Spatial analysis of the socio-educational association with delay and school dropout in regular primary education by department, Peru 2016 to 2021

Authors

  • Magen Danielle Infante Rojas National University of Engineering, Lima, Peru https://orcid.org/0000-0002-9292-7457
  • Augusto Mayorca-Tinoco Cesar Vallejo University, Lima, Peru
  • Wilmer Wilson Aspajo Quiñonez Student - FIEECS - National University of Engineering, Lima, Peru
  • Miliani Stephany Quispe Bejar Student - FIEECS - National University of Engineering, Lima, Peru
  • Ruth Samanta Huamani Llactahuaman Student - FIEECS - National University of Engineering, Lima, Peru
  • Cristopher Norman Malaga Espinoza Student - FIEECS - National University of Engineering, Lima, Peru

DOI:

https://doi.org/10.21754/iecos.v24i2.1972

Keywords:

Socio-educational spatial autocorrelation, Univariate Morán Index, Bivariate Morán Index, primary school inter-annual dropout, primary school backwardness, Geary Clustering

Abstract

Basic Education in Peru is key factor for the development of the country. The Primary Education indicators published by the Institute of Statistics and Informatics (INEI) reveals the need for further research. Although there are various studies regarding primary education, they have not been as exhaustive as expected. For each level of basic education, the real-life situations are different, one of these levels is primary education, which the majority of Peruvians access. The objective is to establish the spatial socio-educational association of backwardness and school dropout. A data frame, called dataframe, was built with the Educational Quality Statistics (ESCALE) of the Ministry of Education (MINEDU) of Peru. In addition to spatial descriptive analysis, spatial auto-correlation at the Departmental level of backwardness and school dropout was verified, moreover, the factors chronic childhood malnutrition, children and adolescents who work and students with mothers with completed higher education are spatially associated with the backwardness and school dropout. This association was confirmed through the Weighted Spatial Regression model.

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Author Biography

Magen Danielle Infante Rojas, National University of Engineering, Lima, Peru

This research sought to estimate the Simplified Azbel model to verify that it is a good fit to Peruvian mortality rates for pension purposes using three estimation methods, with the maximum likelihood (ML), Log-linear Regression type and ordinary least squares (OLS) methods. The mortality tables were segmented by ages near zero, intermediate ages and ages near one. It was confirmed that there is a difference in fit between males and females. With the A/E and ARL similarity metrics, the original and the estimated mortality tables, the hypothesis is corroborated since it is concluded that the best estimates resulted for the SP2005 tables, for the male gender with the Log-linear Regression type and ordinary least squares methods, except for the range between 50 and 90 years of age. In women, there is only a good fit with the Log-linear Regression type method from 15 years of age onwards.  The fit to the SPP2017 tables is barely noticeable in men with the Log-linear Regression type method from the age of 70 years and in women from the age of 80 years.

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Published

2023-12-31

How to Cite

Infante Rojas, M. D., Mayorca-Tinoco , A., Aspajo Quiñonez, W. W., Quispe Bejar, M. S., Huamani Llactahuaman, R. S., & Malaga Espinoza, C. N. (2023). Spatial analysis of the socio-educational association with delay and school dropout in regular primary education by department, Peru 2016 to 2021. Revista IECOS, 24(2), 101–132. https://doi.org/10.21754/iecos.v24i2.1972

Issue

Vol. 24 No. 2 (2023)

Section

Research Articles

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Copyright (c) 2023 Magen Danielle Infante Rojas, Augusto Mayorca Tinoco , Wilmer Wilson Aspajo Quiñonez, Miliani Stephany Quispe Bejar, Ruth Samanta Huamani Llactahuaman, Cristopher Norman Malaga Espinoza

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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