Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different models

Autores
Blanco, Emilio; D’Amato, Laura; Dogliolo, Fiorella; Garegnani, María Lorena
Año de publicación
2020
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Monetary policy making requires a correct and timely assessment of current macroeconomic conditions. While the main source of macroeconomic data is quarterly National Accounts, often published with a significant lag, higher frequency business cycle indicators are increasingly available. Taking this into account, central banks have adopted nowcasting as a useful tool for having an immediate and more accurate perception of economic conditions. In this paper, we extend the use of nowcasting tools to produce early indicators of the evolution of two components of aggregate domestic demand: consumption and investment. The exercise uses a broad and restricted set of indicators to construct different dynamic factor models, as well as a pooling of models in the case of investment. Finally, we compare different approaches in a pseudo-real time out-of-sample exercise and evaluate their predictive performance.
Facultad de Ciencias Económicas
Materia
Ciencias Económicas
Nowcasting
Dynamic factor models
Forecast pooling
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/121678

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spelling Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different modelsBlanco, EmilioD’Amato, LauraDogliolo, FiorellaGaregnani, María LorenaCiencias EconómicasNowcastingDynamic factor modelsForecast poolingMonetary policy making requires a correct and timely assessment of current macroeconomic conditions. While the main source of macroeconomic data is quarterly National Accounts, often published with a significant lag, higher frequency business cycle indicators are increasingly available. Taking this into account, central banks have adopted nowcasting as a useful tool for having an immediate and more accurate perception of economic conditions. In this paper, we extend the use of nowcasting tools to produce early indicators of the evolution of two components of aggregate domestic demand: consumption and investment. The exercise uses a broad and restricted set of indicators to construct different dynamic factor models, as well as a pooling of models in the case of investment. Finally, we compare different approaches in a pseudo-real time out-of-sample exercise and evaluate their predictive performance.Facultad de Ciencias Económicas2020-11info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/121678enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-28590-8-4info:eu-repo/semantics/altIdentifier/url/https://aaep.org.ar/anales/works/works2020/DAmato2020.pdfinfo:eu-repo/semantics/altIdentifier/issn/1852-0022info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:28:54Zoai:sedici.unlp.edu.ar:10915/121678Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:28:54.484SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different models
title Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different models
spellingShingle Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different models
Blanco, Emilio
Ciencias Económicas
Nowcasting
Dynamic factor models
Forecast pooling
title_short Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different models
title_full Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different models
title_fullStr Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different models
title_full_unstemmed Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different models
title_sort Nowcasting macroeconomic aggregates in Argentina: comparing the predictive ability of different models
dc.creator.none.fl_str_mv Blanco, Emilio
D’Amato, Laura
Dogliolo, Fiorella
Garegnani, María Lorena
author Blanco, Emilio
author_facet Blanco, Emilio
D’Amato, Laura
Dogliolo, Fiorella
Garegnani, María Lorena
author_role author
author2 D’Amato, Laura
Dogliolo, Fiorella
Garegnani, María Lorena
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Económicas
Nowcasting
Dynamic factor models
Forecast pooling
topic Ciencias Económicas
Nowcasting
Dynamic factor models
Forecast pooling
dc.description.none.fl_txt_mv Monetary policy making requires a correct and timely assessment of current macroeconomic conditions. While the main source of macroeconomic data is quarterly National Accounts, often published with a significant lag, higher frequency business cycle indicators are increasingly available. Taking this into account, central banks have adopted nowcasting as a useful tool for having an immediate and more accurate perception of economic conditions. In this paper, we extend the use of nowcasting tools to produce early indicators of the evolution of two components of aggregate domestic demand: consumption and investment. The exercise uses a broad and restricted set of indicators to construct different dynamic factor models, as well as a pooling of models in the case of investment. Finally, we compare different approaches in a pseudo-real time out-of-sample exercise and evaluate their predictive performance.
Facultad de Ciencias Económicas
description Monetary policy making requires a correct and timely assessment of current macroeconomic conditions. While the main source of macroeconomic data is quarterly National Accounts, often published with a significant lag, higher frequency business cycle indicators are increasingly available. Taking this into account, central banks have adopted nowcasting as a useful tool for having an immediate and more accurate perception of economic conditions. In this paper, we extend the use of nowcasting tools to produce early indicators of the evolution of two components of aggregate domestic demand: consumption and investment. The exercise uses a broad and restricted set of indicators to construct different dynamic factor models, as well as a pooling of models in the case of investment. Finally, we compare different approaches in a pseudo-real time out-of-sample exercise and evaluate their predictive performance.
publishDate 2020
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info:eu-repo/semantics/altIdentifier/issn/1852-0022
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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