The Impact of Investment and Population Growth on Unemployment in Afghanistan (2002–2024)

This study empirically examines the impact of investment and population growth on unemployment in Afghanistan using time series data from 2002 to 2024. The research is quantitative and empirical in nature and applies standard econometric techniques. The Augmented Dickey Fuller (ADF) test is used to assess data stationarity, while the Engle Granger cointegration test and the ARDL Bounds Test are applied to identify long-run relationships. The ARDL model is used to analyze short-run dynamics. The results show that all variables become stationary after first differencing (I (1)); however, no long-run cointegration relationship is found among unemployment, investment, and population growth. Short-run ARDL results indicate that neither investment nor population growth has a statistically significant effect on unemployment. In contrast, the lagged value of unemployment is the strongest determinant of current unemployment, indicating the persistent nature of unemployment in Afghanistan. Diagnostic tests confirm that the model is free from serial correlation, heteroskedasticity, and specification errors. The study concludes that unemployment in Afghanistan is largely driven by structural and internal factors and that increases in investment or changes in population growth alone are insufficient to reduce unemployment. Therefore, sustainable sector-based and institutional reforms are necessary to effectively address unemployment.