What are We Missing? Quantitative Analysis of Time-Related Underemployment

This research aims to analyse the variables that influence time-related underemployment in Türkiye. The sample was derived from the 2022 Household Labour Force Statistics microdataset from the Turkish Statistical Institute (TURKSTAT). First, descriptive statistics were used to analyse the distribution of time-related underemployment across the sub-sample groups. For the difference analysis, the Mann–Whitney U and Kruskal– Wallis-H tests were applied. Finally, binary logistic regression analysis was used to identify the determinants of time-related underemployment. All the independent variables, which were categorised as individual, social, and work-related, were found to result in statistically significant differences between the sub-sample groups. Furthermore, the findings indicate that gender, age, level of education, marital status, proximity, region of residence, Social Security Institution (SSI) registration, and workplace situation variables are significant predictors of time-related underemployment. In contrast, the analysis revealed that household size did not emerge as a significant predictor. When considered collectively, these independent variables account for 19.2% of the variance in time-related underemployment risk.