GDP Nowcasting: assessing business cycle conditions in Argentina

Having a correct assessment of current business cycle conditions is one of the mayor challenges for monetary policy conduct. Given that GDP figures are available with a significant delay, central banks are increasingly using Nowcasting as a useful tool for having an immediate perception of economic...

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Detalles Bibliográficos
Autores principales: D'Amato, Laura Inés, Garegnani, María Lorena, Ruiz y Blanco, Emilio R.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2014
Materias:
Ciencias Económicas
nowcasting
bridge equations
dynamic factor models
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/173779
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-173779
record_format dspace
spelling I19-R120-10915-1737792024-11-27T20:12:48Z http://sedici.unlp.edu.ar/handle/10915/173779 GDP Nowcasting: assessing business cycle conditions in Argentina D'Amato, Laura Inés Garegnani, María Lorena Ruiz y Blanco, Emilio R. 2014-11 2014 2024-11-27T18:39:07Z en Ciencias Económicas nowcasting bridge equations dynamic factor models Having a correct assessment of current business cycle conditions is one of the mayor challenges for monetary policy conduct. Given that GDP figures are available with a significant delay, central banks are increasingly using Nowcasting as a useful tool for having an immediate perception of economic conditions. Thus we develop a GDP growth nowcasting exercise using two approaches: bridge equations and a dynamic factor model. Both outperform a typical AR(1) benchmark in terms of forecasting accuracy. Moreover, the factor model outperforms the nowcast using bridge equations. Following Giacomini and White (2004) we confirm that these differences are statistically significant. Tener una correcta evaluación de las condiciones actuales del ciclo económico es uno de los mayores retos para la conducción de la política monetaria. Teniendo en cuenta que las cifras del PIB están disponibles con un retraso significativo, el uso de Nowcasting para tener una percepción inmediata de las condiciones cíclicas de la economía ha sido crecientemente adoptado por los bancos centrales. Desarrollamos un ejercicio de Nowcast del crecimiento del PIB utilizando dos enfoques: bridge equations y factor models. Ambos métodos superan en capacidad predictiva a un benchmark AR(1). Adicionalmente, el Nowcast basado en un factor model supera al de bridge equations. Finalmente, Siguiendo a Giacomini y White (2004) confirmamos que estas diferencias son estadísticamente significativas. 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
nowcasting
bridge equations
dynamic factor models
spellingShingle Ciencias Económicas
nowcasting
bridge equations
dynamic factor models
D'Amato, Laura Inés
Garegnani, María Lorena
Ruiz y Blanco, Emilio R.
GDP Nowcasting: assessing business cycle conditions in Argentina
topic_facet Ciencias Económicas
nowcasting
bridge equations
dynamic factor models
description Having a correct assessment of current business cycle conditions is one of the mayor challenges for monetary policy conduct. Given that GDP figures are available with a significant delay, central banks are increasingly using Nowcasting as a useful tool for having an immediate perception of economic conditions. Thus we develop a GDP growth nowcasting exercise using two approaches: bridge equations and a dynamic factor model. Both outperform a typical AR(1) benchmark in terms of forecasting accuracy. Moreover, the factor model outperforms the nowcast using bridge equations. Following Giacomini and White (2004) we confirm that these differences are statistically significant.
format Objeto de conferencia
Objeto de conferencia
author D'Amato, Laura Inés
Garegnani, María Lorena
Ruiz y Blanco, Emilio R.
author_facet D'Amato, Laura Inés
Garegnani, María Lorena
Ruiz y Blanco, Emilio R.
author_sort D'Amato, Laura Inés
title GDP Nowcasting: assessing business cycle conditions in Argentina
title_short GDP Nowcasting: assessing business cycle conditions in Argentina
title_full GDP Nowcasting: assessing business cycle conditions in Argentina
title_fullStr GDP Nowcasting: assessing business cycle conditions in Argentina
title_full_unstemmed GDP Nowcasting: assessing business cycle conditions in Argentina
title_sort gdp nowcasting: assessing business cycle conditions in argentina
publishDate 2014
url http://sedici.unlp.edu.ar/handle/10915/173779
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AT ruizyblancoemilior gdpnowcastingassessingbusinesscycleconditionsinargentina
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