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This study investigates the relationship between sectoral labour productivity and unemployment in South Africa by answering the question how has labour productivity across different sectors affected employment rates in South Africa? Both descriptive statistics and inferential statistics (Augmented Dickey–Fuller and Phillips-Perron tests and Autoregressive Distributed Lag Bound test and estimation techniques) were applied on obtained timeseries data for the period 1991-2022. The analysis surprisingly shows that none of the sectoral labour productivity variables contribute to unemployment reduction in the country. Plausible reasons for this finding include the adoption of automation and technological advancements in labour intensive, imbalance between rate of job loss in labour intensive sector and rate of job creation in the service sector during sectoral shifts and economic transition, and general lower purchasing due to unequal distribution of labour productivity gain and income inequality that could have boosted consumer demand, these measures can stimulate economic growth and job creation. Various recommendations are suggested to reduce unemployment in the light of these findings.

The Manufacturing sector of the Nigerian economy can perform better in job creation, particularly during the period of economic expansion, which did not happen in the last period of economic growth between 1981 and 2014. Consequently, it is important to understand the real relationship between growth and job creation in the sector during the period.  Therefore, this study investigated the employment intensity of gross value added growth in the sector during the period of growth, using Vector Error Correction Model (VECM) with a view to providing useful statistics to facilitate policies for the development of sectoral employment strategy during the next cycle of economic growth. Previous studies have either used descriptive statistics or less robust econometric models applied to aggregate data of shorter series and did not explore the inter-sectoral relationship effect. The estimated employment elasticity of gross value added in the sector was not significant at 95 per cent confidence level, and can, therefore, not be relied upon for pin-point policy. However, the inter-sectoral and inter-temporal relationships provided significant estimates, indicating that such relationships should be taken into account in designing and developing sectoral employment strategy for the manufacturing sector. There is future scope for the extension of research to cover periods of recession, as well, for example, post COVID-19.

This study explores the nexus between population growth and unemployment in South Africa from 2000 to 2023, a period marked by significant demographic changes and economic challenges. South Africa has experienced rising unemployment alongside rapid population growth, which has led to concerns about the country’s ability to absorb its expanding labour force. The aim of this research is to examine how population growth influences unemployment, considering additional factors like foreign direct investment (FDI), gross domestic product (GDP), and inflation. Using time series data from the World Bank, Statistics South Africa, and the South African Reserve Bank, the study employs the Augmented Dickey-Fuller unit root test for stationarity, Johansen cointegration for long-term relationships, and Ordinary Least Squares (OLS) regression to estimate the impact of population growth on unemployment. Key findings indicate that population growth has a positive and statistically significant relationship with unemployment, meaning higher population growth increases unemployment levels. Foreign direct investment also shows a positive effect on unemployment, while GDP and inflation exhibit negative but statistically insignificant relationships. Based on these findings, the study recommends strategic urban planning, family planning initiatives, and targeted policies to attract labour-intensive FDI. Additionally, the government should focus on economic diversification, supporting SMEs, and investing in skill development to create sustainable jobs. This research contributes to understanding the dynamics between population growth and unemployment in South Africa and offers insights for more effective policy interventions.

South Africa has faced consistently elevated unemployment levels despite numerous macroeconomic reforms, prompting worries regarding the effectiveness of key economic indicators in promoting labour absorption. This study analyses the influence of economic growth (GDP), inflation (CPI), and foreign direct investment (FDI) on unemployment in South Africa, employing quarterly data from the first quarter of 2010 to the fourth quarter of 2023. The analysis utilises a quantitative design, implementing the Augmented Dickey-Fuller unit root test, the Johansen cointegration method, and a Vector Error Correction Model to evaluate the long- and short-term dynamics among the variables. The findings indicate that all variables are integrated of order one and possess a long-term equilibrium connection. Long-term estimates demonstrate substantial negative correlations, suggesting that increased GDP, CPI, and FDI are associated with a decrease in unemployment over time. In the near term, GDP elevates unemployment, indicating the prevalence of capital-intensive growth, whereas FDI persistently reduces unemployment and CPI remains negligible. These findings underscore the structural characteristics of unemployment in South Africa and the constraints of macroeconomic factors in facilitating short-term labour absorption. The report emphasises the significance of policies that promote labour-absorbing growth, improve the investment environment, and prioritise skills development to tackle ongoing unemployment.The report advocates for prioritising labour-intensive growth methods, enhancing the investment environment, and fortifying skills development systems to improve employment outcomes. These initiatives are essential for tackling persistent unemployment and fostering inclusive and sustainable economic growth.

This study examines the correlation between unemployment and economic growth in South Africa through a disaggregated analysis focused on educational attainment. Grounded in the Solow growth model and human capital theory, the research utilises annual time-series data from 1994 to 2022, obtained from the World Bank Indicators. Economic growth is represented by GDP growth, labour is indicated by unemployment rates categorised by advanced, intermediate, and basic education levels, and capital is measured by gross fixed capital creation. The Autoregressive Distributed Lag (ARDL) framework is utilised after conducting unit root and bounds tests, which validate the existence of long-run cointegration. The findings reveal a negative and statistically significant long-term association between economic growth and unemployment for those with basic and intermediate education, but unemployment among those with advanced education shows a negative but minor influence. Investment consistently demonstrates a favourable and substantial effect on growth. The findings emphasise structural unemployment and skills mismatches, highlighting the necessity for enhanced alignment between educational systems and labour market requirements to foster inclusive and sustainable economic growth in South Africa.

South Africa has faced consistently elevated unemployment levels despite numerous macroeconomic reforms, prompting worries regarding the effectiveness of key economic indicators in promoting labour absorption. This study analyses the influence of economic growth (GDP), inflation (CPI), and foreign direct investment (FDI) on unemployment in South Africa, employing quarterly data from the first quarter of 2010 to the fourth quarter of 2023. The analysis utilises a quantitative design, implementing the Augmented Dickey-Fuller unit root test, the Johansen cointegration method, and a Vector Error Correction Model to evaluate the long- and short-term dynamics among the variables. The findings indicate that all variables are integrated of order one and possess a long-term equilibrium connection. Long-term estimates demonstrate substantial negative correlations, suggesting that increased GDP, CPI, and FDI are associated with a decrease in unemployment over time. In the near term, GDP elevates unemployment, indicating the prevalence of capital-intensive growth, whereas FDI persistently reduces unemployment and CPI remains negligible. These findings underscore the structural characteristics of unemployment in South Africa and the constraints of macroeconomic factors in facilitating short-term labour absorption. The report emphasises the significance of policies that promote labour-absorbing growth, improve the investment environment, and prioritise skills development to tackle ongoing unemployment.The report advocates for prioritising labour-intensive growth methods, enhancing the investment environment, and fortifying skills development systems to improve employment outcomes. These initiatives are essential for tackling persistent unemployment and fostering inclusive and sustainable economic growth.

This study examines the correlation between unemployment and economic growth in South Africa through a disaggregated analysis focused on educational attainment. Grounded in the Solow growth model and human capital theory, the research utilises annual time-series data from 1994 to 2022, obtained from the World Bank Indicators. Economic growth is represented by GDP growth, labour is indicated by unemployment rates categorised by advanced, intermediate, and basic education levels, and capital is measured by gross fixed capital creation. The Autoregressive Distributed Lag (ARDL) framework is utilised after conducting unit root and bounds tests, which validate the existence of long-run cointegration. The findings reveal a negative and statistically significant long-term association between economic growth and unemployment for those with basic and intermediate education, but unemployment among those with advanced education shows a negative but minor influence. Investment consistently demonstrates a favourable and substantial effect on growth. The findings emphasise structural unemployment and skills mismatches, highlighting the necessity for enhanced alignment between educational systems and labour market requirements to foster inclusive and sustainable economic growth in South Africa.

This study explores the nexus between population growth and unemployment in South Africa from 2000 to 2023, a period marked by significant demographic changes and economic challenges. South Africa has experienced rising unemployment alongside rapid population growth, which has led to concerns about the country’s ability to absorb its expanding labour force. The aim of this research is to examine how population growth influences unemployment, considering additional factors like foreign direct investment (FDI), gross domestic product (GDP), and inflation. Using time series data from the World Bank, Statistics South Africa, and the South African Reserve Bank, the study employs the Augmented Dickey-Fuller unit root test for stationarity, Johansen cointegration for long-term relationships, and Ordinary Least Squares (OLS) regression to estimate the impact of population growth on unemployment. Key findings indicate that population growth has a positive and statistically significant relationship with unemployment, meaning higher population growth increases unemployment levels. Foreign direct investment also shows a positive effect on unemployment, while GDP and inflation exhibit negative but statistically insignificant relationships. Based on these findings, the study recommends strategic urban planning, family planning initiatives, and targeted policies to attract labour-intensive FDI. Additionally, the government should focus on economic diversification, supporting SMEs, and investing in skill development to create sustainable jobs. This research contributes to understanding the dynamics between population growth and unemployment in South Africa and offers insights for more effective policy interventions.

This study investigates the relationship between sectoral labour productivity and unemployment in South Africa by answering the question how has labour productivity across different sectors affected employment rates in South Africa? Both descriptive statistics and inferential statistics (Augmented Dickey–Fuller and Phillips-Perron tests and Autoregressive Distributed Lag Bound test and estimation techniques) were applied on obtained timeseries data for the period 1991-2022. The analysis surprisingly shows that none of the sectoral labour productivity variables contribute to unemployment reduction in the country. Plausible reasons for this finding include the adoption of automation and technological advancements in labour intensive, imbalance between rate of job loss in labour intensive sector and rate of job creation in the service sector during sectoral shifts and economic transition, and general lower purchasing due to unequal distribution of labour productivity gain and income inequality that could have boosted consumer demand, these measures can stimulate economic growth and job creation. Various recommendations are suggested to reduce unemployment in the light of these findings.

The paper investigates the relationship between inflation and unemployment in the South African setting, encompassing a comprehensive analysis of historical, theoretical, and empirical evidence. Existing literature surveys demonstrate that several studies have been conducted in multiple countries to ascertain the correlation between inflation and unemployment. The review incorporated the postulations of many economic schools of thought as they are applied to South Africa. The Phillips Curve was examined in accordance with the research purpose. The process involves gathering secondary data from reputable sources such as Statistics South Africa, the South African Reserve Bank, and other reliable secondary sources to analyse this relationship. The findings are presented using linear regression, tables, and figures. The study utilised annual inflation and unemployment data in South Africa spanning from 2000 to 2022 to elucidate the correlation between inflation and unemployment. The study discovered that the link was nonlinear and did not exhibit any meaningful association or correlation.