Artikel
Qualitative analysis of the Goodwin model of the growth cycle
Goodwin's model is a set of ordinary differential equations and is a well-known model of the growth cycle. However, its four constants require an extensive numerical study of its two differential equations to identify all possible unsteady state behaviors, i.e. phase portraits, which corresponds to infinitely many combinations of numerical values of the constants. Qualitative interpretation of Goodwin's model solves these problems by replacing all numerical constants and all derivatives by trends (increasing, constant and decreasing). The model has two variables - the employment rate V, and the labour share U. A solution of the qualitative Goodwin's model is a scenario. An example of a Goodwin's scenario is - V is increasing more and more rapidly, U is decreasing and the decrease is slowing down. The complete set of all possible 41 Goodwin's scenarios and 168 time transitions among them are given. This result qualitatively represents all possible unsteady state Goodwin's behaviours. It is therefore possible to predict all possible future behaviours if a current behaviour is known/chosen. A prediction example is presented in details. No prior knowledge of qualitative model theory is required.
- Sprache
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Englisch
- Erschienen in
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Journal: Revista de Métodos Cuantitativos para la Economía y la Empresa ; ISSN: 1886-516X ; Volume: 23 ; Year: 2017 ; Pages: 223-233 ; Sevilla: Universidad Pablo de Olavide
- Klassifikation
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Wirtschaft
General Aggregative Models: Forecasting and Simulation: Models and Applications
- Thema
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Goodwin model
business cycle
qualitative
scenario
transition
- Ereignis
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Geistige Schöpfung
- (wer)
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Serebriakov, Vladimir
Dohnall, Mirko
- Ereignis
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Veröffentlichung
- (wer)
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Universidad Pablo de Olavide
- (wo)
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Sevilla
- (wann)
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2017
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Serebriakov, Vladimir
- Dohnall, Mirko
- Universidad Pablo de Olavide
Entstanden
- 2017