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The Impact of Industrial Clusters’ Quality on the Production Resilience in the Global Crisis
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Purpose: This paper aims to verify the difference in production resilience between local clusters and regions without clusters before and after a major crisis. Furthermore, this paper aims to identify the clusters’ quality factors that impact clusters’ shock vulnerability and resilience. Methods: Utilizing open-source data from the US Cluster Mapping platform, this paper compares regions with industrial clusters to those without using the Differences-in-Differences (DID) estimator. It considers the regions with industrial clusters as a treatment group and others as the control group, comparing the period before and after the pandemic. Additionally, the paper examines which cluster factors make a difference in economic resilience during the crisis using Regression Discontinuity Design (RDD). Results: The study finds that regions with industrial clusters show higher production resilience compared to regions without clusters. Moreover, the number of establishments, annual payrolls, and employment can have a positive impact on resilience during the pandemic shock. Conclusion: Though clusters could be vulnerable during the global crisis, industrial clusters can contribute to regional economic development and production resilience in the long-term aspect. Thus, it is required to construct a high-quality local cluster and support it during the economic crisis in the long-term aspect.
Abstract
Purpose: This paper aims to verify the difference in production resilience between local clusters and regions without clusters before and after a major crisis. Furthermore, this paper aims to identify the clusters’ quality factors that impact clusters’ shock vulnerability and resilience. Methods: Utilizing open-source data from the US Cluster Mapping platform, this paper compares regions with industrial clusters to those without using the Differences-in-Differences (DID) estimator. It considers the regions with industrial clusters as a treatment group and others as the control group, comparing the period before and after the pandemic. Additionally, the paper examines which cluster factors make a difference in economic resilience during the crisis using Regression Discontinuity Design (RDD). Results: The study finds that regions with industrial clusters show higher production resilience compared to regions without clusters. Moreover, the number of establishments, annual payrolls, and employment can have a positive impact on resilience during the pandemic shock. Conclusion: Though clusters could be vulnerable during the global crisis, industrial clusters can contribute to regional economic development and production resilience in the long-term aspect. Thus, it is required to construct a high-quality local cluster and support it during the economic crisis in the long-term aspect.
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