Nowcasting economic activity in Argentina with many predictors

We pool a large data set of business cycle indicators to produce Nowcast of contemporaneous GDP growth. We also conduct Nowcast using factors for a restricted subset of the indicators. Using an AR(1) benchmark to compare the forecasting performance of both Nowcasts, we conclude that only the Nowcast...

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Detalles Bibliográficos
Autores principales:	D'Amato, Laura, Garegnani, María Lorena, Blanco, Emilio
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2011
Materias:	Ciencias Económicas Forecast pooling Large dataset Real time forecast Factor Models
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/170412
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-170412
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spelling	I19-R120-10915-1704122024-09-20T20:45:04Z http://sedici.unlp.edu.ar/handle/10915/170412 Nowcasting economic activity in Argentina with many predictors D'Amato, Laura Garegnani, María Lorena Blanco, Emilio 2011-11 2011 2024-09-20T13:12:37Z en Ciencias Económicas Forecast pooling Large dataset Real time forecast Factor Models We pool a large data set of business cycle indicators to produce Nowcast of contemporaneous GDP growth. We also conduct Nowcast using factors for a restricted subset of the indicators. Using an AR(1) benchmark to compare the forecasting performance of both Nowcasts, we conclude that only the Nowcast with pooling outperforms this univariate model. The Giacomini and White (2004) test is employed to evaluate the out of sample forecasting performance of the pooling compared to the AR(1). In general, results indicate that a rich data set approach can provide valuable predictions about GDP behavior for the immediate future. Facultad de Ciencias Económicas Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Económicas Forecast pooling Large dataset Real time forecast Factor Models
spellingShingle	Ciencias Económicas Forecast pooling Large dataset Real time forecast Factor Models D'Amato, Laura Garegnani, María Lorena Blanco, Emilio Nowcasting economic activity in Argentina with many predictors
topic_facet	Ciencias Económicas Forecast pooling Large dataset Real time forecast Factor Models
description	We pool a large data set of business cycle indicators to produce Nowcast of contemporaneous GDP growth. We also conduct Nowcast using factors for a restricted subset of the indicators. Using an AR(1) benchmark to compare the forecasting performance of both Nowcasts, we conclude that only the Nowcast with pooling outperforms this univariate model. The Giacomini and White (2004) test is employed to evaluate the out of sample forecasting performance of the pooling compared to the AR(1). In general, results indicate that a rich data set approach can provide valuable predictions about GDP behavior for the immediate future.
format	Objeto de conferencia Objeto de conferencia
author	D'Amato, Laura Garegnani, María Lorena Blanco, Emilio
author_facet	D'Amato, Laura Garegnani, María Lorena Blanco, Emilio
author_sort	D'Amato, Laura
title	Nowcasting economic activity in Argentina with many predictors
title_short	Nowcasting economic activity in Argentina with many predictors
title_full	Nowcasting economic activity in Argentina with many predictors
title_fullStr	Nowcasting economic activity in Argentina with many predictors
title_full_unstemmed	Nowcasting economic activity in Argentina with many predictors
title_sort	nowcasting economic activity in argentina with many predictors
publishDate	2011
url	http://sedici.unlp.edu.ar/handle/10915/170412
work_keys_str_mv	AT damatolaura nowcastingeconomicactivityinargentinawithmanypredictors AT garegnanimarialorena nowcastingeconomicactivityinargentinawithmanypredictors AT blancoemilio nowcastingeconomicactivityinargentinawithmanypredictors
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Nowcasting economic activity in Argentina with many predictors

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