Home > Uncategorized > Economic forecasting — why it matters and why it is so often wrong

Economic forecasting — why it matters and why it is so often wrong

from Lars Syll

oskarAs Oskar Morgenstern noted 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 underline 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. To 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.”

treatprobHow strange that social scientists and mainstream economists, as a rule, do not even touch upon these aspects of scientific methodology that seem 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’s 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 year 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. Gerald Holtham
    February 6, 2023 at 6:56 am

    If you study OECD forecasts you notice two different regimes. In an average year when no unknown unknowns crop up, no geopolitical crises, the forecasts aren’t magic but they are generally within a percentage point or so of the GDP out-turn. When something happens, like an oil-price shock or a big policy mistake, that causes a pronounced cycle, they get the turning points wrong, by as much as 3 or 4 percentage points of growth. Well, c’est la vie, all forecasts are conditional but here’s the silly part: when examining their own performance they average their errors, mixing errors from the two regimes. They then publish fan charts showing confidence intervals for the forecast. This will have an average error of barely 2 per cent or so and imply that the chances of a 4 per cent error are tiny. Ok most of the time but of course come a big shock and the GDP outcome goes outside the fan.
    Lars would call that a case of trying to apply probabilities to uncertain situations and I suppose he would be right. But the forecasters could do a lot better if they acknowledged two regimes and said the fan chart was applicable to only one of them.
    Morgenstern was a great man but writing before economic data like national accounts were invented, never mind collected. He was also writing before the electronic computer had been invented. He would no doubt have said the same of weather forecasting, which has improved enormously since his time. Economics? Not quite so much because too many economists think real-world data are just an uninteresting special case of the abstract world they want to model. That’s not harmless when they impose their “results” on supposedly empirical work.

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