Analysing the macroeconomic determinants of NEET youth in Iran: A spatial panel data approach

Youth disengagement is persistently high in Iran due to economic sanctions, rapid demographic growth, and uneven regional development. Macroeconomic factors determine youth not in Employment, Education, or Training (NEET) status, but spatial spillovers, gender, and urban-rural heterogeneity are rarely considered. This study examines the association between NEET rates and provincial-level GDP per capita, unemployment, inflation, government spending, urbanization, the Gini coefficient, vocational training programs (VET), gross value added in agriculture and services, industrial diversity, and human capital indicators across Iran's 30 provinces. This study differentiates between male, female, urban, and rural youth. We estimate spatial autoregression (SAR) models. Diagnostic tests (Moran's I, Pesaran CD, unit root, and cointegration) confirm spatial autocorrelation, cross-sectional dependence, and stationarity. The results show that a 1% increase in GDP per capita reduces NEET rates by approximately 0.18%, with stronger effects for males. Human capital and government spending also yield significant negative elasticities, particularly in rural provinces. Contrary to expectations, moderate inflation exhibits a small negative NEET elasticity (approximate to-0.047), likely reflecting demand-pull labor opportunities. The SAR spatial lag (rho =-0.334, P < 0.05) reveals significant negative spillovers, where higher NEET in one province corresponds to lower NEET in its neighbors, suggesting labor market migration effects. To fully comprehend and overcome youth disengagement in Iran requires understanding spatial interdependencies and subgroup heterogeneities. NEET rates could be reduced by combining regionally tailored economic strategies, coordinated cross-provincial training initiatives, and targeted gender and rural-focused interventions.