Determinants of unemployment and earnings in South Africa

Thesis (M. Sc. (Statistics)) --University of Limpopo, 2017. === South Africa is one of the countries with chronic high unemployment rate. The unemployment rate has consistently been above 24% for a considerable period of time. It is important for policy and decision makers to know the type of person...

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Main Author: Mathebula, Inocent Nelson
Other Authors: Tessera, A.
Format: Others
Language:en
Published: University of Limpopo 2018
Subjects:
Online Access:http://hdl.handle.net/10386/1958
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-ul-oai-ulspace.ul.ac.za-10386-19582019-10-30T04:07:01Z Determinants of unemployment and earnings in South Africa Mathebula, Inocent Nelson Tessera, A. Yibas, N Yibas, N. Unemployment Highest educational level completed Population group Marital status Unemployment -- South Africa. Unemployement -- Social aspects Thesis (M. Sc. (Statistics)) --University of Limpopo, 2017. South Africa is one of the countries with chronic high unemployment rate. The unemployment rate has consistently been above 24% for a considerable period of time. It is important for policy and decision makers to know the type of persons who are unemployed, and underemployed in order to come up with the right intervention. The purpose of this study was to find and describe the determinants of unemployment, underemployment, and earnings in South Africa. In order to realize the objectives of the study, secondary data from 2012 Quarterly Labour Force Survey was used. Statistics South Africa collects labour market related information from persons between the age of 15 and 64. The data have information on status of unemployment, underemployment and earnings and other related to variables. Logistic regression was applied on the data and it was found that age, gender, population group, marital status, level of education, and province were significant determinants of unemployment in South Africa. Gender, population group, sector, marital status and contract duration were found to be significantly associated with time-related underemployment. Generalised linear model was applied on the data and it was found that gender, population group, marital status, level of education contract duration, geographical location, and sector were the determinants of earnings. 2018-06-11T12:15:26Z 2018-06-11T12:15:26Z 2017 Thesis http://hdl.handle.net/10386/1958 en pdf ix, 82 leaves University of Limpopo
collection NDLTD
language en
format Others
sources NDLTD
topic Unemployment
Highest educational level completed
Population group
Marital status
Unemployment -- South Africa.
Unemployement -- Social aspects
spellingShingle Unemployment
Highest educational level completed
Population group
Marital status
Unemployment -- South Africa.
Unemployement -- Social aspects
Mathebula, Inocent Nelson
Determinants of unemployment and earnings in South Africa
description Thesis (M. Sc. (Statistics)) --University of Limpopo, 2017. === South Africa is one of the countries with chronic high unemployment rate. The unemployment rate has consistently been above 24% for a considerable period of time. It is important for policy and decision makers to know the type of persons who are unemployed, and underemployed in order to come up with the right intervention. The purpose of this study was to find and describe the determinants of unemployment, underemployment, and earnings in South Africa. In order to realize the objectives of the study, secondary data from 2012 Quarterly Labour Force Survey was used. Statistics South Africa collects labour market related information from persons between the age of 15 and 64. The data have information on status of unemployment, underemployment and earnings and other related to variables. Logistic regression was applied on the data and it was found that age, gender, population group, marital status, level of education, and province were significant determinants of unemployment in South Africa. Gender, population group, sector, marital status and contract duration were found to be significantly associated with time-related underemployment. Generalised linear model was applied on the data and it was found that gender, population group, marital status, level of education contract duration, geographical location, and sector were the determinants of earnings.
author2 Tessera, A.
author_facet Tessera, A.
Mathebula, Inocent Nelson
author Mathebula, Inocent Nelson
author_sort Mathebula, Inocent Nelson
title Determinants of unemployment and earnings in South Africa
title_short Determinants of unemployment and earnings in South Africa
title_full Determinants of unemployment and earnings in South Africa
title_fullStr Determinants of unemployment and earnings in South Africa
title_full_unstemmed Determinants of unemployment and earnings in South Africa
title_sort determinants of unemployment and earnings in south africa
publisher University of Limpopo
publishDate 2018
url http://hdl.handle.net/10386/1958
work_keys_str_mv AT mathebulainocentnelson determinantsofunemploymentandearningsinsouthafrica
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