Phase Space Reconstruction from Economic Time Series Data: Improving Models of Complex Real-World Dynamic Systems

Failure of economic models to anticipate the global financial crisis illustrates the need for modeling to better capture complex real-world dynamics. Conventional models—in which economic variables evolve toward equilibria or fluctuate about equilibria in response to exogenous random shocks—are ill-equipped to portray complex real-world dynamics in which economic variables may cycle aperiodically along low-dimensional ‘strange attractors’. We present a method developed in the physics literature—‘phase space reconstruction’—that reconstructs strange attractors present in real-world dynamical systems using time series data on a single variable. Phase space reconstruction provides pictures of real-world dynamics that can guide model specification


Issue Date:
2010-10
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/97021
Published in:
International Journal on Food System Dynamics, Volume 01, Number 3
Page range:
184-193
Total Pages:
10
Series Statement:
Volume 1
Issue 3




 Record created 2017-04-01, last modified 2017-04-27

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