<![CDATA[Young and low-skilled workers are the most affected groups due to the labor market disruption caused by the pandemic. One of the impacts is the transition of young workers, especially workers with low skills, or called blue-collar workers. The transition could be a change from blue-collar young workers to those Not in Education, Employment, or Training (NEET). This study aims to examine the determinants of the transition of blue-collar young workers who become Unemployed NEET or Inactive NEET during the pandemic. In this study, data from the National Labor Force Survey (SAKERNAS) with individual panel observations, observed in two survey periods, namely August 2019 and August 2020, were analyzed using multinomial logistic regression. Demographic factors, human capital, and the risk status of COVID-19 in the area where young workers live are important issues in the transition of blue-collar young workers to NEET. Optimizing gender-based employment policies, implementing policies that suit the needs of young workers in rural or urban areas, as well as intensifying the use of the internet for work that can increase worker resilience, are some of the solutions to prevent the NEET transition from blue-collar young workers during the pandemic. Keywords: Blue-Collar Worker, Multinomial logistic regression, NEET, Sakernas, Young worker]]>
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