Physicists have a new, maybe better way to predict GDP

See Physicists’ simple spanks economists’ complex in economic growth forecasts: Take economic ideas, add a touch of dynamics, get accurate GDP predictions by Chris Lee, a physicist who writes for Ars Technica.

The main idea seems to be using "economic fitness" to predict a country's future GDP (along with past GDP). Fitness means that a country has a wide variety of exports. If the rest of the world likes many of your products, that might mean your economy is "fit" or in good shape. Maybe that means that no matter what happens in the world economy, your country will usually have something other countries will want to buy. Excerpt:

"Applying physics to economics

The economy is a bit different from many physical models, though: there is no complete model of an economy. There isn’t even a good approximate model. Indeed, simple models that provide insight do not offer predictions. Instead, predictive models are statistical in nature. These make use of historical economic data to predict future economic data—essentially, the model looks for correlations between historical and recent data. These correlations are then used to take current economic data to predict future economic data. The model is then constructed from our understanding of how the measured data relates to economic activity.

The problem with this approach is that, if you don't have sufficient data, predictions quickly become inaccurate. To resolve this problem, we collect more information. That information allows new processes to be included in the model with the hope that this will yield increased accuracy over longer time intervals. And this certainly works: current models are better than older models.

To improve on predictive models about the economy, researchers took a counterintuitive approach. They reduced the number of parameters in their model to just two: economic fitness and gross domestic product, the idea being that if the economic fitness and GDP are measured at a given time, then the change in GDP can be predicted.

So what is the economic fitness? It is, in short, a measure of the complexity of a country’s exports. The idea is that exports represent the products from a country that are competitive with like products from the rest of the world. The larger the variety of exported products, the fitter an economy is. One advantage of it as a measure is that exports and imports are very carefully measured, because companies rely on that data to survive. And that data is collected and reported in a relatively standardized way. The researchers basically created a matrix that allows the variety of exports to be summed.

This number is then iteratively normalized with data from all other countries to come up with a self-consistent scale of economic fitness. Economic fitness drives changes in economic growth, which is accounted for in GDP.

Now, it is important to realize that no one really has a model (in the physical sense) of the link between economic fitness and GDP. But we do have statistical data that can be used to infer how the two are linked. We can estimate from the averages in the dataset how high the economic fitness of an economy has to be to support a given GDP and use that to determine if the GDP will increase or decrease.

The speed of the increase or decrease is estimated using a kind of force-response model. In other words, if the GDP is far away from that expected from the current economic fitness, there is a strong hidden economic drive to change the GDP. Hence, we can expect rapid economic growth (or contraction).

Predicting the past

This case is exemplified by China in 1995. China at that time had a low GDP but high economic fitness. As predicted by the model, China experienced 20 years of steep economic growth, with its GDP increasing remarkably. In a standard economic analysis, this seems extraordinary. But, the researchers argue that this is actually expected behavior: much like a stretched spring being released to jump back to its position.

The model also allows economic momentum to play a role. The speed at which economic fitness is changing also influences the change in GDP. The researchers found that using the trajectory of economic fitness to predict GDP leads to even more accurate results.

The researchers tested their model on historical data from 169 countries over three different five-year windows. They compared their GDP predictions with those produced by the international monetary fund (IMF) model and with the actual GDP data.

They found that their model was better than the IMF model, especially when they also took into account the trajectory of the economic fitness. Furthermore, a close analysis of how the IMF model and their dynamical model predictions differed showed that the sources of inaccuracy were different. That meant that combining the two models led to predictions that were even more accurate.

Another important factor is that there is a kind of self-similar behavior in trajectories. Even though the total size of the economy might be different, countries with similar ratios (I’m simplifying here) of economic fitness to GDP experienced similar trajectories. And a final point: the model also shows where predictability fails. Countries with a very low economic fitness are incredibly difficult to predict. This is true of both the IMF model and their model, but it highlights that the poorer you are, the more subject you are to the random buffeting of economic noise."