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Since 1997, when Namibia started conducting National labour force surveys, there is no in-depth analysis of underemployment in the country. However, time-related under-employment is reported to be currently at 3.5% (NSA, 2013). This rate is high if measured exclusively without self-employed proportion. Thus, this study is intended to analyse factors that are associated with number of hours that employed persons spend working. Specifically, the research investigates the socio-economic factors of employed individuals that lead to time-related underemployment in Namibia and measures the level of…mehr

Produktbeschreibung
Since 1997, when Namibia started conducting National labour force surveys, there is no in-depth analysis of underemployment in the country. However, time-related under-employment is reported to be currently at 3.5% (NSA, 2013). This rate is high if measured exclusively without self-employed proportion. Thus, this study is intended to analyse factors that are associated with number of hours that employed persons spend working. Specifically, the research investigates the socio-economic factors of employed individuals that lead to time-related underemployment in Namibia and measures the level of this visible underemployment among regions in order to compute the gap between actual total number of hours and total usual number of hours. The research is based on secondary data acquired from Namibia Statistic Agency (NSA). Thus, it adopted all sampling and data collection methods. Binary logistic regression was used to test for association between variables of interest; occupation and industries with respectively the dependent variable total actual number of hours, with 35 hours as the cut-off point.
Autorenporträt
Lukas Silas was awarded Bachelor's of Science (Honours Degree) in Population Studies & Statistics from the University of Namibia. He is highly interested in Social and Labour Statistics, Child mortality and Gender Studies. He is looking for an opportunity to peruse his career in Labour and Economic Statistics domain.