Medium term growth forecasts : experts vs. simple models

Autores
Aromí, José Daniel
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión aceptada
Descripción
Fil: Aromí, José Daniel. Pontificia Universidad Católica Argentina. Facultad de Ciencias Económicas. Departamento de Investigación Francisco Valsecchi; Argentina
Fil: Aromí, José Daniel. Universidad de Buenos Aires; Argentina
Fil: Aromí, José Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Abstract: We compare the medium-term GDP growth forecasts generated by experts to those generated by simple models. This study analyzes a large set of forecasts that covers 48 countries from 1997 to 2016. Out-of-sample exercises indicate that no noticeable difference in performance is observed for advanced economies. In contrast, in the case of emerging economies, model forecasts perform better than expert forecasts. In addition, similar patterns are found for a collection of forecasts from a different set of experts, which suggests that the reported regularity is prevalent. Further analyses suggest that the documented difference in performance can be explained by an optimism bias, excessive reactions to innovations in growth trajectories, and insufficient responses to the information contained in the current account balance.
Fuente
International Journal of Forecasting, 35(3), 2019
Materia
ECONOMIA
PBI
CRECIMIENTO ECONOMICO
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
Repositorio Institucional (UCA)
Institución
Pontificia Universidad Católica Argentina
OAI Identificador
oai:ucacris:123456789/8770
Acceder
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oai_identifier_str oai:ucacris:123456789/8770
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repository_id_str 2585
network_name_str Repositorio Institucional (UCA)
spelling Medium term growth forecasts : experts vs. simple modelsAromí, José DanielECONOMIAPBICRECIMIENTO ECONOMICOFil: Aromí, José Daniel. Pontificia Universidad Católica Argentina. Facultad de Ciencias Económicas. Departamento de Investigación Francisco Valsecchi; ArgentinaFil: Aromí, José Daniel. Universidad de Buenos Aires; ArgentinaFil: Aromí, José Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaAbstract: We compare the medium-term GDP growth forecasts generated by experts to those generated by simple models. This study analyzes a large set of forecasts that covers 48 countries from 1997 to 2016. Out-of-sample exercises indicate that no noticeable difference in performance is observed for advanced economies. In contrast, in the case of emerging economies, model forecasts perform better than expert forecasts. In addition, similar patterns are found for a collection of forecasts from a different set of experts, which suggests that the reported regularity is prevalent. Further analyses suggest that the documented difference in performance can be explained by an optimism bias, excessive reactions to innovations in growth trajectories, and insufficient responses to the information contained in the current account balance.Elsevier2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://repositorio.uca.edu.ar/handle/123456789/87700169-207010.1016/j.ijforecast.2019.03.004Aromí, J. D. (2019). Medium term growth forecasts : experts vs. simple models [en línea]. International Journal of Forecasting, 35(3), 1085-1099. doi:10.1016/j.ijforecast.2019.03.004 Disponible en: https://repositorio.uca.edu.ar/handle/123456789/8770International Journal of Forecasting, 35(3), 2019reponame:Repositorio Institucional (UCA)instname:Pontificia Universidad Católica ArgentinaengEstudios de estados subjetivos en contextos microeconómicosinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/4.0/2025-07-03T10:56:54Zoai:ucacris:123456789/8770instacron:UCAInstitucionalhttps://repositorio.uca.edu.ar/Universidad privadaNo correspondehttps://repositorio.uca.edu.ar/oaiclaudia_fernandez@uca.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:25852025-07-03 10:56:55.243Repositorio Institucional (UCA) - Pontificia Universidad Católica Argentinafalse
dc.title.none.fl_str_mv Medium term growth forecasts : experts vs. simple models
title Medium term growth forecasts : experts vs. simple models
spellingShingle Medium term growth forecasts : experts vs. simple models
Aromí, José Daniel
ECONOMIA
PBI
CRECIMIENTO ECONOMICO
title_short Medium term growth forecasts : experts vs. simple models
title_full Medium term growth forecasts : experts vs. simple models
title_fullStr Medium term growth forecasts : experts vs. simple models
title_full_unstemmed Medium term growth forecasts : experts vs. simple models
title_sort Medium term growth forecasts : experts vs. simple models
dc.creator.none.fl_str_mv Aromí, José Daniel
author Aromí, José Daniel
author_facet Aromí, José Daniel
author_role author
dc.subject.none.fl_str_mv ECONOMIA
PBI
CRECIMIENTO ECONOMICO
topic ECONOMIA
PBI
CRECIMIENTO ECONOMICO
dc.description.none.fl_txt_mv Fil: Aromí, José Daniel. Pontificia Universidad Católica Argentina. Facultad de Ciencias Económicas. Departamento de Investigación Francisco Valsecchi; Argentina
Fil: Aromí, José Daniel. Universidad de Buenos Aires; Argentina
Fil: Aromí, José Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Abstract: We compare the medium-term GDP growth forecasts generated by experts to those generated by simple models. This study analyzes a large set of forecasts that covers 48 countries from 1997 to 2016. Out-of-sample exercises indicate that no noticeable difference in performance is observed for advanced economies. In contrast, in the case of emerging economies, model forecasts perform better than expert forecasts. In addition, similar patterns are found for a collection of forecasts from a different set of experts, which suggests that the reported regularity is prevalent. Further analyses suggest that the documented difference in performance can be explained by an optimism bias, excessive reactions to innovations in growth trajectories, and insufficient responses to the information contained in the current account balance.
description Fil: Aromí, José Daniel. Pontificia Universidad Católica Argentina. Facultad de Ciencias Económicas. Departamento de Investigación Francisco Valsecchi; Argentina
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://repositorio.uca.edu.ar/handle/123456789/8770
0169-2070
10.1016/j.ijforecast.2019.03.004
Aromí, J. D. (2019). Medium term growth forecasts : experts vs. simple models [en línea]. International Journal of Forecasting, 35(3), 1085-1099. doi:10.1016/j.ijforecast.2019.03.004 Disponible en: https://repositorio.uca.edu.ar/handle/123456789/8770
url https://repositorio.uca.edu.ar/handle/123456789/8770
identifier_str_mv 0169-2070
10.1016/j.ijforecast.2019.03.004
Aromí, J. D. (2019). Medium term growth forecasts : experts vs. simple models [en línea]. International Journal of Forecasting, 35(3), 1085-1099. doi:10.1016/j.ijforecast.2019.03.004 Disponible en: https://repositorio.uca.edu.ar/handle/123456789/8770
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Estudios de estados subjetivos en contextos microeconómicos
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv International Journal of Forecasting, 35(3), 2019
reponame:Repositorio Institucional (UCA)
instname:Pontificia Universidad Católica Argentina
reponame_str Repositorio Institucional (UCA)
collection Repositorio Institucional (UCA)
instname_str Pontificia Universidad Católica Argentina
repository.name.fl_str_mv Repositorio Institucional (UCA) - Pontificia Universidad Católica Argentina
repository.mail.fl_str_mv claudia_fernandez@uca.edu.ar
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score 13.13397

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