Dynamic Structural Modelling of Systemic Interactions Under Crisis:   A Generalised Moment Framework with Application to Pandemic–Economic Dynamics

V. E. G. Vilchis; S. J. Antony; S. Munjal

doi:10.1007/s41885-026-00198-8

Dynamic Structural Modelling of Systemic Interactions Under Crisis: A Generalised Moment Framework with Application to Pandemic–Economic Dynamics

V. E. G. Vilchis
, S. J. Antony^*
, S. Munjal

^*Corresponding author for this work

University of Leeds

Research output: Contribution to journal › Article › peer-review

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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.

Original language	English
Article number	18
Number of pages	29
Journal	Economics of Disasters and Climate Change
Volume	10
Issue number	2
Early online date	12 May 2026
DOIs	https://doi.org/10.1007/s41885-026-00198-8
Publication status	E-pub ahead of print - 12 May 2026

Bibliographical note

© The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

Data Access Statement

Data will be made available upon reasonable request.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Systemic risk interactions
Seemingly Unrelated Regressions (SUR)
Pandemic–economic dynamics
Generalised Method of Moments (GMM)
Dynamic structural modelling
Crisis resilience analysis

Access to Document

10.1007/s41885-026-00198-8Licence: CC BY 4.0

Dynamic Structural Modelling of Systemic Interactions Under Crisis: A Generalised Moment Framework with Application to Pandemic–Economic Dynamics
© The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
Final published version, 1.87 MBLicence: CC BY 4.0

Cite this

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title = "Dynamic Structural Modelling of Systemic Interactions Under Crisis: A Generalised Moment Framework with Application to Pandemic–Economic Dynamics",

abstract = "This study models the behaviour of economic systems during pandemic events by extending Zellner{\textquoteright}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.",

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N2 - 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.

AB - 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.

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