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Complex Systems in Economic and Social Science: An Application of the Goodwin Model to Italy Using the Statistical Software R

Authors: De Sanctis, Angela; Porreca, Annamaria; Maturo, Fabrizio;

Complex Systems in Economic and Social Science: An Application of the Goodwin Model to Italy Using the Statistical Software R

Abstract

Recent research has highlighted that, in dynamical systems, especially when they are non-linear, small noises at the starting datum produce substantial changes in the long-term dynamics; this is connected with the so-called “complexity” and “deterministic chaos”. The stability theory aims to detect the asymptotic behavior of the system through the observation of its equilibrium points. A well-known example of non-linear system is the Lotka-Volterra model that describes the growth in an ecosystem, where only two species interact (“predators” and “prey”). This paper aims to show the adaptability of this model in the social-economical context, because it helps in explaining aspects of dichotomy not only in natural phenomena. Indeed, we also present the Goodwin model that extends the Lotka-Volterra model to the socio-economic context, and we apply it to Italy, using the R statistical software.

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Italy
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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