Analysing the Occupational Skills Productivity of South Africa’s Non-Agricultural Jobs: An ARDL Approach
Abstract
This study showed that South Africa’s employment of different occupational groups or broad skills dubbed as highly either skilled, semi-skilled, and low- or unskilled labour, and explained variations in non-agricultural labor productivity in their respective capacities. The Autoregressive Distributed Lag Model (ARDL) was employed to gauge the long- and short-run cointegration between the regressand (non-agricultural labor productivity) and employment trends of broad skills for different occupational groups, i.e., clerks, crafts and trades, elementary, management, plant and machinery, professionals, sales and services, technicians and domestic workers, as explanatory or regressor series. The tests for variance decomposition and Granger causality were also estimated. Findings showed that different highly skilled occupations had different productivity effects. Evidence of positive short-run co-integration was established for highly skilled managers and technicians; however, in the long run, the results were non-significant for the technicians, whereas they were statistically significant but negative for managers. However, results for highly skilled professional occupations were statistically nonsignificant. Subsequently, semi-skilled craft and trade occupations and sales and services occupations exhibited statistically significant and positive long- and short-run cointegration with non-agricultural labor productivity. However, the results of semi-skilled occupations for clerks and plant operators were statistically non-significant. Lastly, positive long- and short-run co-integrating relationships were established for unskilled domestic work occupations and non-agricultural labor productivity, albeit negative but statistically significant co-integration was revealed between unskilled elementary occupations and the regressand.
Keywords: labour productivity, occupational groups, autoregressive distributed lag, skilled labour, unskilled labour.
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