely outcome is growth – economies usually expand slowly and steadily so its reasonable to forecast this. But sometimes unfortunately economies contract sharply…

…and this means the biggest forecasting errors occurred ahead of contractions. The average projection 22 months before the end of a downturn year missed by 3.7 points, four times more than in other years. In part, this is because growth figures are “skewed”: economies usually expand slowly and steadily, but sometimes contract sharply. As a result, forecasters seeking to predict the most likely outcome expect growth.

So why are they so abysmal?

Well, first the economy is a complex system full of positive and negative feedback loops. And so it doesn’t necessarily follow that a change in one part of the economy (say a cut in interest rates by X) would automatically lead to an improvement of Y elsewhere. Its non-linear.

“Nobody has a clue,” Jan Hatzius, Goldman Sachs’ chief economist, said to Nate Silver in the book “The Signal and the Noise”. “It’s hugely difficult to forecast the business cycle. Understanding an organism as complex as the economy is very hard.”

According to Hatzius, forecasters face three fundamental challenges: first, it is very hard to determine cause and effect; second, that the economy is always changing and, third, that the data that they have to work with is pretty bad.

Second, economic forecasters of all stripes are prone to the same biases. They are prone to recency bias (thinking the current trend will continue), availability bias (only considering salient data and insights) and confirmation bias only seeking out information that confirms their worldview).

Finally, they are all subject to different incentives. And the main one is whether to herd, or not to herd. If a forecaster strays too far from the consensus forecast and turns out to be wrong they may lose their job or be passed over for promotion.

As the great investor Warren Buffet said, “Forecasts usually tell us more of the forecaster than the future.” Forecasters are too busy looking in the rear view mirror and looking across at their competitors to provide an unbiased forecast of the future.

Related article: Financial market forecasts: How to avoid buying a lemon

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