Abstract This study models the behaviour of economic systems during pandemic events by extending Zellner’s Seemingly Unrelated Regressions (SUR) within a Generalised Method of Moments (GMM) framework. The proposed approach identifies systems of equations that remain stable when explaining one or more variables simultaneously. Applied to pandemic–economic dynamics across major economies (2020–2023), the results show interactions between epidemiological indicators (transmission, recovery, mortality) and macroeconomic variables (employment, trade, investment, inflation). The findings suggest that the pandemic negatively affected employment and trade, while higher recovery rates acted as stabilising forces, reducing inflationary pressures and supporting economic resilience. The framework captures how structural relationships evolve across risk phases including initial shock, early recovery and post-vaccination, identifying systemic vulnerabilities and resilience pathways during global disruptions.
Vilchis et al. (2026) studied this question.