Disasters impose socioeconomic consequences on communities that extend beyond immediate physical damage. Indirect economic impacts arise from disruptions to production, supply chains, and demand, and can propagate through interconnected systems and interregional trade ties. The propagation of initial disruptions amplifies total losses and creates uneven recovery outcomes across regions, economic sectors, and populations. The lack of systematic approaches to quantify these cascading consequences limits effective preparedness and recovery planning across interdependent systems. My research develops methodologies to quantify regional socioeconomic impacts following disasters, accounting for interdependencies across regions and systems. I first synthesize the existing literature on macroeconomic modeling approaches and their applications in disaster impact assessment. Building on these insights, I develop computational modeling frameworks that simulate regional post-disaster economic recovery, incorporating multi-regional interactions and physical–economic system dynamics. Moreover, I extend this framework to model business-level recovery processes and evaluate macroeconomic implications for household well-being risk. The models are applied to estimate indirect economic losses from the 2011 Tohoku earthquake in Japan and predict socioeconomic risks in California from earthquakes. Results show that indirect losses can exceed direct damages in major disasters, with regional heterogeneity and infrastructure- economic interdependencies exacerbating cascading effects. In addition, the household well-being metric reveals vulnerable populations with limited recovery capacity that are not captured by conventional asset-based risk measures. The identified vulnerabilities in the physical–economic interdependencies, business operations, and household recovery support more effective and equitable resilience planning across scales, from individual businesses to regional governance.