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dc.contributor.authorMwangi, Mary M
dc.date.accessioned2014-08-04T08:28:14Z
dc.date.available2014-08-04T08:28:14Z
dc.date.issued2014-06
dc.identifier.citationMwangi,M.M.,June,2014. A Research Project Submitted In Partial Fulfillment Of The Requirement For The Degree Of Masters Of Science In Social Statistics Of The University Of Nairobi.en_US
dc.identifier.urihttp://hdl.handle.net/11295/73562
dc.description.abstractIn this project, we have modeled labor market performance in Sub-Sahara Africa using convex optimization. Labor market indicators were adopted as a reliable source of information capable of describing Sub-Sahara Africa labor market condition. We aimed at investigating a set of measures that could explain a maximum performance in the labor market using a set of variables categorized as independent, moderating, intervening, and dependent variables to labor market performance. Using linear programming, each category was considered as a constraint to labor market performance. Four constraint equations were constructed using factor analysis conducted on a set of variables in each category. The equations were named as employment by sector, labor force participation rate, status on employment, and working poverty. The objective function was constructed by fitting a multiple linear regression equation to a set of factors in the constraint equation. Using simplex method of solving linear programming problems, the solution revealed that out of the nine selected indicators, only four could explain Sub-Sahara Africa labor market performance. These were unemployment rate, labor force participation rate, labor productivity, and working poverty. This predictive model advises anybody concerned with Sub-Sahara Africa labor market on the areas that need more emphasis for a maximum performance to be realized.en_US
dc.language.isoenen_US
dc.publisherUniversity Of Nairobien_US
dc.subjectLabor market indicators, labor market performance, Sub-Sahara Africa, labor forceen_US
dc.titleModeling Labor Market Performance In Sub-Sahara Africa Using Convex Optimization Techniquesen_US
dc.typeThesisen_US
dc.type.materialen_USen_US


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