by There is a big difference between predicting and forecasting. Scientific theory is about causal explanation and prediction through formulating testable hypothesis that challenge the theory rigorously based on experimental evidence. Forecasting is making educated guesses based on limited and variable information information. The former applies chiefly to ergodic systems and the latter to non-ergodic, or if the system is actually ergodic, not enough it known about it to construct a rigorous causal explanation.The ideal causal explanation is in terms of deterministic functions in which a rule applied to a single measurable input results invariably in a single measurable output. The debate over whether statistics can deliver on causal explanation is still raging, in light of the principle
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Mike Norman considers the following as important: Economics, forecasting, prediction, probability and statistics, scientific method
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There is a big difference between predicting and forecasting. Scientific theory is about causal explanation and prediction through formulating testable hypothesis that challenge the theory rigorously based on experimental evidence. Forecasting is making educated guesses based on limited and variable information information. The former applies chiefly to ergodic systems and the latter to non-ergodic, or if the system is actually ergodic, not enough it known about it to construct a rigorous causal explanation.
The ideal causal explanation is in terms of deterministic functions in which a rule applied to a single measurable input results invariably in a single measurable output. The debate over whether statistics can deliver on causal explanation is still raging, in light of the principle that correlation is not causation. For example, Einstein rejected that it could and continued to seek for a set of deterministic functions as the basis for causal explanation in physics, viewing QM as an admission of lingering ignorance about the laws of nature owing to QM being stochastic.
Libraries are full of tomes debating the details of this, but this is a rough outline to which most agree. Thus, forecasting can be "scientific" and even based on causal explanation, but it fails the test of prediction strictly speaking based on performance. The subject matter of the social sciences is more like the weather than planetary motion, and so the results are mixed. There is no ephemeris for economic cycles.
Why is this important other than philosophically? Because humans are ideological and affected by presumptions as hidden assumptions. We tend to overestimate our level of knowledge, on one hand, and other the other, we inflate our degree of confidence.
To paraphrase Richard Feynman the purpose of science is to prevent us from fooling ourselves and we ourselves are the easiest people to fool (owing to cognitive-affective bias).
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Is economics — really — predictable?
Lars P. Syll | Professor, Malmo University