Improving the resilience of economies to crises is of societal and policy interest. In this article, we complement the regional economics literature on resistance and recovery facets of resilience by instead exploring signals for loss of resilience prior to crises. In particular, we adapt spatiotemporal indicators from the ecological literature to spatially disaggregated unemployment data to assess the resilience of the economy of France. Key questions are whether more information about the resilience of the system can be gained by considering the spatial dimension, and whether the indicators can be used as a detection method of impending economic crises. This approach reveals that a spatially disaggregated principal components analysis enables to capture of signals of critical slowing down and to assess which specific region or groups of regions dominate the unemployment dynamics, which represents critical information that is missed when using nonspatial early warning signals. We find that different regions dominate the signal before or after a crisis. This resembles response diversity as seen in ecosystems. The spatial early warning signal, Moran’s I, is found to increase prior to the moments of economic crises. These findings suggest that the spatial characteristics of a country’s unemployment are crucial to assess a country’s resilience.

Halleck Vega, S.M., Patuelli, R., Van Voorn, G., Weinans, E. (2025). Spatial Early Warning Signals to Assess Economic Resilience. ISCIENCE, 28(12), 1-9 [10.1016/j.isci.2025.114097].

Spatial Early Warning Signals to Assess Economic Resilience

Patuelli, Roberto;
2025

Abstract

Improving the resilience of economies to crises is of societal and policy interest. In this article, we complement the regional economics literature on resistance and recovery facets of resilience by instead exploring signals for loss of resilience prior to crises. In particular, we adapt spatiotemporal indicators from the ecological literature to spatially disaggregated unemployment data to assess the resilience of the economy of France. Key questions are whether more information about the resilience of the system can be gained by considering the spatial dimension, and whether the indicators can be used as a detection method of impending economic crises. This approach reveals that a spatially disaggregated principal components analysis enables to capture of signals of critical slowing down and to assess which specific region or groups of regions dominate the unemployment dynamics, which represents critical information that is missed when using nonspatial early warning signals. We find that different regions dominate the signal before or after a crisis. This resembles response diversity as seen in ecosystems. The spatial early warning signal, Moran’s I, is found to increase prior to the moments of economic crises. These findings suggest that the spatial characteristics of a country’s unemployment are crucial to assess a country’s resilience.
2025
Halleck Vega, S.M., Patuelli, R., Van Voorn, G., Weinans, E. (2025). Spatial Early Warning Signals to Assess Economic Resilience. ISCIENCE, 28(12), 1-9 [10.1016/j.isci.2025.114097].
Halleck Vega, Sol Maria; Patuelli, Roberto; Van Voorn, George; Weinans, Els
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1031534
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