<p>This study aims to measure regional economic resilience at the neighborhood commercial district level, focusing on sales dynamics and recovery patterns during the COVID-19 pandemic. Using quarterly sales data from 825 neighborhood commercial districts in Seoul, we categorized commercial districts based on sales recovery patterns before and after the shock. Employing the panel vector autoregression model, we dynamically assess the short- and long-term effects of key factors on resilience. Unlike prior studies that emphasized static or unidirectional analysis, our approach integrates Granger causality and impulse response functions to uncover lag effects and dynamic interactions among influential factors. The results reveal that resilient districts benefit from diverse industries and robust purchasing power, whereas stagnated districts face limited market size and weak adaptability. Counterintuitively, increases in income negatively impacted sales for recovered areas in the short term. The changes in sales in growing areas did not respond significantly to either demand- and supply-side shocks, whereas in recovered areas, significant sales responses were observed to supply-side changes, particularly in the number of stores and the franchise store ratio. By systematically examining the structural dynamics and variance of resilience factors, this study provides actionable insights for designing sustainable policies to enhance economic resilience at the micro level against future shocks.</p>