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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/121678
Ver los metadatos del registro completo
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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 |
dc.date.none.fl_str_mv |
2020-11 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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http://sedici.unlp.edu.ar/handle/10915/121678 |
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eng |
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eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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