Editing Economic model (section)

=== Effects of deterministic chaos on economic models ===

Economic and meteorological simulations may share a fundamental limit to their predictive powers: [[Chaos theory|chaos]]. Although the modern mathematical work on [[chaotic systems]] began in the 1970s the danger of chaos had been identified and defined in ''[[Econometrica]]'' as early as 1958:
:"Good theorising consists to a large extent in avoiding assumptions&nbsp;... [with the property that] a small change in what is posited will seriously affect the conclusions."
:([[William Baumol]], Econometrica, 26 ''see'': [http://www.iemss.org/iemss2004/pdf/keynotes/Keynote_OXLEY.pdf ''Economics on the Edge of Chaos'']).

It is straightforward to design economic models susceptible to [[butterfly effect]]s of initial-condition sensitivity.<ref>[[Paul Wilmott]] on his early research in finance: "I quickly dropped&nbsp;... chaos theory [as] it was too easy to construct ‘toy models’ that looked plausible but were useless in practice." {{citation|first=Paul|last=Wilmott|title=Frequently Asked Questions in Quantitative Finance| publisher=John Wiley and Sons|year=2009|url=https://books.google.com/books?id=n4swgjSoMyIC&pg=PT227 |page=227|isbn=9780470685143 }}</ref><ref>{{citation|url=http://www.sp.uconn.edu/~ages/files/NL_Chaos_and_%20Macro%20-%20429%20Essay.pdf|first=Steve|last=Kuchta|title=Nonlinearity and Chaos in Macroeconomics and Financial Markets|publisher=[[University of Connecticut]]|year=2004}}</ref>

However, the [[econometric]] research program to identify which variables are chaotic (if any) has largely concluded that aggregate macroeconomic variables probably do not behave chaotically.{{Citation needed|reason=This claim and conclusions based on it need one or more reliable sources.|date=October 2023}} This would mean that refinements to the models could ultimately produce reliable long-term forecasts. However, the validity of this conclusion has generated two challenges:
* In 2004 [[Philip Mirowski]] challenged this view and those who hold it, saying that chaos in economics is suffering from a biased "crusade" against it by [[neo-classical economics]] in order to preserve their mathematical models.
* The variables in [[finance]] may well be subject to chaos. Also in 2004, the [[University of Canterbury]] study ''Economics on the Edge of Chaos'' concludes that after noise is removed from [[S&P 500]] returns, evidence of [[determinism|deterministic]] chaos ''is'' found.

More recently, chaos (or the butterfly effect) has been identified as less significant than previously thought to explain prediction errors. Rather, the predictive power of economics and meteorology would mostly be limited by the models themselves and the nature of their underlying systems (see [[Economic models#Comparison with models in other sciences|Comparison with models in other sciences]] above).