Is economics — really — predictable?

9 Jan, 2020 at 14:54 | Posted in Economics | 2 Comments

oskarAs Oskar Morgenstern noted already back in his 1928 classic Wirtschaftsprognose: Eine Untersuchung ihrer Voraussetzungen und Möglichkeiten, economic predictions and forecasts amount to little more than intelligent guessing.

Making forecasts and predictions obviously isn’t a trivial or costless activity, so why then go on with it?

The problems that economists encounter when trying to predict the future really underlines how important it is for social sciences to incorporate Keynes’s far-reaching and incisive analysis of induction and evidential weight in his seminal A Treatise on Probability (1921).

According to Keynes we live in a world permeated by unmeasurable uncertainty – not quantifiable stochastic risk – which often forces us to make decisions based on anything but ‘rational expectations.’ Keynes rather thinks that we base our expectations on the confidence or ‘weight’ we put on different events and alternatives. treatprobTo Keynes, ​expectations are a question of weighing probabilities by ‘degrees of belief,’ beliefs that often have preciously little to do with the kind of stochastic probabilistic calculations made by the rational agents as modelled by ‘modern’ social sciences. And often we “simply do not know.”

How strange that social scientists and mainstream economists, as a rule, do not even touch upon these aspects of scientific methodology that seems to be so fundamental and important for anyone trying to understand how we learn and orient ourselves in an uncertain world. An educated guess on why this is a fact would be that Keynes concepts are not possible to squeeze into a single calculable numerical ‘probability.’ In the quest for measurable quantities, one puts a blind eye to qualities and looks the other way.

So why do companies, governments, and central banks, continue with this more or less expensive, but obviously worthless, activity?

A part of the answer concerns ideology and apologetics. Forecasting is a non-negligible part of the labour market for (mainstream) economists, and so, of course, those in the business do not want to admit that they are occupied with worthless things (not to mention how hard it would be to sell the product with that kind of frank truthfulness). Governments, the finance sector and (central) banks also want to give the impression to customers and voters that they, so to say, have the situation under control (telling people that next years x will be 3.048 % makes wonders in that respect). Why else would anyone want to pay them or vote for them? These are sure not glamorous aspects of economics as a science, but as a scientist, it would be unforgivably dishonest to pretend that economics doesn’t also perform an ideological function in society.


  1. The only uncertainty for players like JP Morgan and Goldman Sachs is whether the Fed will backstop them in a panic.
    See a recent Nomura note
    “we desensitize to headlines and short volatility knowing that we are backstopped”
    Financial uncertainty is purely psychological, and the Fed can easily fix it by supplying liquidity on demand. When will economists figure this out?

  2. Governments have to try and steer the economic ship. Some kind of forecasting is better than none. If you give up on forecasting you are essentially saying Governments have no responsibility for economic performance. A lot of private sector forecasting is to second guess Government policy to make money.

    Some forecasts are easier than others. Europe will probably have disappointingly low growth, at best, for the next five years. This is a safe bet based on current fiscal and monetary policy in European countries and the long lead times required to change policy in those countries. In the unlikely event of effective growth policy being implemented across Europe tomorrow it would still take years to have an effect.

    Given the fact that you can’t predict the future the correct response is to more accurately measure what is going on now and adapt policy to react faster. Bring down the cycle time of your OODA Loop. This should be the focus for economic reasearch but sadly it isn’t currently.

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