Analysis of Factors Influencing Not in Employment, Education, or Training (NEET) Among Youth in Indonesia from 2019 to 2023 Using Panel Data Regression
Keywords:
NEET, Data Panel Regression, EconomicAbstract
The phenomenon of youth categorized as ‘Not in Employment, Education, or Training (NEET)’ poses a significant challenge for Indonesia’s economic and social development, particularly during the demographic bonus era. This study aims to analyze the factors influencing the percentage of NEET youth aged 15-24 in Indonesia during the 2021-2023 period. Using panel data regression analysis, the study examines data from 34 provinces, with independent variables including the ‘Open Unemployment Rate (TPT), Labor Force Participation Rate (TPAK), Net Enrollment Rate (APM)’, proportion of informal employment, proportion of young women married at an early age, the ‘Human Development Index (HDI), and GRDP’. The best model for panel data regression in this study is the fixed effects model. The results show that the independent variables TPT, TPAK, APM, HDI, and the proportion of informal employment significantly influence the NEET percentage, with an R-squared value of 97.7% and an adjusted R-squared value of 96.2%. This indicates that the significant independent variables in the model explain 96.2% of the NEET percentage, while the remaining 3.8% is explained by other variables outside the independent variables in this study. In conclusion, this study underscores the importance of addressing the identified factors to reduce NEET prevalence. The findings provide valuable insights for policymakers and stakeholders to design targeted strategies for sustainable human resource development, improve access to education, and create better employment opportunities for Indonesian youth.