Goodwin economic cycle via p-fuzzy system

Author(s)

Eduardo Sanchez, Daniel ; Esmi, Estevao ; de Barros, Laecio Carvalho ; Miebach, Alessandro Donadio ; Cecconello, Moiseis dos Santos

• Document type: Journal article
• Source: JOURNAL OF INTELLIGENT & FUZZY SYSTEMS; v. 38, n. 4, p. 12-pg., 2020-01-01.

Abstract

In this manuscript, we present numerical solutions of a p-fuzzy system that models the Goodwin economic cycle. This model describes the dynamic interaction between labour share and the employment rate in an economy. One can use p-fuzzy systems to obtain solutions for differential equations whose the vector field are uncertain and partially known. The proposed p-fuzzy system is based on a fuzzy rule-based systems whose fuzzy rules represent economic premises described in the Goodwin model. We use two approaches to adjust the fuzzy terms of the corresponding fuzzy rule base from the economical data of a given country. The first approach is based on statical measures and the second one uses fuzzy c-means clustering method. Finally, we test our proposal to estimate the growth cycles of the labour share and the employment rate of Germany and we compare the obtained results with the historical data. (AU)

• FAPESP's process: 16/26040-7 - Differential and integral calculus based on arithmetic of interactive fuzzy numbers
• Grantee: Estevão Esmi Laureano
• Support Opportunities: Regular Research Grants
• FAPESP's process: 18/10946-2 - The 13th International FLINS Conference on Data Science and Knowledge Engineering for Sensing Decision Support
• Grantee: Laécio Carvalho de Barros
• Support Opportunities: Research Grants - Meeting - Abroad