Socio-Economic Determinants of Unemployment: A Mixed-Method Causal Analysis and Policy Implications

The aim of the research is to reveal the causal relationships of socio-economic variables affecting the unemployment rate both individually and holistically. It also aims to reveal country-specific results and future policy recommendations. For these purposes, it analyzes the factors affecting the unemployment rate with both symmetric (correlation analysis, structural equation modeling) and asymmetric (fsQCA) methods. In the analysis using data from international organizations such as OECD and ILO for 2023, the number of hours worked (HW), self-employment rate (SER), young female unemployment rate (UYF), human rights index (HRI), employment by education level (EEL) and labor income share (LIS) variables are examined. As a result of correlation analyses, strong and positive correlations were found between the IIP and UER, HRI and LIS, and SER and HW. Moreover, the relationships between HW and EEL, SER and EEL, and HRI and SER are found to be negative. According to the results of the structural model, p=0.030 and R2 value of the model is 0.761, which shows that the model is significant and has a high explanatory power. According to the FsQCA analysis, all variables were found to be individually sufficient for the unemployment rate, while the absence of the NIF was determined as a necessary variable. Configuration analysis reveals that unemployment dynamics differ across countries, and these differences suggest guidelines for policymakers for sustainable development.