Assesing Hp Filter Performance for Argentina and U.S. Macro Aggregates
- Autores
- Ahumada, Hildegart; Garegnani, María Lorena
- Año de publicación
- 2000
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Hodrick-Prescott filter has been the favourite empirical technique among researchers studying “cycles”. Software facilities and the optimality criterion, from which the filter can be derived, can explain its wide use. However, different shortcomings and drawbacks have been pointed out in the literature, as alteration of variability and persistence and detecting spurious cycles and correlations. This paper discusses these criticisms from an empirical point of view trying to clarify what the filter can and cannot do. In particular, a less mechanical use for descriptive analysis is proposed: testing how the estimated cyclical component behaves and using autocorrelation adjusted standard errors to evaluate cross correlations to differentiate the “genuine” from “spurious” case. Simulation results to test these bivariate correlations when there is a “genuine” relationship are presented. Some examples of descriptive analysis for macro aggregates (real activity, trade flows and money) of Argentina and USA are reported to show that not always the filter is appropriate. Simple tools are used to appreciate how the filtered series result and to evaluate cross correlations.
Facultad de Ciencias Económicas - Materia
-
Ciencias Económicas
HP filter
Cycles
Spurious cycles
Genuine cross correlation - 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:10915/123574
Ver los metadatos del registro completo
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Assesing Hp Filter Performance for Argentina and U.S. Macro AggregatesAhumada, HildegartGaregnani, María LorenaCiencias EconómicasHP filterCyclesSpurious cyclesGenuine cross correlationHodrick-Prescott filter has been the favourite empirical technique among researchers studying “cycles”. Software facilities and the optimality criterion, from which the filter can be derived, can explain its wide use. However, different shortcomings and drawbacks have been pointed out in the literature, as alteration of variability and persistence and detecting spurious cycles and correlations. This paper discusses these criticisms from an empirical point of view trying to clarify what the filter can and cannot do. In particular, a less mechanical use for descriptive analysis is proposed: testing how the estimated cyclical component behaves and using autocorrelation adjusted standard errors to evaluate cross correlations to differentiate the “genuine” from “spurious” case. Simulation results to test these bivariate correlations when there is a “genuine” relationship are presented. Some examples of descriptive analysis for macro aggregates (real activity, trade flows and money) of Argentina and USA are reported to show that not always the filter is appropriate. Simple tools are used to appreciate how the filtered series result and to evaluate cross correlations.Facultad de Ciencias Económicas2000info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf257-284http://sedici.unlp.edu.ar/handle/10915/123574enginfo:eu-repo/semantics/altIdentifier/issn/1514-0326info:eu-repo/semantics/altIdentifier/issn/1667-6726info:eu-repo/semantics/altIdentifier/doi/10.1080/15140326.2000.12040551info: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:UNLP2025-09-03T11:01:34Zoai:sedici.unlp.edu.ar:10915/123574Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 11:01:34.433SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Assesing Hp Filter Performance for Argentina and U.S. Macro Aggregates |
title |
Assesing Hp Filter Performance for Argentina and U.S. Macro Aggregates |
spellingShingle |
Assesing Hp Filter Performance for Argentina and U.S. Macro Aggregates Ahumada, Hildegart Ciencias Económicas HP filter Cycles Spurious cycles Genuine cross correlation |
title_short |
Assesing Hp Filter Performance for Argentina and U.S. Macro Aggregates |
title_full |
Assesing Hp Filter Performance for Argentina and U.S. Macro Aggregates |
title_fullStr |
Assesing Hp Filter Performance for Argentina and U.S. Macro Aggregates |
title_full_unstemmed |
Assesing Hp Filter Performance for Argentina and U.S. Macro Aggregates |
title_sort |
Assesing Hp Filter Performance for Argentina and U.S. Macro Aggregates |
dc.creator.none.fl_str_mv |
Ahumada, Hildegart Garegnani, María Lorena |
author |
Ahumada, Hildegart |
author_facet |
Ahumada, Hildegart Garegnani, María Lorena |
author_role |
author |
author2 |
Garegnani, María Lorena |
author2_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Económicas HP filter Cycles Spurious cycles Genuine cross correlation |
topic |
Ciencias Económicas HP filter Cycles Spurious cycles Genuine cross correlation |
dc.description.none.fl_txt_mv |
Hodrick-Prescott filter has been the favourite empirical technique among researchers studying “cycles”. Software facilities and the optimality criterion, from which the filter can be derived, can explain its wide use. However, different shortcomings and drawbacks have been pointed out in the literature, as alteration of variability and persistence and detecting spurious cycles and correlations. This paper discusses these criticisms from an empirical point of view trying to clarify what the filter can and cannot do. In particular, a less mechanical use for descriptive analysis is proposed: testing how the estimated cyclical component behaves and using autocorrelation adjusted standard errors to evaluate cross correlations to differentiate the “genuine” from “spurious” case. Simulation results to test these bivariate correlations when there is a “genuine” relationship are presented. Some examples of descriptive analysis for macro aggregates (real activity, trade flows and money) of Argentina and USA are reported to show that not always the filter is appropriate. Simple tools are used to appreciate how the filtered series result and to evaluate cross correlations. Facultad de Ciencias Económicas |
description |
Hodrick-Prescott filter has been the favourite empirical technique among researchers studying “cycles”. Software facilities and the optimality criterion, from which the filter can be derived, can explain its wide use. However, different shortcomings and drawbacks have been pointed out in the literature, as alteration of variability and persistence and detecting spurious cycles and correlations. This paper discusses these criticisms from an empirical point of view trying to clarify what the filter can and cannot do. In particular, a less mechanical use for descriptive analysis is proposed: testing how the estimated cyclical component behaves and using autocorrelation adjusted standard errors to evaluate cross correlations to differentiate the “genuine” from “spurious” case. Simulation results to test these bivariate correlations when there is a “genuine” relationship are presented. Some examples of descriptive analysis for macro aggregates (real activity, trade flows and money) of Argentina and USA are reported to show that not always the filter is appropriate. Simple tools are used to appreciate how the filtered series result and to evaluate cross correlations. |
publishDate |
2000 |
dc.date.none.fl_str_mv |
2000 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Articulo http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/123574 |
url |
http://sedici.unlp.edu.ar/handle/10915/123574 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/issn/1514-0326 info:eu-repo/semantics/altIdentifier/issn/1667-6726 info:eu-repo/semantics/altIdentifier/doi/10.1080/15140326.2000.12040551 |
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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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application/pdf 257-284 |
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