Resilience, tail-risk and connectedness mechanism: An inter-industry perspective

While existing research has extensively examined inter-industry risk spillovers, it has largely neglected resilience connectedness across industries, overlooking a critical dimension of systemic stability. This paper uses the Time-Varying Parameter Vector Autoregression (TVP-VAR) model to quantify industry-level resilience in China by assessing responses to multiple shocks, then constructs resilience networks using the DY spillover index and tail-risk networks through the LASSO-quantile regression to compare their transmission structure, and finally employs the Quadratic Assignment Procedure (QAP) model and input–output linkages to analyze the spatial driving factors of these two interconnectedness mechanisms. The results indicate heterogeneity in industry resilience across shock origins. Static analyses reveal that resilience networks center on real-economy industries, whereas tail-risk network centers on finance industries. Dynamic results show that total resilience connectedness leads tail-risk connectedness, suggesting its utility as a forward-looking early warning indicator. The QAP estimates indicate that resilience tends to propagate upstream along supply chains, while tail risk flows downstream. Overall, this study provides a dual perspective of inter-industry resilience and risk connectedness, offering new evidence for risk management and policy design in complex economic environments.