Education and the probability of being poor in Peru

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The main objective of this research is to analyze the educational, de-mographic, geographic, labor market, housing, income and wealth factors related to the head of household and poverty through a logit model, trying to explain the probability of being monetary poor. For this, the data collected by...

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Detalles Bibliográficos
Autor: Quiroz Vera, Eduardo Fernando
Formato: artículo
Fecha de Publicación:2017
Institución:Universidad Nacional de Ingeniería
Repositorio:Revistas - Universidad Nacional de Ingeniería
Lenguaje:español
inglés
OAI Identifier:oai:oai:revistas.uni.edu.pe:article/1176
Enlace del recurso:https://revistas.uni.edu.pe/index.php/iecos/article/view/1176
Nivel de acceso:acceso abierto
Materia:Educación
pobreza monetaria
Logit
Education
Monetary poverty
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spelling Education and the probability of being poor in PeruLa educación y la probabilidad de ser pobre en el PerúQuiroz Vera, Eduardo FernandoEducaciónpobreza monetariaLogitEducation Monetary poverty LogitThe main objective of this research is to analyze the educational, de-mographic, geographic, labor market, housing, income and wealth factors related to the head of household and poverty through a logit model, trying to explain the probability of being monetary poor. For this, the data collected by the 2016 National Household Survey conducted by INEI was analyzed. Through the first logit model, it is found that education -due to its effects on productivity and income generation- is a key instrument in the policy of overcoming poverty, since the higher the level achieved in their studies, the greater the reductions in the probability of being poor; in particular, it is found that concluding university means reducing the probability of being poor by 14.1 percentage points, with respect to an individual who concludes secondary school, while concluding a technical career means reducing the probability of being poor by 9 percentage points with respect to an individual who concludes secondary school. The second logit model demonstrates the importance of education in the probability of being poor, but that it alone cannot exhibit positive returns if the design of public policies is not efficient and does not consider some aspects such as demographics, labor, property, geography and housing, which also explain the probability of being poor.El principal objetivo de esta investigación es analizar los factores educacionales, demográficos, geográficos, mercado laboral, vivienda, ingreso y patrimonio relacionados con el jefe de hogar y la pobreza a través de un modelo logit, tratando de explicar la probabilidad de ser pobre monetario. Para esto se analizó los datos recogidos por la Encuesta Nacional de Hogares del 2016 realizada por el INEI. A través del primer modelo logit se encuentra que la educación –por sus efectos sobre la productividad y la generación de ingresos– se constituye en un instrumento clave en la política de superación de la pobreza, puesto que si mayor es el nivel alcanzado en sus estudios, mayores son las reducciones en la probabilidad de ser pobre; en especial se encuentra que concluir la universidad significa reducir la probabilidad de ser pobre en 14,1 puntos porcentuales, con respecto a un individuo que concluye secundaria, mientras que concluir una carrera técnica significa reducir la probabilidad de ser pobre en 9 puntos porcentuales con respecto a un individuo que concluye secundaria. En el segundo modelo logit queda demostrada la importancia de la educación en la probabilidad de ser pobre, pero de que por sí sola no podrá exhibir retornos positivos si el diseño de las políticas públicas no son eficientes y no se consideran algunos aspectos como son los aspectos demográficos, laborales, patrimoniales, geográficos y de vivienda, que son los que también explican la probabilidad de ser pobre. Universidad Nacional de Ingeniería2017-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer ReviewedEvaluado por paresapplication/pdfaudio/mpegaudio/mpeghttps://revistas.uni.edu.pe/index.php/iecos/article/view/117610.21754/iecos.v18i0.1176revista IECOS; Vol. 18 (2017); 72-96Revista IECOS; Vol. 18 (2017); 72-962788-74802961-284510.21754/iecos.v18i0reponame:Revistas - Universidad Nacional de Ingenieríainstname:Universidad Nacional de Ingenieríainstacron:UNIspaenghttps://revistas.uni.edu.pe/index.php/iecos/article/view/1176/3145https://revistas.uni.edu.pe/index.php/iecos/article/view/1176/3146https://revistas.uni.edu.pe/index.php/iecos/article/view/1176/3147Derechos de autor 2017 Eduardo Fernando Quiroz Verahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:oai:revistas.uni.edu.pe:article/11762025-01-20T02:33:13Z
dc.title.none.fl_str_mv Education and the probability of being poor in Peru
La educación y la probabilidad de ser pobre en el Perú
title Education and the probability of being poor in Peru
spellingShingle Education and the probability of being poor in Peru
Quiroz Vera, Eduardo Fernando
Educación
pobreza monetaria
Logit
Education
Monetary poverty
Logit
title_short Education and the probability of being poor in Peru
title_full Education and the probability of being poor in Peru
title_fullStr Education and the probability of being poor in Peru
title_full_unstemmed Education and the probability of being poor in Peru
title_sort Education and the probability of being poor in Peru
dc.creator.none.fl_str_mv Quiroz Vera, Eduardo Fernando
author Quiroz Vera, Eduardo Fernando
author_facet Quiroz Vera, Eduardo Fernando
author_role author
dc.subject.none.fl_str_mv Educación
pobreza monetaria
Logit
Education
Monetary poverty
Logit
topic Educación
pobreza monetaria
Logit
Education
Monetary poverty
Logit
description The main objective of this research is to analyze the educational, de-mographic, geographic, labor market, housing, income and wealth factors related to the head of household and poverty through a logit model, trying to explain the probability of being monetary poor. For this, the data collected by the 2016 National Household Survey conducted by INEI was analyzed. Through the first logit model, it is found that education -due to its effects on productivity and income generation- is a key instrument in the policy of overcoming poverty, since the higher the level achieved in their studies, the greater the reductions in the probability of being poor; in particular, it is found that concluding university means reducing the probability of being poor by 14.1 percentage points, with respect to an individual who concludes secondary school, while concluding a technical career means reducing the probability of being poor by 9 percentage points with respect to an individual who concludes secondary school. The second logit model demonstrates the importance of education in the probability of being poor, but that it alone cannot exhibit positive returns if the design of public policies is not efficient and does not consider some aspects such as demographics, labor, property, geography and housing, which also explain the probability of being poor.
publishDate 2017
dc.date.none.fl_str_mv 2017-07-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer Reviewed
Evaluado por pares
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.uni.edu.pe/index.php/iecos/article/view/1176
10.21754/iecos.v18i0.1176
url https://revistas.uni.edu.pe/index.php/iecos/article/view/1176
identifier_str_mv 10.21754/iecos.v18i0.1176
dc.language.none.fl_str_mv spa
eng
language spa
eng
dc.relation.none.fl_str_mv https://revistas.uni.edu.pe/index.php/iecos/article/view/1176/3145
https://revistas.uni.edu.pe/index.php/iecos/article/view/1176/3146
https://revistas.uni.edu.pe/index.php/iecos/article/view/1176/3147
dc.rights.none.fl_str_mv Derechos de autor 2017 Eduardo Fernando Quiroz Vera
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2017 Eduardo Fernando Quiroz Vera
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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audio/mpeg
dc.publisher.none.fl_str_mv Universidad Nacional de Ingeniería
publisher.none.fl_str_mv Universidad Nacional de Ingeniería
dc.source.none.fl_str_mv revista IECOS; Vol. 18 (2017); 72-96
Revista IECOS; Vol. 18 (2017); 72-96
2788-7480
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10.21754/iecos.v18i0
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collection Revistas - Universidad Nacional de Ingeniería
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