Using the flow of conjectural information for short term forecasting of economic activity in Argentina
- Autores
- D'Amato, Laura; Garegnani, María Lorena; Blanco, Emilio
- Año de publicación
- 2009
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- We exploit the richness of a large data set of daily and monthly business cycle indicators by combining them to produce nowcast of contemporaneous real GDP growth as well as forecast. Nowcast outperforms two benchmark models: the one-quarter ahead forecast of an AR(1) in the previous quarter and previous quarter actual value of GDP growth used as current value predictor. When we combine indicators to produce forecasts, the RMSE forecast pooling outperforms the AR(1) benchmark model predictions at the 3, 6 and 12 month horizons. The methodology offers a valuable approach for providing timely information for policy decision making.
Explotamos la riqueza de un gran conjunto de indicadores del ciclo de frecuencia diaria y mensual para producir predicciones en tiempo real y pronósticos del crecimiento del producto real en Argentina. Las predicciones en tiempo real superan en capacidad predictiva a dos predictores usados como benchmark: el pronóstico de un AR(1) en el trimestre previo y el propio valor observado en ese trimestre. El pronóstico fuera de la muestra utilizando ponderaciones basadas en RMSE supera al modelo AR(1) en capacidad predictiva. La metodología ofrece una alternativa valiosa para proveer información en tiempo para la toma de decisiones de política económica.
Facultad de Ciencias Económicas - Materia
-
Ciencias Económicas
indicators
real GDP growth - 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:10915/170447
Ver los metadatos del registro completo
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Using the flow of conjectural information for short term forecasting of economic activity in ArgentinaD'Amato, LauraGaregnani, María LorenaBlanco, EmilioCiencias Económicasindicatorsreal GDP growthWe exploit the richness of a large data set of daily and monthly business cycle indicators by combining them to produce nowcast of contemporaneous real GDP growth as well as forecast. Nowcast outperforms two benchmark models: the one-quarter ahead forecast of an AR(1) in the previous quarter and previous quarter actual value of GDP growth used as current value predictor. When we combine indicators to produce forecasts, the RMSE forecast pooling outperforms the AR(1) benchmark model predictions at the 3, 6 and 12 month horizons. The methodology offers a valuable approach for providing timely information for policy decision making.Explotamos la riqueza de un gran conjunto de indicadores del ciclo de frecuencia diaria y mensual para producir predicciones en tiempo real y pronósticos del crecimiento del producto real en Argentina. Las predicciones en tiempo real superan en capacidad predictiva a dos predictores usados como benchmark: el pronóstico de un AR(1) en el trimestre previo y el propio valor observado en ese trimestre. El pronóstico fuera de la muestra utilizando ponderaciones basadas en RMSE supera al modelo AR(1) en capacidad predictiva. La metodología ofrece una alternativa valiosa para proveer información en tiempo para la toma de decisiones de política económica.Facultad de Ciencias Económicas2009-11info: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/10915/170447enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-99570-7-3info:eu-repo/semantics/altIdentifier/url/https://bd.aaep.org.ar/anales/works/works2009/damato.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:UNLP2025-09-29T11:43:20Zoai:sedici.unlp.edu.ar:10915/170447Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:43:21.272SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Using the flow of conjectural information for short term forecasting of economic activity in Argentina |
title |
Using the flow of conjectural information for short term forecasting of economic activity in Argentina |
spellingShingle |
Using the flow of conjectural information for short term forecasting of economic activity in Argentina D'Amato, Laura Ciencias Económicas indicators real GDP growth |
title_short |
Using the flow of conjectural information for short term forecasting of economic activity in Argentina |
title_full |
Using the flow of conjectural information for short term forecasting of economic activity in Argentina |
title_fullStr |
Using the flow of conjectural information for short term forecasting of economic activity in Argentina |
title_full_unstemmed |
Using the flow of conjectural information for short term forecasting of economic activity in Argentina |
title_sort |
Using the flow of conjectural information for short term forecasting of economic activity in Argentina |
dc.creator.none.fl_str_mv |
D'Amato, Laura Garegnani, María Lorena Blanco, Emilio |
author |
D'Amato, Laura |
author_facet |
D'Amato, Laura Garegnani, María Lorena Blanco, Emilio |
author_role |
author |
author2 |
Garegnani, María Lorena Blanco, Emilio |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Económicas indicators real GDP growth |
topic |
Ciencias Económicas indicators real GDP growth |
dc.description.none.fl_txt_mv |
We exploit the richness of a large data set of daily and monthly business cycle indicators by combining them to produce nowcast of contemporaneous real GDP growth as well as forecast. Nowcast outperforms two benchmark models: the one-quarter ahead forecast of an AR(1) in the previous quarter and previous quarter actual value of GDP growth used as current value predictor. When we combine indicators to produce forecasts, the RMSE forecast pooling outperforms the AR(1) benchmark model predictions at the 3, 6 and 12 month horizons. The methodology offers a valuable approach for providing timely information for policy decision making. Explotamos la riqueza de un gran conjunto de indicadores del ciclo de frecuencia diaria y mensual para producir predicciones en tiempo real y pronósticos del crecimiento del producto real en Argentina. Las predicciones en tiempo real superan en capacidad predictiva a dos predictores usados como benchmark: el pronóstico de un AR(1) en el trimestre previo y el propio valor observado en ese trimestre. El pronóstico fuera de la muestra utilizando ponderaciones basadas en RMSE supera al modelo AR(1) en capacidad predictiva. La metodología ofrece una alternativa valiosa para proveer información en tiempo para la toma de decisiones de política económica. Facultad de Ciencias Económicas |
description |
We exploit the richness of a large data set of daily and monthly business cycle indicators by combining them to produce nowcast of contemporaneous real GDP growth as well as forecast. Nowcast outperforms two benchmark models: the one-quarter ahead forecast of an AR(1) in the previous quarter and previous quarter actual value of GDP growth used as current value predictor. When we combine indicators to produce forecasts, the RMSE forecast pooling outperforms the AR(1) benchmark model predictions at the 3, 6 and 12 month horizons. The methodology offers a valuable approach for providing timely information for policy decision making. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009-11 |
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/10915/170447 |
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http://sedici.unlp.edu.ar/handle/10915/170447 |
dc.language.none.fl_str_mv |
eng |
language |
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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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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