Abstract
Lessons from chaos theory for economic science are presented: (i) low dimensional deterministic dynamics can generate behavior thatwill fool the statistician into thinking the behavior is random, (ii) a small shift in the dynamics can generate behavior that looks like non-stationarity to statisticians, (iii) small measurement errors today multiply into exponentially growing forecast errors further ahead, (iv) if the underlying economic dynamics are truly described by a chaos (which may be of very high dimension so that it is indistinguishable from randomness) then economic forecasting may be impossible except for the very short term.
Research support of the National Science Foundation, the Wisconsin Alumni Research Foundation, and the Wisconsin Graduate School is gratefully acknowledged.
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Brock, W.A. (1990). Chaos and Complexity in Economic and Financial Science. In: Acting under Uncertainty: Multidisciplinary Conceptions. Theory and Decision Library, vol 13. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-7873-8_17
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DOI: https://doi.org/10.1007/978-94-015-7873-8_17
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