Statistical modeling of unemployment duration in South Africa

Unemployment in South Africa has continued to be consistently high as indicated by the various reports published by Statistics South Africa. Unemployment is a global problem where in Organisation for Economic Co-operation and Development (OECD) countries it is related to economic condition. The econ...

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Main Author: Nonyana, Jeanette Zandile
Other Authors: Njuho, P. M.
Format: Others
Language:en
Published: 2016
Subjects:
Online Access:Nonyana, Jeanette Zandile (2015) Statistical modeling of unemployment duration in South Africa, University of South Africa, Pretoria, <http://hdl.handle.net/10500/20982>
http://hdl.handle.net/10500/20982
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-unisa-oai-uir.unisa.ac.za-10500-209822018-11-19T17:15:23Z Statistical modeling of unemployment duration in South Africa Nonyana, Jeanette Zandile Njuho, P. M. Unemployment duration Panel data Duration dependence Non-parametric Semi-parametric Survival technique Exit probability 331.1370968 Unemployment -- South Africa -- Statistics Unemployment in South Africa has continued to be consistently high as indicated by the various reports published by Statistics South Africa. Unemployment is a global problem where in Organisation for Economic Co-operation and Development (OECD) countries it is related to economic condition. The economic conditions are not solely responsible for the problem of unemployment in South Africa. Consistently high unemployment rates are observed irrespective of the level of economic growth, where unemployment responds marginally to changes Gross Domestic Product (GDP). To understand factors that influence unemployment in South Africa, we need to understand the dynamics of the unemployed population. This study aims at providing a statistical tool useful in improving the understanding of the labour market and enhancing of the labour market policy relevancy. Survival techniques are applied to determine duration dependence, probabilities of exiting unemployment, and the association between socio-demographic factors and unemployment duration. A labour force panel data from Statistic South Africa is used to analyse the time it takes an unemployed person to find employment. The dataset has 4.9 million people who were unemployed during the third quarter of 2013. The data is analysed by computing non-parametric and semi-parametric estimates to avoid making assumption about the functional form of the hazard. The results indicate that the hazard of finding employment is reduced as people spend more time in unemployment (negative duration dependence). People who are unemployed for less than six months have higher hazard functions. The hazards of leaving unemployment at any given duration are significantly lower for people in the following categories - females, adults, education level of lower than tertiary, single or divorced, attending school or doing other activities prior to job search and no work experience. The findings suggest an existence of association between demographics and the length of stay in unemployment; which reflect the nature of the labour market. Due to lower exit probabilities young people spent more time unemployed thus growing out of the age group which is more likely to be employed. Seasonal jobs are not convenient for pregnant women and for those with young kids at their care thus decreasing their employment probabilities. Analysis of factors that affect employment probabilities should be based on datasets which have no seasonal components. The findings suggest that the seasonal components on the labour force panel impacted on the results. According to the findings analysis of unemployment durations can be improved by analysing men and women separately. Men and women have different challenges in the labour market, which influence the association between other demographic factors and unemployment duration Statistics M. Sc. (Statistics) 2016-07-12T07:00:23Z 2016-07-12T07:00:23Z 2015-12 2016-07-12 Dissertation Nonyana, Jeanette Zandile (2015) Statistical modeling of unemployment duration in South Africa, University of South Africa, Pretoria, <http://hdl.handle.net/10500/20982> http://hdl.handle.net/10500/20982 en 1 online resource (vii, 74 leaves) : tables, graphs
collection NDLTD
language en
format Others
sources NDLTD
topic Unemployment duration
Panel data
Duration dependence
Non-parametric
Semi-parametric
Survival technique
Exit probability
331.1370968
Unemployment -- South Africa -- Statistics
spellingShingle Unemployment duration
Panel data
Duration dependence
Non-parametric
Semi-parametric
Survival technique
Exit probability
331.1370968
Unemployment -- South Africa -- Statistics
Nonyana, Jeanette Zandile
Statistical modeling of unemployment duration in South Africa
description Unemployment in South Africa has continued to be consistently high as indicated by the various reports published by Statistics South Africa. Unemployment is a global problem where in Organisation for Economic Co-operation and Development (OECD) countries it is related to economic condition. The economic conditions are not solely responsible for the problem of unemployment in South Africa. Consistently high unemployment rates are observed irrespective of the level of economic growth, where unemployment responds marginally to changes Gross Domestic Product (GDP). To understand factors that influence unemployment in South Africa, we need to understand the dynamics of the unemployed population. This study aims at providing a statistical tool useful in improving the understanding of the labour market and enhancing of the labour market policy relevancy. Survival techniques are applied to determine duration dependence, probabilities of exiting unemployment, and the association between socio-demographic factors and unemployment duration. A labour force panel data from Statistic South Africa is used to analyse the time it takes an unemployed person to find employment. The dataset has 4.9 million people who were unemployed during the third quarter of 2013. The data is analysed by computing non-parametric and semi-parametric estimates to avoid making assumption about the functional form of the hazard. The results indicate that the hazard of finding employment is reduced as people spend more time in unemployment (negative duration dependence). People who are unemployed for less than six months have higher hazard functions. The hazards of leaving unemployment at any given duration are significantly lower for people in the following categories - females, adults, education level of lower than tertiary, single or divorced, attending school or doing other activities prior to job search and no work experience. The findings suggest an existence of association between demographics and the length of stay in unemployment; which reflect the nature of the labour market. Due to lower exit probabilities young people spent more time unemployed thus growing out of the age group which is more likely to be employed. Seasonal jobs are not convenient for pregnant women and for those with young kids at their care thus decreasing their employment probabilities. Analysis of factors that affect employment probabilities should be based on datasets which have no seasonal components. The findings suggest that the seasonal components on the labour force panel impacted on the results. According to the findings analysis of unemployment durations can be improved by analysing men and women separately. Men and women have different challenges in the labour market, which influence the association between other demographic factors and unemployment duration === Statistics === M. Sc. (Statistics)
author2 Njuho, P. M.
author_facet Njuho, P. M.
Nonyana, Jeanette Zandile
author Nonyana, Jeanette Zandile
author_sort Nonyana, Jeanette Zandile
title Statistical modeling of unemployment duration in South Africa
title_short Statistical modeling of unemployment duration in South Africa
title_full Statistical modeling of unemployment duration in South Africa
title_fullStr Statistical modeling of unemployment duration in South Africa
title_full_unstemmed Statistical modeling of unemployment duration in South Africa
title_sort statistical modeling of unemployment duration in south africa
publishDate 2016
url Nonyana, Jeanette Zandile (2015) Statistical modeling of unemployment duration in South Africa, University of South Africa, Pretoria, <http://hdl.handle.net/10500/20982>
http://hdl.handle.net/10500/20982
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