A bayesian hierarchical modelling of small area variation in youth unemployment in Namibia
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Date
2023
Authors
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Journal ISSN
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Publisher
University of Namibia
Abstract
Youth unemployment has been one of Namibia's socio-economic problems, which has
the potential to have significant and serious social repercussions on economic growth
and development and could cause social exclusion and unrest in the affected country.
Youth unemployment rates estimates are only available at the national (46.1 percent
in 2018) and regional levels in Namibia; however, the Namibia Labour Force survey
(NLFS) does not provide such statistics at small area e.g., at constituency level. The
census data could be used to provide estimates of youth unemployment at constituency
level; however, the data is only obtained every 10 years which in most cases the time
frame is too long given the developmental changes that may take place during the 10-
year periods. In view of these challenges, it is paramount to estimate the variation in
unemployment rates at constituency level for possible targeted interventions within
regions. In comparison to conventional small area estimation (SAE) models, the
hierarchical Bayesian approach to SAE problems has several benefits, one of which is
the ability to properly account for the kind of surveyed variable. For this reason, the
main objective of this study was to estimate the risk of youth unemployment at
constituency level using the 2018 NLFS data. The likelihood was estimated using a
hierarchical Bayesian model and results from the study showed that the chance of
youths being unemployed was very high among male youths than female youths in
urban areas with OR=1.35 (1.10, 1.66) and OR=0.79 (0.65, 0.96) respectively. Several
models were fitted, and the best model was used to estimate the probability of being
unemployed amongst the male and female youths (with the DIC values of 4900.90 for
the males and 5719.48 for females). The best model considered the fixed effects
together with the unstructured spatial effects at constituency and regional levels. Even
though employment is the result of aggregate demographic and socio-economic
factors, the study recommends that employment opportunities specifically targeting
youths should be created by either government or private sectors in constituencies
especially those in the rural constituencies. Furthermore, special attention should be
paid to integrating the youth into the labour market by improving their educational
levels
Description
A thesis submitted in partial fulfilment of the requirements for the degree of master of science in applied statistics and demography
Keywords
Unemployment rate, Youth, Small area estimation, Hierarchical Bayesian