Conceptualizing and measuring "industry resilience": Composite indicators for postshock industrial policy decision-making. (February 2023)

• Record Type: Journal Article
• Authors: Di Tommaso, Marco R.; Prodi, Elena; Pollio, Chiara; Barbieri, Elisa
• Is Part Of: Socio-economic planning sciences. Number 85(2023)
• Publication Date: 2023-02
• Subjects: Industry resilience -- Composite indicators -- CIs -- Industrial policies -- Employment; L52 -- O14 -- C43 -- L16; Planning -- Periodicals; Economic policy -- Periodicals; Social policy -- Periodicals; Planification -- Périodiques; Politique économique -- Périodiques; Politique sociale -- Périodiques; ECONOMIC PLANNING; SOCIAL PLANNING; DECISION-MAKING; 361
• DOI: 10.1016/j.seps.2022.101448
• Languages: English
• ISSNs: 0038-0121

Abstract

Abstract: Can resilience be a relevant concept for industrial policy? Resilience is usually described as the ability of a socioeconomic system to recover from unexpected shocks. While this concept has caught the attention of regional economics researchers seeking to understand the different patterns behind regional recovery after a disruption, it is increasingly recognized that resilience can have policy-relevant conceptual applications in many other regards. In this paper, we apply it to industries and define the "industry resilience" concept and measurements. Our contribution is twofold. Theoretically, we frame industry resilience as a useful conceptual framework for policy-making to support the selection of industrial policy targets that are more capable of recovering after unexpected shocks. In addition, industry resilience can mitigate government failures by supporting decision-makers in promoting both economically and socially sustainable structural change. Methodologically, building on post-2008 U.S. data, we develop two composite indicators (CIs) to separately analyze quantitative and qualitative postshock variations in sectoral employment. Such CIs support policy-makers in visualizing sectoral performances dynamically and multidimensionally and can be used to compare each sector both to other sectors and to its counterfactual. Our results highlight that sectors react heterogeneously to shocks. This points to the relevance of tailoring vertical industrial policies according to sector features and the aims of industrial policy initiatives. Highlights: The study defines industry resilience and develops an approach to measure it. Industry resilience is particularly relevant for sustainable structural change. We develop composite indicators measuring changes in jobs quantity and quality. We look at the behavior of selected variables across a whole crisis-recovery period. Industry resilience can work as a support for industrial policy decisions.