<![CDATA[Despite the recovery trend in the labor market after the scarring effects caused by the pandemic, the share of white-collar workers remains below pre-pandemic levels. This study aims to analyze the determinants of reemployment among individuals who exited the workforce due to COVID-19, with a specific focus on differences between white-collar and blue-collar workers. We use micro data from the August 2022 National Labor Force Survey (Sakernas) and employ a survival analysis with the Fine and Gray competing risks model to estimate the subdistribution hazard ration (SHR) for each covariate such as gender, living area, education, and age. The results show that individuals living in urban areas, with post-secondary education, younger age (15–30 years), previous white-collar work experience, and participation in training programs have a significantly higher likelihood of reemployment in white-collar occupations. Conversely, blue-collar reemployment is more likely among those with lower education, rural residence, head-of-household status, previous blue-collar work experience and unmarried individuals. This research emphasizes the importance of investing in human capital and post secondary education for maximizing white-collar jobs reabsorption.]]>
Copyrights © 2025
