This study explores the evolving landscape of industrial policy in a post-shock global context, where fostering the resilience of strategic assets has become crucial for both advanced and emerging economies. Within this framework, the paper develops a novel integrated methodology to assist decision-makers in addressing the complexities of industrial policy design and implementation. Specifically, our approach accounts for multiple dimensions of resilience, enabling a nuanced understanding of territorial responses across different domains. We apply this methodology to examine the resilience of Chinese provinces across both industrial and social dimensions in the aftermath of the COVID-19 shock. Our results show that industrial and social resilience do not always align; rather, they can diverge significantly, even within the same regional clusters. These findings open new theoretical avenues for analyzing the interaction—and at times tension—between different resilience domains within a single territorial context. Furthermore, we find that the relationship between manufacturing specialization and resilience may not be straightforward. Among provinces with higher manufacturing specialization, resilience tends to manifest strongly in either the social or industrial dimension, depending on the specific characteristics of their manufacturing sectors. Additionally, we show that provinces with greater investment in social policies were generally better equipped to absorb shocks. Overall, our findings offer valuable insights for policymakers by providing a more nuanced understanding of resilience and highlighting where targeted interventions may be necessary across different domains to support more balanced and inclusive recovery trajectories.
Prodi, E., Pollio, C., Di Tommaso, M.R., Huang, M. (2026). Post-shock resilience and preference for manufacturing? A study on Chinese provinces. SOCIO-ECONOMIC PLANNING SCIENCES, 103, 1-19 [10.1016/j.seps.2025.102346].
Post-shock resilience and preference for manufacturing? A study on Chinese provinces
Marco R. Di Tommaso;
2026
Abstract
This study explores the evolving landscape of industrial policy in a post-shock global context, where fostering the resilience of strategic assets has become crucial for both advanced and emerging economies. Within this framework, the paper develops a novel integrated methodology to assist decision-makers in addressing the complexities of industrial policy design and implementation. Specifically, our approach accounts for multiple dimensions of resilience, enabling a nuanced understanding of territorial responses across different domains. We apply this methodology to examine the resilience of Chinese provinces across both industrial and social dimensions in the aftermath of the COVID-19 shock. Our results show that industrial and social resilience do not always align; rather, they can diverge significantly, even within the same regional clusters. These findings open new theoretical avenues for analyzing the interaction—and at times tension—between different resilience domains within a single territorial context. Furthermore, we find that the relationship between manufacturing specialization and resilience may not be straightforward. Among provinces with higher manufacturing specialization, resilience tends to manifest strongly in either the social or industrial dimension, depending on the specific characteristics of their manufacturing sectors. Additionally, we show that provinces with greater investment in social policies were generally better equipped to absorb shocks. Overall, our findings offer valuable insights for policymakers by providing a more nuanced understanding of resilience and highlighting where targeted interventions may be necessary across different domains to support more balanced and inclusive recovery trajectories.| File | Dimensione | Formato | |
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MANUSCRIPT_SEPS_REV1_01.07_w Authors docx corrected.pdf
embargo fino al 25/10/2026
Tipo:
Postprint / Author's Accepted Manuscript (AAM) - versione accettata per la pubblicazione dopo la peer-review
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Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale - Non opere derivate (CCBYNCND)
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1.17 MB
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Adobe PDF
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