Economic resilience, defined as the ability of regions to withstand shocks, adapt to uncertainty, and sustain economic recovery,has become a central topic in regional economics and development planning. This study examines the relationship between population density, measured as persons per square kilometer, and the economic resilience of Iran’s 31 provinces during 2010–2024.It also explores the potential indirect statistical roles of consumer demand and technological innovation.Annual provincial panel data are analyzed using a fixed-effects generalized least squares (GLS) model to control for unobserved spatial and temporal heterogeneity. Panel Granger causality tests and instrumental variable (IV) estimation are employed to reduce concerns regarding endogeneity and reverse causality. Results indicate a positive and statistically significant association between population density and economic resilience, suggesting that more densely populated provinces exhibit greater capacity to absorb shocks and maintain economic stability. Sobel tests further indicate statistically significant indirect relationships through consumer demand and technological innovation. Granger causality and IV estimates provide evidence that the observed association is unlikely to be primarily explained by reverse causality, although they should not be interpreted as definitive proof of causality. These findings suggest that population concentration may strengthen local markets, improve productivity,and facilitate knowledge diffusion. Overall,the study emphasizes the importance of balanced population density management alongside policies promoting innovation, domestic demand, human capital development,and institutional capacity. The findings offer useful evidence for regional development strategies and spatial planning while recognizing the limitations of causal inference in observational panel data and encouraging future research using stronger identification strategies and richer datasets.