Dynamic regression models with stochastic trends: an application to the unemployment -growth relation
- Autores
- Abril, Juan Carlos
- Año de publicación
- 2003
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The form in which the national product affects the level of unemployment has become one of the most relevant macroeconomic subjects. A simple form of measuring the relation between the increase (decrease) of the national product and the decrease (increase) of the unemployment rate is explained by the so called ``Okun Law´´, according to which it is not expected, except under very special conditions, that each point of increase of the product results in a point of increase of the employment and, consequently, a fall of one point in the unemployment rate. The relation between growth and unemployment is much more complex and can be resumed in the following equation ut - ut-1 = - r (gt - ct), where ut is the unemployment rate, gt the percentage growth of the product and ct represents the percentage growth of the product that it is needed to maintain the unemployment level of the previous period. One of our objectives is to estimate ct .
Fil: Abril, Juan Carlos. Universidad Nacional de Tucumán. Facultad de Ciencias Económicas. Instituto de Investigaciones Estadísticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina - Materia
-
STYLIZED FACTS
KALMAN FILTERING
GROWTH
UNEMPLOYMENT - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/105977
Ver los metadatos del registro completo
id |
CONICETDig_016d4da46bf395083dca3368a18ab648 |
---|---|
oai_identifier_str |
oai:ri.conicet.gov.ar:11336/105977 |
network_acronym_str |
CONICETDig |
repository_id_str |
3498 |
network_name_str |
CONICET Digital (CONICET) |
spelling |
Dynamic regression models with stochastic trends: an application to the unemployment -growth relationAbril, Juan CarlosSTYLIZED FACTSKALMAN FILTERINGGROWTHUNEMPLOYMENThttps://purl.org/becyt/ford/5.2https://purl.org/becyt/ford/5The form in which the national product affects the level of unemployment has become one of the most relevant macroeconomic subjects. A simple form of measuring the relation between the increase (decrease) of the national product and the decrease (increase) of the unemployment rate is explained by the so called ``Okun Law´´, according to which it is not expected, except under very special conditions, that each point of increase of the product results in a point of increase of the employment and, consequently, a fall of one point in the unemployment rate. The relation between growth and unemployment is much more complex and can be resumed in the following equation ut - ut-1 = - r (gt - ct), where ut is the unemployment rate, gt the percentage growth of the product and ct represents the percentage growth of the product that it is needed to maintain the unemployment level of the previous period. One of our objectives is to estimate ct .Fil: Abril, Juan Carlos. Universidad Nacional de Tucumán. Facultad de Ciencias Económicas. Instituto de Investigaciones Estadísticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaPakistan Journal of Statistics2003-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/105977Abril, Juan Carlos; Dynamic regression models with stochastic trends: an application to the unemployment -growth relation; Pakistan Journal of Statistics; Pakistan Journal of Statistics; 19; 2; 5-2003; 175-1981012-9367CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.pakjs.com/1985-to-2016/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:20:28Zoai:ri.conicet.gov.ar:11336/105977instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:20:29.163CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Dynamic regression models with stochastic trends: an application to the unemployment -growth relation |
title |
Dynamic regression models with stochastic trends: an application to the unemployment -growth relation |
spellingShingle |
Dynamic regression models with stochastic trends: an application to the unemployment -growth relation Abril, Juan Carlos STYLIZED FACTS KALMAN FILTERING GROWTH UNEMPLOYMENT |
title_short |
Dynamic regression models with stochastic trends: an application to the unemployment -growth relation |
title_full |
Dynamic regression models with stochastic trends: an application to the unemployment -growth relation |
title_fullStr |
Dynamic regression models with stochastic trends: an application to the unemployment -growth relation |
title_full_unstemmed |
Dynamic regression models with stochastic trends: an application to the unemployment -growth relation |
title_sort |
Dynamic regression models with stochastic trends: an application to the unemployment -growth relation |
dc.creator.none.fl_str_mv |
Abril, Juan Carlos |
author |
Abril, Juan Carlos |
author_facet |
Abril, Juan Carlos |
author_role |
author |
dc.subject.none.fl_str_mv |
STYLIZED FACTS KALMAN FILTERING GROWTH UNEMPLOYMENT |
topic |
STYLIZED FACTS KALMAN FILTERING GROWTH UNEMPLOYMENT |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/5.2 https://purl.org/becyt/ford/5 |
dc.description.none.fl_txt_mv |
The form in which the national product affects the level of unemployment has become one of the most relevant macroeconomic subjects. A simple form of measuring the relation between the increase (decrease) of the national product and the decrease (increase) of the unemployment rate is explained by the so called ``Okun Law´´, according to which it is not expected, except under very special conditions, that each point of increase of the product results in a point of increase of the employment and, consequently, a fall of one point in the unemployment rate. The relation between growth and unemployment is much more complex and can be resumed in the following equation ut - ut-1 = - r (gt - ct), where ut is the unemployment rate, gt the percentage growth of the product and ct represents the percentage growth of the product that it is needed to maintain the unemployment level of the previous period. One of our objectives is to estimate ct . Fil: Abril, Juan Carlos. Universidad Nacional de Tucumán. Facultad de Ciencias Económicas. Instituto de Investigaciones Estadísticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina |
description |
The form in which the national product affects the level of unemployment has become one of the most relevant macroeconomic subjects. A simple form of measuring the relation between the increase (decrease) of the national product and the decrease (increase) of the unemployment rate is explained by the so called ``Okun Law´´, according to which it is not expected, except under very special conditions, that each point of increase of the product results in a point of increase of the employment and, consequently, a fall of one point in the unemployment rate. The relation between growth and unemployment is much more complex and can be resumed in the following equation ut - ut-1 = - r (gt - ct), where ut is the unemployment rate, gt the percentage growth of the product and ct represents the percentage growth of the product that it is needed to maintain the unemployment level of the previous period. One of our objectives is to estimate ct . |
publishDate |
2003 |
dc.date.none.fl_str_mv |
2003-05 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 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://hdl.handle.net/11336/105977 Abril, Juan Carlos; Dynamic regression models with stochastic trends: an application to the unemployment -growth relation; Pakistan Journal of Statistics; Pakistan Journal of Statistics; 19; 2; 5-2003; 175-198 1012-9367 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/105977 |
identifier_str_mv |
Abril, Juan Carlos; Dynamic regression models with stochastic trends: an application to the unemployment -growth relation; Pakistan Journal of Statistics; Pakistan Journal of Statistics; 19; 2; 5-2003; 175-198 1012-9367 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://www.pakjs.com/1985-to-2016/ |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Pakistan Journal of Statistics |
publisher.none.fl_str_mv |
Pakistan Journal of Statistics |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
_version_ |
1842981118481006592 |
score |
12.48226 |