Incorporating Fuzzy Logic in Harrod’s Economic Growth Model

This paper suggests the possibility of incorporating the methodology of fuzzy logic theory into Harrod’s economic growth model, a classic model of economic dynamics for studying the growth of a developing economy based on the assumption that an economy with only savings and investment income is in e...

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Main Authors: Joan Carles Ferrer-Comalat, Salvador Linares-Mustarós, Ricard Rigall-Torrent
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/9/18/2194
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spelling doaj-44c16b8109dd4292b04276a0b9af06522021-09-26T00:37:52ZengMDPI AGMathematics2227-73902021-09-0192194219410.3390/math9182194Incorporating Fuzzy Logic in Harrod’s Economic Growth ModelJoan Carles Ferrer-Comalat0Salvador Linares-Mustarós1Ricard Rigall-Torrent2Department of Business Administration, University of Girona, C/Universitat de Girona 10, 17071 Girona, SpainDepartment of Business Administration, University of Girona, C/Universitat de Girona 10, 17071 Girona, SpainDepartment of Economics, University of Girona, C/Universitat de Girona 10, 17071 Girona, SpainThis paper suggests the possibility of incorporating the methodology of fuzzy logic theory into Harrod’s economic growth model, a classic model of economic dynamics for studying the growth of a developing economy based on the assumption that an economy with only savings and investment income is in equilibrium when savings are equal to investment. This model was the first precursor to exogenous growth models, which in turn gave rise to endogenous growth models. This article therefore represents a first step towards introducing fuzzy logic into economic growth models. The study concerned considers consumption and savings to depend on income by means of uncertain factors, and investment to depend on the variation of income through the accelerator factor, which we consider uncertain. These conditions are used to determine the equilibrium growth rate of income and investment, as well as the uncertain values for these variables in terms of fuzzy numbers. As a result, the new model is shown to expand the classical model by incorporating uncertainty into its variables.https://www.mdpi.com/2227-7390/9/18/2194fuzzy logicfuzzy arithmeticextension principleeconomic modelsHarrod’s growth
collection DOAJ
language English
format Article
sources DOAJ
author Joan Carles Ferrer-Comalat
Salvador Linares-Mustarós
Ricard Rigall-Torrent
spellingShingle Joan Carles Ferrer-Comalat
Salvador Linares-Mustarós
Ricard Rigall-Torrent
Incorporating Fuzzy Logic in Harrod’s Economic Growth Model
Mathematics
fuzzy logic
fuzzy arithmetic
extension principle
economic models
Harrod’s growth
author_facet Joan Carles Ferrer-Comalat
Salvador Linares-Mustarós
Ricard Rigall-Torrent
author_sort Joan Carles Ferrer-Comalat
title Incorporating Fuzzy Logic in Harrod’s Economic Growth Model
title_short Incorporating Fuzzy Logic in Harrod’s Economic Growth Model
title_full Incorporating Fuzzy Logic in Harrod’s Economic Growth Model
title_fullStr Incorporating Fuzzy Logic in Harrod’s Economic Growth Model
title_full_unstemmed Incorporating Fuzzy Logic in Harrod’s Economic Growth Model
title_sort incorporating fuzzy logic in harrod’s economic growth model
publisher MDPI AG
series Mathematics
issn 2227-7390
publishDate 2021-09-01
description This paper suggests the possibility of incorporating the methodology of fuzzy logic theory into Harrod’s economic growth model, a classic model of economic dynamics for studying the growth of a developing economy based on the assumption that an economy with only savings and investment income is in equilibrium when savings are equal to investment. This model was the first precursor to exogenous growth models, which in turn gave rise to endogenous growth models. This article therefore represents a first step towards introducing fuzzy logic into economic growth models. The study concerned considers consumption and savings to depend on income by means of uncertain factors, and investment to depend on the variation of income through the accelerator factor, which we consider uncertain. These conditions are used to determine the equilibrium growth rate of income and investment, as well as the uncertain values for these variables in terms of fuzzy numbers. As a result, the new model is shown to expand the classical model by incorporating uncertainty into its variables.
topic fuzzy logic
fuzzy arithmetic
extension principle
economic models
Harrod’s growth
url https://www.mdpi.com/2227-7390/9/18/2194
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