Spatial early warning signals to assess economic resilience

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.

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Journal
iScience
Published
2025-11-20
DOI
https://doi.org/10.1016/j.isci.2025.114097
Primary Topic
Regional resilience and development
Type
article
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article

Spatial early warning signals to assess economic resilience

Roberto Patuelli, Els Weinans, George van Voorn, Solmaria Halleck Vega
iScience
Regional resilience and development
article

Spatial early warning signals to assess economic resilience

Roberto Patuelli, Els Weinans, George van Voorn, Solmaria Halleck Vega
article en

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.

iScienceVol. 28(12)
Utrecht University (NL), Wageningen University & Research (NL), University of Bologna (IT)
Openalex Percentile: Top 57%
Regional resilience and development
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Spatial early warning signals to assess economic resilience — Roberto Patuelli, Els Weinans, et al. · iScience (2025) | TGRS Research Map | TGRS