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A look into the nature of complex systems and beyond “Stonehenge” economics: coping with complexity or ignoring it in applied economics?
Author(s) -
Noell Chris
Publication year - 2007
Publication title -
agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.29
H-Index - 82
eISSN - 1574-0862
pISSN - 0169-5150
DOI - 10.1111/j.1574-0862.2007.00268.x
Subject(s) - self organized criticality , complex system , criticality , toolbox , empirical research , economics , self organization , computer science , mathematics , artificial intelligence , statistics , physics , nuclear physics , programming language
Real‐world economic systems are complex in general but can be approximated by the “open systems” approach. Economic systems are very likely to possess the basic and advanced emergent properties (e.g., self‐organized criticality, fractals, attractors) of general complex systems. The theory of “self‐organized criticality” is proposed as a major source of dynamic equilibria and complexity in economic systems. This is exemplified in an analysis for self‐organized criticality of Danish agricultural subsectors, indicated by power law distributions of the monetary production value for the time period from 1963 to 1999. Major conclusions from the empirical part are: (1) The sectors under investigation are obviously self‐organizing and thus very likely to show a range of complex properties. (2) The characteristics of the power law distributions that were measured might contain further information about the state or graduation of self‐organization in the sector. Varying empirical results for different agricultural sectors turned out to be consistent with the theory of self‐organized criticality. (3) Fully self‐organizing sectors might be economically the most efficient. Finally, empirical implications of the results are discussed. Complexity theory should be considered as a valuable supplement to the existing analytical toolbox.