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The quality of institutions is widely recognized as a key determinant of public sector performance across various levels of governance. This paper investigates how institutional quality shaped the resilience of Italian Labour Market Areas during the COVID-19 pandemic. To this end, we introduce a localized, non-parametric Interrupted Time Series (ITS) approach, using long-run mortality data (2004-2023), to construct a data-driven, local-level resilience index. This index captures deviations from counterfactual mortality trajectories, reflecting the ability of local areas to withstand and recover from the pandemic. We then assess the determinants of this resilience index, with a particular focus on institutional quality. Our findings show that higher institutional quality - particularly the quality of local politicians - emerges as the most significant factor driving differences in performance at the local level. Multiple robustness checks, including alternative model specifications and pre-pandemic forecast accuracy benchmarks, confirm the reliability of our results.
Fontana et al. (Mon,) studied this question.