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RANDOM DYNAMICAL SYSTEMS IN ECONOMICS

Name: RANDOM DYNAMICAL SYSTEMS IN ECONOMICS
Creator: Schenk-Hoppé, Klaus Reiner
Keywords: Random dynamical systems, info:eu-repo/classification/ddc/330, Stochastic models in economics, Economics, 05 social sciences, jel:E32, Stochastic programming, jel:C00, stochastic economic growth, 330 Economics

Random dynamical systems in economics

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type , Research , Preprint 01 Mar 2001Embargo end date: 01 Jan 2000 Switzerland English Publisher:World Scientific Pub Co Pte LtJournal:Stochastics and Dynamics, volume 1, pages 63-83 (issn: 0219-4937, eissn: 1793-6799,

Authors: Schenk-Hoppé, Klaus Reiner;

doi: 10.1142/s0219493701000059 , 10.2139/ssrn.259135 , 10.5167/uzh-51968 , 10.3929/ethz-a-004373692

handle: 20.500.11850/146608

RANDOM DYNAMICAL SYSTEMS IN ECONOMICS

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Abstract

This paper surveys recent advances in the application of random dynamical systems theory in economics. It illustrates the usefulness of this framework for modeling and analysis of economic phenomena with stochastic components, mainly focusing on stochastic dynamic models of economic growth. The paper also highlights some directions for further applications and interdisciplinary research on random dynamical systems.

Country

Switzerland

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Keywords

Random dynamical systems, info:eu-repo/classification/ddc/330, Stochastic models in economics, Economics, Stochastic programming, stochastic economic growth, 330 Economics, random dynamical systems, dynamic models, economic growth, 10007 Department of Economics, IEW Institute for Empirical Research in Economics (former), Economic growth models, Dynamical systems in optimization and economics, dynamic economic models, jel: jel:E32, jel: jel:C00, jel: jel:O41

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	citations 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).	62
	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.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 1%