The influence of scale in modeling social vulnerability and disaster assistance
Understanding how social vulnerability relates to disaster impacts is critical for addressing social equity, yet the role of spatial scale in this relationship is often overlooked. Most studies use aggregated data, risking ecological fallacy—misinterpreting individual outcomes from group-level data. This study examines how spatial scale influences the relationship between social vulnerability and federal disaster assistance after Hurricane Harvey. Using spatial econometric models at both household and census tract levels, we assessed the strength of key vulnerability indicators in explaining disaster assistance. Results show that disability, housing tenure, household size, and income predict assistance at the household level, but their influence shifts across scales. Income and disability remain strong predictors at the tract level, whereas housing factors weaken or reverse. These findings suggest that using aggregated data to model household-level relationships between social vulnerability and disaster assistance can distort understanding of vulnerability processes, potentially leading to misinformed disaster policies and inequitable outcomes. Our findings have implications for disaster management, but the primary contribution of this study is methodological, in providing a critical evaluation of how spatial scale and data aggregation shape the statistical interpretation of social vulnerability and aid distribution.