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Dynamics of economic growth: Uncertainty treatment using differential inclusions

The article is focused on applications of the differential inclusions to the models of economic growth, rather than the model building. The models are taken from the known literature, and some modifications are introduced to reflect an additional inertia. The aim is to treat the uncertainty in the m...

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Detalles Bibliográficos
Autor principal: Raczynski, Stanislaw
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6446044/
https://www.ncbi.nlm.nih.gov/pubmed/30984570
http://dx.doi.org/10.1016/j.mex.2019.02.029
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author Raczynski, Stanislaw
author_facet Raczynski, Stanislaw
author_sort Raczynski, Stanislaw
collection PubMed
description The article is focused on applications of the differential inclusions to the models of economic growth, rather than the model building. The models are taken from the known literature, and some modifications are introduced to reflect an additional inertia. The aim is to treat the uncertainty in the model parameters by using differential inclusions instead of the stochastic approach. The reachable sets for the models are shown, to assess the possible ranges of the outcome with given parameters uncertainty. The approach may be interpreted as a generalization to the system dynamics methodology, providing attainable sets instead of single model trajectory and simple sensitivity analysis. A comparison with Powersim risk analysis is provided. The models of Solow and Swan, Mankiw, Bhattacharya, Romer and Weil are used. A brief review of the models is given, and several examples of simple simulations, differential inclusion applications and optimization are presented.
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spelling pubmed-64460442019-04-12 Dynamics of economic growth: Uncertainty treatment using differential inclusions Raczynski, Stanislaw MethodsX Computer Science The article is focused on applications of the differential inclusions to the models of economic growth, rather than the model building. The models are taken from the known literature, and some modifications are introduced to reflect an additional inertia. The aim is to treat the uncertainty in the model parameters by using differential inclusions instead of the stochastic approach. The reachable sets for the models are shown, to assess the possible ranges of the outcome with given parameters uncertainty. The approach may be interpreted as a generalization to the system dynamics methodology, providing attainable sets instead of single model trajectory and simple sensitivity analysis. A comparison with Powersim risk analysis is provided. The models of Solow and Swan, Mankiw, Bhattacharya, Romer and Weil are used. A brief review of the models is given, and several examples of simple simulations, differential inclusion applications and optimization are presented. Elsevier 2019-02-28 /pmc/articles/PMC6446044/ /pubmed/30984570 http://dx.doi.org/10.1016/j.mex.2019.02.029 Text en © 2019 The Author http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Raczynski, Stanislaw
Dynamics of economic growth: Uncertainty treatment using differential inclusions
title Dynamics of economic growth: Uncertainty treatment using differential inclusions
title_full Dynamics of economic growth: Uncertainty treatment using differential inclusions
title_fullStr Dynamics of economic growth: Uncertainty treatment using differential inclusions
title_full_unstemmed Dynamics of economic growth: Uncertainty treatment using differential inclusions
title_short Dynamics of economic growth: Uncertainty treatment using differential inclusions
title_sort dynamics of economic growth: uncertainty treatment using differential inclusions
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6446044/
https://www.ncbi.nlm.nih.gov/pubmed/30984570
http://dx.doi.org/10.1016/j.mex.2019.02.029
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