bulelamasondo0-del/youth-unemployment-sa-analysis

Econometric analysis of youth unemployment in South Africa using regression models and macroeconomic data # youth-unemployment-sa-analysis Econometric analysis of youth unemployment in South Africa using regression models and macroeconomic data The regression results indicate that GDP growth is negatively associated with unemployment, suggesting that higher economic growth reduces joblessness. Education also shows a negative relationship with unemployment, highlighting the importance of human capital in improving labour market outcomes. Inflation displays a weaker and less consistent relationship. Overall, the model provides useful insights into the macroeconomic drivers of unemployment in South Africa. ## 📈 Time-Series Forecasting (ARIMA) An ARIMA model was applied to forecast unemployment trends using historical data. The model captures temporal patterns and dependencies in the data. The results suggest that unemployment is persistent over time, with forecasts indicating continued high levels in the near future. This highlights structural challenges in the South African labour market.