How's business? Manufacturing small, medium and micro enterprises (SMMEs') contributions to the formal sector employment in Gauteng and the Western Cape between 2007 AND 2013

Malepe, Naume (2014-12)

Thesis (MPhil)--Stellenbosch University, 2014.

Thesis

ENGLISH ABSTRACT: Job creation through support to Small, Medium and Micro Enterprises (SMMEs) is one of the government’s priorities in the National Development Plan 2030 (NDP 2030) to overcome the chronic unemployment situation faced by millions of South Africans. According to Gibrat’s Law businesses have the same potential for growth regardless of their initial size. Jovanovic’s Passive Learning Model extends Gibrat’s Law by including age into the calculation – businesses learn through experience which determines if it will survive or not. This article uses the panel data from 2007 to 2013 from the Quarterly Employment Statistics (QES) from Statistics South Africa (Stats SA) to calculate Ordinary Least Squares regression models to test Gibrat’s Law and Jovanovic’s Passive Learning Model to determine if formal manufacturing SMMEs in Gauteng and the Western Cape experience more business growth in terms of employment and turnover than larger formal manufacturing businesses. Results indicate that Gibrat’s Law and Jovanovic’s Passive Learning Model were both rejected with regards to employment, indicating that Small, medium, micro enterprises (SMMEs) grow faster than larger businesses. Conversely, both models were accepted in terms of turnover; the experiences gained by businesses operating in the market over the years allow larger businesses to grow at a faster rate than SMMEs. These results support the NDP 2030 policy that more jobs can be created once government finds innovative ways to support manufacturing SMMEs.

AFRIKAANS OPSOMMING: Werkskepping deur ondersteuning aan klein, medium en mikro ondernemings (KMMOs) is een van die regering se prioriteite in die Nasionale Ontwikkelingsplan (NOP) om die kroniese werkloosheidsituasie wat deur miljoene Suid-Afrikaners ervaar word te oorkom. Volgens Gibrat se Wet het besighede dieselfde potensiaal vir groei ongeag hul aanvanklike grootte. Jovanovic se Passiewe Leer Model verleng Gibrat se Wet deur ouderdom in die bereken in te sluit – besighede leer deur ervaring, wat bepaal of dit sal oorleef of nie. Hierdie artikel gebruik paneel data vanaf 2007 tot 2013 vanaf die Kwartaallikse Indiensneming Statistieke van Statistiek Suid-Afrika om gewone kleinstekwadrate regressie modelle te bereken om Gibrat se Wet en Jovanovic se Passiewe Leer Model te toets om te bepaal of formele vervaardigings KMMOs in Gauteng en die Wes-Kaap meer besigheidsgroei in terme van indiensneming en omset toon as groter formele vervaardigingsbesighede. Resultate toon dat Gibrat se Wet en Jovanovic se Passiewe Leer Model word altwee in terme van indiensneming verwerp, wat aandui dat KMMOs vinnger as groter besighede groei. In teenstelling, beide modelle word in terme van omset aanvaar; die ervaring wat deur besighede opgedoen word deur oor ‘n paar jaar in die mark te werk, laat groter besighede toe om teen ‘n vinniger koers as KMMOs. te groei. Hierdie resultate ondersteun die NOP beleid dat meer werksgeleenthede geskep kan word sodra die regering innoverende maniere kan kry om vervaardigings KMMOs te ondersteun.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/95730
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