Diffusion paths: fixed points, periodicity and chaos
Main Author: | |
---|---|
Publication Date: | 2010 |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://ciencia.iscte-iul.pt/public/pub/id/22741 http://hdl.handle.net/10071/10483 |
Summary: | It is common to recognize that ideas, technology and information disseminate across the economy following some kind of diffusion pattern. Typically, the process of adopting a new piece of knowledge will be translated into an s-shaped trajectory for the adoption rate. This type of process of diffusion tends to be stable in the sense that convergence from any initial state towards the long-term scenario in which all the potential adopters enter in contact with the innovation is commonly guaranteed. Here, we introduce a mechanism under which stability of the diffusion process does not necessarily hold. When the perceived law of motion concerning the evolution of the number of potential adopters differs from the actual law of motion, and agents try to learn this law resorting to an adaptive learning rule, nonlinear long-term outcomes might emerge: the percentage of individuals accepting the innovation in the long-run may be a varying value that evolves according to some cyclical (periodic or a-periodic) pattern. The concept of nonlinear diffusion that is addressed is applied to a problem of information and monetary policy. |
id |
RCAP_47fce1209b06ac66eec201b36fd9a71a |
---|---|
oai_identifier_str |
oai:repositorio.iscte-iul.pt:10071/10483 |
network_acronym_str |
RCAP |
network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository_id_str |
https://opendoar.ac.uk/repository/7160 |
spelling |
Diffusion paths: fixed points, periodicity and chaosDiffusionNonlinearitiesChaosStabilityAdaptive learningMonetary policyIt is common to recognize that ideas, technology and information disseminate across the economy following some kind of diffusion pattern. Typically, the process of adopting a new piece of knowledge will be translated into an s-shaped trajectory for the adoption rate. This type of process of diffusion tends to be stable in the sense that convergence from any initial state towards the long-term scenario in which all the potential adopters enter in contact with the innovation is commonly guaranteed. Here, we introduce a mechanism under which stability of the diffusion process does not necessarily hold. When the perceived law of motion concerning the evolution of the number of potential adopters differs from the actual law of motion, and agents try to learn this law resorting to an adaptive learning rule, nonlinear long-term outcomes might emerge: the percentage of individuals accepting the innovation in the long-run may be a varying value that evolves according to some cyclical (periodic or a-periodic) pattern. The concept of nonlinear diffusion that is addressed is applied to a problem of information and monetary policy.Economics Bulletin2015-12-23T13:02:04Z2010-01-01T00:00:00Z20102015-12-23T12:59:57Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://ciencia.iscte-iul.pt/public/pub/id/22741http://hdl.handle.net/10071/10483eng1545-2921Gomes, O.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-07-07T03:13:17Zoai:repositorio.iscte-iul.pt:10071/10483Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T18:18:20.075633Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Diffusion paths: fixed points, periodicity and chaos |
title |
Diffusion paths: fixed points, periodicity and chaos |
spellingShingle |
Diffusion paths: fixed points, periodicity and chaos Gomes, O. Diffusion Nonlinearities Chaos Stability Adaptive learning Monetary policy |
title_short |
Diffusion paths: fixed points, periodicity and chaos |
title_full |
Diffusion paths: fixed points, periodicity and chaos |
title_fullStr |
Diffusion paths: fixed points, periodicity and chaos |
title_full_unstemmed |
Diffusion paths: fixed points, periodicity and chaos |
title_sort |
Diffusion paths: fixed points, periodicity and chaos |
author |
Gomes, O. |
author_facet |
Gomes, O. |
author_role |
author |
dc.contributor.author.fl_str_mv |
Gomes, O. |
dc.subject.por.fl_str_mv |
Diffusion Nonlinearities Chaos Stability Adaptive learning Monetary policy |
topic |
Diffusion Nonlinearities Chaos Stability Adaptive learning Monetary policy |
description |
It is common to recognize that ideas, technology and information disseminate across the economy following some kind of diffusion pattern. Typically, the process of adopting a new piece of knowledge will be translated into an s-shaped trajectory for the adoption rate. This type of process of diffusion tends to be stable in the sense that convergence from any initial state towards the long-term scenario in which all the potential adopters enter in contact with the innovation is commonly guaranteed. Here, we introduce a mechanism under which stability of the diffusion process does not necessarily hold. When the perceived law of motion concerning the evolution of the number of potential adopters differs from the actual law of motion, and agents try to learn this law resorting to an adaptive learning rule, nonlinear long-term outcomes might emerge: the percentage of individuals accepting the innovation in the long-run may be a varying value that evolves according to some cyclical (periodic or a-periodic) pattern. The concept of nonlinear diffusion that is addressed is applied to a problem of information and monetary policy. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-01-01T00:00:00Z 2010 2015-12-23T13:02:04Z 2015-12-23T12:59:57Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ciencia.iscte-iul.pt/public/pub/id/22741 http://hdl.handle.net/10071/10483 |
url |
https://ciencia.iscte-iul.pt/public/pub/id/22741 http://hdl.handle.net/10071/10483 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1545-2921 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Economics Bulletin |
publisher.none.fl_str_mv |
Economics Bulletin |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
_version_ |
1833597320974827520 |