Once upon a time some men decided to play a con trick on the Emperor. So they told the emperor that in exchange for only a mildly exorbitant fee they would produce the greatest econometric model in the world (after all you can’t spell econometric without con or tric). The Emperor agreed but instead of creating an econometric model, the consters merely covered pages and pages with random letters and obscure symbols. Eventually the conmen decided to present their model to one of the Emperor’s advisors. They told him that it was an econometric model of such complexity that only the wise could understand it, to the uneducated it looked like random symbols. The advisor who knew little economics, pretended to read it before agreeing with the conmen about its sophistication.
Next the conmen went to the Emperor’s economist. He was a busy man and didn’t have time to pour over the tiny details so he read the abstract and didn’t see anything amiss. To be honest he didn’t quite understand it, but he wasn’t going to admit this and risk damaging his career out of ignorance. And so the model got passed to all of the main economists and advisors of the Emperor. Not a single one could understand it, but all presumed this was due to their own lack of mathematical knowledge. After all, didn’t the men say that only those who didn’t understand maths would be confused and only the wise could read it? And hadn’t everyone signed off on it and agreed on how great a theory it was? There was no point in standing out from the crowd and revealing your lack of understanding, better still to stay quiet and go along with it.
So the conmen reaped a huge reward in terms of gold, silver and academic tenure. Even the Emperor was impressed and complemented the men on their fantastic model (not that the Emperor read or understood it, but if none of his advisors complained then there mustn’t be any problems). So the Emperor strolled through the streets of the Empire covered only with the mathematical beauty of his econometric model. None of the ordinary people understood what was going on, but if very serious looking people from very serious sounding institutions agreed, then it must be good. A few people pretended they understood the model and praised its complexity while the rest felt stupid and remained silent.
It was not until a boy, an economics college student to be exact, shouted out, “The model doesn’t make any sense, it’s only a load of gibberish and random symbols!” All the Emperor’s advisors tuttered at this outburst. “He’s clearly not smart enough to understand. Should have paid more attention in class. Sure the model isn’t perfect but it is a useful approximation.” And so the very serious people in their very serious suits scoffed at those who doubted the Emperor’s new model.
The Emperor’s New Clothes is a nice fairytale that has a lot of relevance for the way economics operates. You see economists place a heavy emphasis on econometrics. You can hardly publish a paper in the leading journals with including several pages of difficult maths and Greek symbols. It is no longer good enough to simply explain economic issues; you must also mathemathise it too. And if you don’t like the use of maths? Well that’s probably because you are not smart enough to understand it. However, the obsession with precise formulations has led economists in the wrong direction and meant most were blind-sided by the financial crisis.
The fundamental problem with econometrics is that it tries to fit a square peg into a round hole. In order to build a mathematical model you must be dealing with events that are predictable and consistent, that you can easily compile data on. If on the other had people are not rational then it becomes far harder to mathemathise their actions. If the economy was composed solely of computers, then econometrics would be fantastically accurate. Unfortunately, it is composed of humans in all our irrational and illogical glory. The only way you can build econometric models is by creating gross simplifications that bare only a slight resemblance to the real world. Secondly, the fall of the Soviet Union showed how incredibly difficult it is to measure all the aspects of the economy. Many economists concluded that it was impossible to do.
The strange thing is that many economists actually agree that the use of mathematical models is flawed. However they say that such simplification is necessary because at least it provides answers. A common saying is that “all models are wrong, but some are useful”. Econometrics is preferred because it allows economists give precise answers rather than make rough guesses. For example if the government wants to raise the tax on petrol, rather than saying this will reduce demand, econometrics allows economists to give an exact measurement of how much demand will fall.
However, the problem with using unrealistic foundations is that while it may give you an exact answer, the answer may be wrong. As the saying (attributed to Keynes) goes “it is better to be roughly right than precisely wrong.” So econometrics may produce impressive jargon and realms of statistics about how markets are efficient and a financial crash is impossible, but that is little good when reality contradicts maths. Econometric models are only as good as their assumptions and the data they use. So while it makes things easier to assume the market is efficient and to only use the data from the last decade this meant economic models were blissfully unaware of the idea that the financial crisis could occur. Econometric models presume that all events can estimate, predicated and given an accurate probability function. If only the word was so. In reality most of the future is unknowable and attempts to predict it are almost always inaccurate. Uncertainty has dominated much of the financial and housing markets over the last number of years as people have no idea what the future state of the market will be or are unwilling to act upon it.
The simple fact about human life is that there are many aspects that cannot be shoved into an equation. Issues such as trust, co-operation, uncertainty, tradition and a host of social norms and heuristics guide how we interact with other. However, as these cannot be mathemathise they are treated as if they do not exist. This reminds me of the story of a man who was walking through a park when he came across a second man searching on the ground underneath a street light. The second man explained he was looking for his keys, so the first man decided to help him. After several minutes searching without luck, the first man asks if he is sure he lost his keys here. The second man replies “No, I lost my keys in the bushes, but the light is much better here”.
I have a great love for economics but its obsession with mathematics is its greatest flaw. Most people are driven away from economics because they cannot understand the gibberish they must learn. I don’t think any of us have ever come across a situation where a Cobb-Douglas function or a lagrangian would come in handy. As a result it is only the people who like and/or are good at maths that stick with it, become economists and write economic courses. If you read an economics journal it is almost mandatory to plough through pages of unintelligible gibberish that might as well be Japanese. I have a theory that some of the authors don’t even understand it and pulling a prank to see how gullible the rest of us are.
Econometrics fails on its own term of being precise and scientific. For example, I know of no economic debate that has been solved by use of econometrics. Even some of the main issues in econometrics in which hundreds of articles have been written over the years, we are no closer to a consensus. For example, what is the benefit of education or is discrimination present in the labour market? Econometricians cannot find an acceptable answer. Every time a study is performed, it is criticised for missing variables, having unrealistic foundations or using questionable data. No sooner is one study complete than another is done which gets different results. Thus econometrics fails on its own level of providing scientific results. It is incredibly difficult to replicate the results of an econometrics result and all are heavily dependent on the assumptions made.
It seems unlikely we will ever know the returns of education. Any given study can easily be dismissed due to its flaws. Perhaps they use poor data (an unfortunate feature of economics education is that it teaches students how to interpret data but not how to gather it). Or they treat all levels of education the same as though a year of primary school is the same as a year of college. Or that all colleges were the same or all courses or all teachers. Either way econometrics fails at its task of being a precise science, because no matter how mathematically impressive the methodology may be, it conclusions are no convincing than an argument from words alone.
Likewise econometricians have been struggling for years to find out whether or not racism is present in the economy. It is clear that black workers get paid less than white workers in America but is this due to racism? Econometricians try to measure this by adding controls, the only problem is that if you add enough controls you remove all differences and end up comparing two identical models and finding no difference. Furthermore econometrics is based on the assumption that the variables are independent. But racism takes more than one form. So when econometricians find that the difference in wages can be explained by geographic or educational or even occupational, they may conclude that racism isn’t present. But what if racism affects these issues and black people suffer from poorer education, live in ghettos and are excluded from certain issues? We could end up looking at a restaurant where all the well paid chefs are white and all the badly paid servers are black and conclude that no racism is present.
I’m not suggesting that we burn our computer models or econometrics is useless. Rather I see myself as a mathematical sceptic. Maths should only be used as a last resort when it has something to contribute to the debate and helps explain the issue. Too often mathematical jargon is used smugly to add to the illusion of intelligence and to swat off criticism. Too often it is used to obfuscate rather than illuminate and muddle rather than clarify. In a way it resembles abstract art, few can understand or explain it and they look condescendingly on the rest of us while we fail to distinguish the difference between it and random, meaningless scribbling. We need to admit that the Emperor has no clothes and bring economics away from the siren call of mathematical elegance and back towards the rough but rewarding seas of reality. We should focus on the problems that matter not the ones that are easiest to deal with.