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...

Descripción completa

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
Descripción
Sumario: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.
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).