, Business

Economics 101 typically begins with the theory of the firm and, more specifically, a perfectly competitive market. This market is characterised by demand equalling supply, the cost of producing one extra unit of a good equalling the revenue added from selling the good. There is no one dominant company and prices are at a level where people can afford them. It looks like a utopia, and as such, there are no real examples of a perfectly competitive market.

Yet students are taught this basic model as a means, perhaps, of introducing these young abecedarians to modelling human behaviour through simplification. Economic models typically have a caveat to all its models – ceteris paribus, or all other things being the same – in order to deconstruct the markets and attempt to explain them. But this simplification paradoxically reveals the upmost complexity of the economics subject. For economics is not a subject that can be defined by fixed laws; rather it is an endeavour to explain human behaviour and human behaviour is not the most precise of sciences.

Nevertheless economics is being billed as a science. Indeed, undergraduate students are expected to have a decent grasp of statistics before embarking on the course rather than an understanding of economic concepts. Even a rigorous economic degree is consumed by a focus on statistics. The reason for this is to explain human behaviour in any given context; correlations should identify trends and trends should enable policy makers to determine how best to allocate resources. Consequently, just as any of the physical sciences – physics, biology, and chemistry – progress through experimentation and observation, it is assumed economics should embrace this course.

Rationally, this is a fair justification for the usage of statistics because human behaviour can be gleaned somewhat though percentages. How often do we see some survey and be impressed by its results and anticipate the conclusions. But every survey, every data set is weakened by the fact that it is a sample of a population. It is difficult to conduct a comprehensive survey and far easier to rely on a representative sample.

Once again, this is all good and well, until and when people rely on the results to produce comprehensive conclusions. In many regards there is often a blinkering arrogance to economist conclusions. To assume future behaviour will represent past actions is a path to eventual trouble. One just has to look at the financial crisis as an example. Another weakness of statistical analysis is the assumptions and choice of technique made by the researcher in analysing the data set; the same data set can result in differing conclusions. For instance, today there is a debate as to whether microfinance is as effective as its supporters claim it to be.

The overemphasis on statistical analysis can also be seen with the countless analysis looking to explain the markets. The average equity analyst will be explaining to clients how they see the market or a particular stock performing over a given time scale. The satisfied client might invest more into a particular asset comfortable in the analyst’s predictions garnered from much research. But suddenly a thunderbolt hits the market; the stock does not perform as well, and the client is caught unawares.

Thus, there is usually some caveat in any prospectus or research that the conclusions are opinions not facts, and hence any investor has to be careful in his investment. In the end, all an analyst or economist can do is to give a reasoned justification for his opinion through the methods of analysis he utilises. He is always limited by the tangible uncertainties of human behaviour. There is always a black swan somewhere.

And this is what makes economics perhaps one of the most complex subjects taught. Human behaviour can only partially be quantified; it is by no means an exact science. Its complexity was recognised by no less a figure as John Maynard Keynes, who gave the example of a brilliant physicist he knew who was more comfortable with the tangibles (if one can call it that) of physical laws than the randomness of human behaviour. The physicist in question could have solved the mathematical dilemmas of economics, but economics on the whole is not maths.

For the great economists, people like Smith, Marx, Keynes, Minsky, Hayek and others, the ones we still read today, their most important facet was their acute observations of the human condition. That the human condition cannot be deconstructed into a series of numbers was something understood then, but is being forgotten. Rather economists are essentially philosophers (now considered a fluff subject) seeking to explain the human condition. When Keynes speaks of increasing government spending in times of recession, he is in fact talking about how to incentivise people to act; when Marx talks about the conflict between bourgeoisie and the proletariat, he is describing the feelings of inequality that can grow and manifest itself with dangerous results.

The human condition is made up of more than just economic value; it is a product of history, moulded by society, motivated by desire, and limited by law. Economists then have to be historians, sociologists, psychologists and lawyers. This is in an addition to having some ability in statistics; however relying on the numbers on a screen to generate conclusions is a massive disservice to the essence of the subject. To overemphasise the numerical aspect of the subject has slowly led to the notion that economics is a dismal science. Instead the subject is more than that, certainly more complex than the formulae Nobel Prize winners put on their sheets of paper. To realise how skewed the understanding of economics has become, one only has to look at the winners of this prestigious prize. Just ask yourself one question: Why did Muhammad Yunus win a Nobel Prize for Peace, when what he produced was an economic idea? Maybe because it was not mathematical enough.

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