Education and the probability of being poor in Peru
Descripción del Articulo
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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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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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 audio/mpeg 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 2961-2845 10.21754/iecos.v18i0 reponame:Revistas - Universidad Nacional de Ingeniería instname:Universidad Nacional de Ingeniería instacron:UNI |
instname_str |
Universidad Nacional de Ingeniería |
instacron_str |
UNI |
institution |
UNI |
reponame_str |
Revistas - Universidad Nacional de Ingeniería |
collection |
Revistas - Universidad Nacional de Ingeniería |
repository.name.fl_str_mv |
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repository.mail.fl_str_mv |
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1833562788857905152 |
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13.982926 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).