The thing about the Aristotelian world-view, as perfected later by Claudius Ptolemaios, is this — and they don’t talk about it much — for predictions of planetary positioning on the night sky, it’s really accurate. I wanted to say this first, to get to the point, through a round-about point about economics and Scotland at the end of this long post.

When the Copernican model of the universe was proposed by Nicolaus Copernicus, the Earth centric model was far more accurate than the Copernican one. The Aristotelian one was more complex to calculate, yes, but it was more accurate.

If your intention was to map the seasons for harvests, or position your ship on a map using the stars, then clearly anything that was less accurate was bad. In those cases, the Copernican model was a degradation of usability. A large part of the resistance against Copernicus ideas was that it was less useful.

But, here’s the thing. As an explanation of how the heavens worked the Aristotelian model was utterly bonkers. It wasn’t correct in any shape or form. The Aristotelian model required that the planets were fixed to perfect spheres made of crystal, and oddities in orbits were explained that each sphere had extra, mini spheres attached to them. To accurately account for the movement of stars and planets, one had to account for dozens of spheres, mini-spheres, and so on.

And comets and meteorites? Those were atmospheric phenomena, not space-based ones. They were signals and omens, bringing bad tidings — not features of the universe model itself. The heavens were perfect, the Earth not so, and breaks with order and beauty was caused by the corruption of the Earth. The model calculations were complex and time-consuming. But its predictions were accurate. It could be accurate because the universe moves in a linear fashion. Objects move at a set speed in a set direction.

Nicholas Copernicus proposed his heliocentric model in the 16th century. It would take hundreds of years, and the work of scientific giants like Galileo, Kepler, and Newton before the heliocentric model caught up, in accuracy terms, with the Aristotelian one. Without knowledge of elliptical orbits, gravity, and so on — the Copernican model introduced errors in the calculations.

Therefore, before Galileo Kepler and Newton, it was entirely rational for people to point to proponents of heliocentrism and say “What? Are you mad? Your calculations are way off here. If we went by these numbers, we’d start to plant seeds at the time of harvest, and any ship that used these charts would end up on a rock in Iceland when sailing to Africa.”

So, with that out of the way as an explanation for what I’m about to say. Statistics and data on its own are rarely useful. Data needs a model it can be slotted into. Data is rarely useful if there’s not a model attached. It becomes meaningless noise. Models can be utterly wrong, yet give useful predictions. And sometimes the predictions can be useful because they are assumed to be useful. What you get out of the model depends on the questions you ask of the data, and the assumptions you make in creating the model to represent the data.

Like, pollsters take hundreds of entries, and then create elaborate models based on those entries, using weighting and demographic data to try to come up with a snapshot view of a particular electorate. Then the collected statistics is massaged to the model to attempt to answer a specific question. Whether the predictions are, actually, objectively useful or not depends on the value we attach to the predictions. This is why it’s dangerous that polling is so prevalent, because without knowledge of the models the data is near meaningless. This is the reason why the pollsters got is so wrong in the last election: their demographic models were wrong, and the data fed into the model gave the wrong result. Garbage in, garbage out, in other words.

Like pollsters, Economists create models that they hinge their data to. These models are based on perceived equilibrium states within an economy. It’s a nation’s economy frozen as a specific instant, at a point where the economy is tought to be in a state of equilibrium. Yes, even the schools which objects to the Neoclassicals equilibrium states operate on those equilibrium states because they obsess over trying to undermine them, or to find another state at which to freeze an economy.

Again, those states are snapshots if you will, that they can apply statistical data to. Much of the perceived value of the predictions, and the requirement to act on the predictions, depend on the value attached to the questions. Assumptions about the predictions drive action, and therefore assumptions can be drivers for action. Like push-polling which is designed to cause a specific outcome politically. Economists’ predictions are often wrong.

And this is where things become iffy, and if you’re like Professor Steve Keen of Kingston University in the UK, you start to suspect that macro economists are really Aristotelians peddling a geocentric model when the economic universe is in fact heliocentric.

Economists can make predictions. Sometimes accurate ones. Like the Aristotelian model, economics can be accurate, up to the point where something unusual happens. As with the oddities of space such as meteorites and comets and the Jovian moons, it is when models go wrong that they are revealed to be barking. One could say that for macro economists, the state of the global economy is like the months and years immediately after Galileo turned his new telescope to Jupiter and asked the Aristotelians to explain the Jovian moons, and the craters on the moon.

It doesn’t really matter if you’re a Neoclassical economist, a Keynesian, a post-Keynsian, a MMT-adherant or an Austrian. Once you start to dig into how the models look, they all appear to make assumptions which can’t be adequately explained, or even accepted. This is true of the assumptions of IFS, of OBR, of the BoE, and of GERS. Scotland’s and the wider UKs economy may be built on crystal spheres within crystal spheres just so that phenomena in the economy can be explained. Usually the predictions are accurate, but now the predictions are wildly off-track because the underlying model is mad.

These models are built on guesswork, derived by looking at an opaque black box of contradictions and processes, trying to derive mathematical formulae of inner workings one can’t see. Hell, members of the Austrian school have even thrown up their hands, and forswear the use of models altogether, and claim that the economy can’t be quantified at all.

I can use the Austrians to illustrate the attitude of all the different macroeconomic groups. They like to embrace Friedrich Hayek, but haven’t read what he actually wrote, or they ignore what he actually wrote because it’s too hard. They think that he rejected the use of models in economics, and that their ‘praxeology’ is actually supposed to establish the logic of not using maths. This is as crazy as using models based on equilibrium states in the other schools.

What Hayek actually suggested was to use the economic equivalents of the work that Edward Lorenz did in meteorology. Lorenz thought that the underlying mechanics of weather was that of a chaotic system, and therefore one couldn’t use the linear statistical models to make predictions. Thinking about how to predict weather, Lorenz ended up inventing chaos theory. Hayek had the same epiphany about economics and concurrent with Lorenz he wrote about the complexity of dynamic systems like economics. His followers took that work as a rejection of mathematical models altogether.

I have always been sympathetic to Hayek’s view in this. Not in much else, but in this. I think he was on to something. I don’t have the foundation in maths to make a statement one way or another, but it seems clear that a society of individual actors making individual decisions based on incomplete data is the classical definition of a complex or chaotic dynamic system that require a non-linear approach rather than the linear statistical models of frozen ideal states that the macroeconomic schools use now.

Unfortunately that flies in the face of every leading academic school of Economics, who want to use linear statistical models. Whether you’re a Krugmanite, a Pikettyan, a Hayekian, or a Wren-Lewisian, there’s the Earth-centric economic model, there’s the linear data, there’s the economy frozen at an arbitrary thought equilibrium. Have at it, and make predictions which will come back to bite in five years time.

So, maybe people should stop beating each other over economic data and realise that since the model could be wrong, we should all treat economics with suspicion. Because maybe macro economists are the Aristotelians trying to dodge questions about the moons around Jupiter, or about the surface of the moon not being the perfect unblemished sphere that the model says it should be.