Multivariate Bayesian spatial modelling of child labour and out of school children in Nigeria: mapping areas of excess risk

This research implemented a Bayesian multivariate spatial model to identify areas where the risk of children being out of school, engaging in child labour, or undertaking hazardous work differs from the risk of poverty in Nigeria. Using recently released geo-coded UNICEF MICS survey data, the results showed how the spatial distribution of the three outcomes studied differ and highlighted specific areas where the excess risk for each outcome, after accounting for poverty, is high. The model was also used to predict the risk of each outcome across the whole of Nigeria at a high spatial resolution.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-16
DOI
https://doi.org/10.5281/zenodo.15229825
Primary Topic
Musicology and Musical Analysis
Type
article
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article

Multivariate Bayesian spatial modelling of child labour and out of school children in Nigeria: mapping areas of excess risk

Zenodo (CERN European Organization for Nuclear Research)
Musicology and Musical Analysis
article

Multivariate Bayesian spatial modelling of child labour and out of school children in Nigeria: mapping areas of excess risk

article en

Abstract

This research implemented a Bayesian multivariate spatial model to identify areas where the risk of children being out of school, engaging in child labour, or undertaking hazardous work differs from the risk of poverty in Nigeria. Using recently released geo-coded UNICEF MICS survey data, the results showed how the spatial distribution of the three outcomes studied differ and highlighted specific areas where the excess risk for each outcome, after accounting for poverty, is high. The model was also used to predict the risk of each outcome across the whole of Nigeria at a high spatial resolution.

Zenodo (CERN European Organization for Nuclear Research)
University of Manchester (GB), Space Research Institute (UA), Manchester University (US)
No poverty
Openalex Percentile: Top 52%
Musicology and Musical Analysis
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