Global optimization of the CUE objective function by eigenvalue methods
Autor(a) principal: | |
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Data de Publicação: | 2024 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | https://hdl.handle.net/10438/35834 |
Resumo: | Desde sua concepção em Hansen et al. (1996), o Estimador de GMM de Atualização Contínua (CUE) tem representado um desafio para os métodos de otimização numérica devido à estrutura de sua função objetivo. Mesmo em modelos lineares simples, ela pode apresentar múltiplos mínimos locais e seções planas que frequentemente derrotam tanto os métodos de descida de gradiente quanto os de busca em grade. Esse problema de longa data na literatura foi recentemente resolvido por Moreira et al. (2023). Construindo sobre este resultado, propomos um método alternativo que é simples de implementar e mantém garantias semelhantes de produzir resultados globalmente ótimos. Mostramos como as condições de primeira ordem da função objetivo do CUE podem ser reformuladas na forma de um problema de autovalores e especializadas para casos em que algoritmos eficientes estão disponíveis. |
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Exel, Guilherme SohnleinEscolas::EPGENewey, Whitney KentSant'Anna, Marcelo Castello BrancoSharifvaghefi, MahradMoreira, Marcelo J2024-09-03T17:51:21Z2024-09-03T17:51:21Z2024-03-26https://hdl.handle.net/10438/35834Desde sua concepção em Hansen et al. (1996), o Estimador de GMM de Atualização Contínua (CUE) tem representado um desafio para os métodos de otimização numérica devido à estrutura de sua função objetivo. Mesmo em modelos lineares simples, ela pode apresentar múltiplos mínimos locais e seções planas que frequentemente derrotam tanto os métodos de descida de gradiente quanto os de busca em grade. Esse problema de longa data na literatura foi recentemente resolvido por Moreira et al. (2023). Construindo sobre este resultado, propomos um método alternativo que é simples de implementar e mantém garantias semelhantes de produzir resultados globalmente ótimos. Mostramos como as condições de primeira ordem da função objetivo do CUE podem ser reformuladas na forma de um problema de autovalores e especializadas para casos em que algoritmos eficientes estão disponíveis.Since its inception in Hansen et al. (1996, the Continuously Updating GMM Estimator (CUE) has posed a challenge for numerical optimization methods due to the structure of its criterion function. Even in simple linear models, it can present multiple local minima and flat sections which often defeat both gradient descent and grid search methods. This longstanding problem in the literature has recently been solved by Moreira et al. (2023). We build upon their insight and propose an alternative method which is simple to implement and retains similar guarantees of producing globally optimal results. We show how the first order conditions of the CUE criterion function can be restated in the form of an eigenvalue problem and specialize to cases for which efficient algorithms are available.engEstimador de atualização contínuaMétodo generalizado dos momentosProblemas de autovalores não linearesProblemas de autovalores multiparamétricosContinuously updating estimatorGeneralized method of momentsNonlinear eigenvalue problemsMultiparameter eigenvalue problemsEconomiaEconometria – Processamento de dadosAutovaloresMetodo dos momentos (Estatistica)Otimização matemáticaGlobal optimization of the CUE objective function by eigenvalue methodsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas 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|
dc.title.eng.fl_str_mv |
Global optimization of the CUE objective function by eigenvalue methods |
title |
Global optimization of the CUE objective function by eigenvalue methods |
spellingShingle |
Global optimization of the CUE objective function by eigenvalue methods Exel, Guilherme Sohnlein Estimador de atualização contínua Método generalizado dos momentos Problemas de autovalores não lineares Problemas de autovalores multiparamétricos Continuously updating estimator Generalized method of moments Nonlinear eigenvalue problems Multiparameter eigenvalue problems Economia Econometria – Processamento de dados Autovalores Metodo dos momentos (Estatistica) Otimização matemática |
title_short |
Global optimization of the CUE objective function by eigenvalue methods |
title_full |
Global optimization of the CUE objective function by eigenvalue methods |
title_fullStr |
Global optimization of the CUE objective function by eigenvalue methods |
title_full_unstemmed |
Global optimization of the CUE objective function by eigenvalue methods |
title_sort |
Global optimization of the CUE objective function by eigenvalue methods |
author |
Exel, Guilherme Sohnlein |
author_facet |
Exel, Guilherme Sohnlein |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EPGE |
dc.contributor.member.none.fl_str_mv |
Newey, Whitney Kent Sant'Anna, Marcelo Castello Branco Sharifvaghefi, Mahrad |
dc.contributor.author.fl_str_mv |
Exel, Guilherme Sohnlein |
dc.contributor.advisor1.fl_str_mv |
Moreira, Marcelo J |
contributor_str_mv |
Moreira, Marcelo J |
dc.subject.por.fl_str_mv |
Estimador de atualização contínua |
topic |
Estimador de atualização contínua Método generalizado dos momentos Problemas de autovalores não lineares Problemas de autovalores multiparamétricos Continuously updating estimator Generalized method of moments Nonlinear eigenvalue problems Multiparameter eigenvalue problems Economia Econometria – Processamento de dados Autovalores Metodo dos momentos (Estatistica) Otimização matemática |
dc.subject. por.fl_str_mv |
Método generalizado dos momentos Problemas de autovalores não lineares Problemas de autovalores multiparamétricos |
dc.subject.eng.fl_str_mv |
Continuously updating estimator Generalized method of moments Nonlinear eigenvalue problems Multiparameter eigenvalue problems |
dc.subject.area.por.fl_str_mv |
Economia |
dc.subject.bibliodata.por.fl_str_mv |
Econometria – Processamento de dados Autovalores Metodo dos momentos (Estatistica) Otimização matemática |
description |
Desde sua concepção em Hansen et al. (1996), o Estimador de GMM de Atualização Contínua (CUE) tem representado um desafio para os métodos de otimização numérica devido à estrutura de sua função objetivo. Mesmo em modelos lineares simples, ela pode apresentar múltiplos mínimos locais e seções planas que frequentemente derrotam tanto os métodos de descida de gradiente quanto os de busca em grade. Esse problema de longa data na literatura foi recentemente resolvido por Moreira et al. (2023). Construindo sobre este resultado, propomos um método alternativo que é simples de implementar e mantém garantias semelhantes de produzir resultados globalmente ótimos. Mostramos como as condições de primeira ordem da função objetivo do CUE podem ser reformuladas na forma de um problema de autovalores e especializadas para casos em que algoritmos eficientes estão disponíveis. |
publishDate |
2024 |
dc.date.accessioned.fl_str_mv |
2024-09-03T17:51:21Z |
dc.date.available.fl_str_mv |
2024-09-03T17:51:21Z |
dc.date.issued.fl_str_mv |
2024-03-26 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10438/35834 |
url |
https://hdl.handle.net/10438/35834 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional do FGV (FGV Repositório Digital) instname:Fundação Getulio Vargas (FGV) instacron:FGV |
instname_str |
Fundação Getulio Vargas (FGV) |
instacron_str |
FGV |
institution |
FGV |
reponame_str |
Repositório Institucional do FGV (FGV Repositório Digital) |
collection |
Repositório Institucional do FGV (FGV Repositório Digital) |
bitstream.url.fl_str_mv |
https://repositorio.fgv.br/bitstreams/15cc81f5-c483-4732-b8e9-000db81d6830/download https://repositorio.fgv.br/bitstreams/0cefecc4-aaca-4cb9-8792-3dc3505039d7/download https://repositorio.fgv.br/bitstreams/230e35eb-9890-4617-8d85-c0f79da5ca1b/download https://repositorio.fgv.br/bitstreams/7c01ff7d-bc68-4d59-ad58-7a439c809196/download |
bitstream.checksum.fl_str_mv |
defca06cc628511ef69ba08a298e01c3 2a4b67231f701c416a809246e7a10077 f48927d5019b7afe5beae41bed824b21 2597a464d63439592e23622d81d8e526 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV) |
repository.mail.fl_str_mv |
|
_version_ |
1810023608891736064 |