by Why economists can’t forecast The problem of evaluating models built for forecasting is that one cannot get around invariance. There must be a stable bridge that connects the past and pres. ent with the future … To evaluate invariance its domain should be considered. In other words, one has to investigate what the list of all relevant non-negligible potential influences is. To ensure invariance, this list should be complete. This latter point was also emphasised by John Maynard Keynes when he was criticising Tinbergen’s econometric method: “Am I right in thinking that the method multiple correlation analysis essentially depends on the economist having furnished, not merely a list of significant causes, which is correct so far as it goes, but a complete
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Why economists can’t forecast
The problem of evaluating models built for forecasting is that one cannot get around invariance. There must be a stable bridge that connects the past and pres. ent with the future … To evaluate invariance its domain should be considered. In other words, one has to investigate what the list of all relevant non-negligible potential influences is. To ensure invariance, this list should be complete. This latter point was also emphasised by John Maynard Keynes when he was criticising Tinbergen’s econometric method: “Am I right in thinking that the method multiple correlation analysis essentially depends on the economist having furnished, not merely a list of significant causes, which is correct so far as it goes, but a complete list?” (Keynes 1939, p. 560).”
But these considerations are not sufficient for the evaluation of the predictive per. performance of a non-natural science such as economics. Predictive power also implies that both the domain of invariance as well as the magnitudes of the potential influences should be invariant. This point, too, was raised by Keynes in his critique on Tinbergen’s method:
“The environment in all relevant respects, other than the fluctuations in those factors of which we take particular account, should be uniform and homogeneous over a period of time. We cannot be sure that such conditions will persist in the future, even if we find them in the past. (Keynes 1939, pp. 566-67)”
This latter point was discussed extensively in Keynes’s Treatise on Probability (1921, CW VIlL) under the heading of the theory of statistical inference: “It seeks to extend its description of certain characteristics of observed events to the corresponding characteristics of other events which have not been observed. (Keynes 1921, CW VIII, p. 358).” For inductive inference based on statistical analysis it is of relevance to show whether the statistical series shows some ‘stability’. The verification of whether a statistical series has some stability is required because the condition for economic statistical series to be applicable for inductive inference is that it shows sufficient ‘homogeneity’ or ‘uniformity’ …
This all shows why economists perform so badly when it concerns forecasting.
Marcel Boumans
Maintaining that economics is a science in the ‘true knowledge’ business, yours truly remains a sceptic of the pretences and aspirations of econometrics. The marginal return on its ever-higher technical sophistication in no way makes up for the lack of serious under-labouring of its deeper philosophical and methodological foundations that already Keynes complained about. The rather one-sided emphasis of usefulness and its concomitant instrumentalist justification cannot hide that the legions of probabilistic econometricians who give supportive evidence for their considering it ‘fruitful to believe’ in the possibility of treating unique economic data as the observable results of random drawings from an imaginary sampling of an imaginary population are skating on thin ice.
A rigorous application of econometric methods in economics really presupposes that the phenomena of our real-world economies are ruled by stable causal relations between variables. The endemic lack of predictive success of the econometric project indicates that this hope of finding fixed parameters is a hope for which there, really, is no other ground than hope itself.
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.”
How 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 5.04 % 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.