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Household and Contextual Indicators of Poverty in the Gauteng Province of South Africa: a Multilevel Analysis

100%
Molepo N., Molepo N. S.
Journal of Agribusiness and Rural Development
|
2022
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vol. 66
|
issue 4
341-354
EN
This study aims to analyse the socio-economic factors contributing to poverty reduction in South Africa using time series data from 2006 to 2019. The stationarity of the variables will be assessed by applying the Augmented Dickey Fuller (ADF) test. The Autoregressive Distributed Lag (ARDL) analytical technique will be adopted to analyse the cointegration amongst variables pertaining to different orders of cointegration amongst lower bound [I(0)] and upper bound [I(1)]. The study will analyse the long-term and short-term effects of the socio-economic factors contributing to poverty reduction in South Africa. If the calculated F-statistic is greater than the upper bound [I(1)], the Error Correction Model will be adopted to assess the short-run effects. Diagnostic tests will be performed to test the robustness of the model. The tests will performed will include: (1) the Breusch-Godfrey test for serial correlation; (2) the Jarque-Bera test for normality; (3) the Breusch-Pagan-Godfrey technique to test for heteroscedasticity; and (4) the cumulative sum chart to detect deviation from the average associated with a subgroup.
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Impact of international trade on employment in orange industry of South Africa

81%
Molepo N. S., Belete A., Hlongwane J.
Journal of Agribusiness and Rural Development
|
2021
|
vol. 60
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issue 2
193-201
EN
The purpose of the study is to analyse the long-run and short-run dynamic relations amongst total employment (lnEMPGt), export output (EXPOt) and import output (IMPOt) from 1990 to 2018, by applying a time-series analysis. The study adopts the secondary data for total employment from the Citrus Growers Association of South Africa, while both export and import output were sourced from the Global Trade Atlas. The multivariate cointegration approach is adopted in the study to identify any causal relationships amongst the concerned variables. The chosen optimum lag selection criterion was the Akaike Information Criterion (AIC) due to its association dependence on the log-likelihood ratio. The third lag was selected for the entire analysis. The results from the cointegration test and the Vector Error Correction Model (VECM) suggest a positive long-run effect between total employment and export output, while import output is negatively associated with total employment. The adjustment term of lnEMPGt, EXPOt and IMPOt suggests that the previous year’s errors are corrected for the current year at a convergence speed of 0.002, 1.11 and 25.37 percentage points, respectively. The results of the Granger causality test show that there are bidirectional causality effects between export output and total employment in the long run, while there are no causality effects between import output and total employment. The overall conclusion is that export outputs positively impact employment, while import outputs impact it negatively in the South African orange industry.
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