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We employ a pooled OLS model with panel-corrected standard errors (PCSE) to address cross-sectional dependence, serial correlation, and heteroskedasticity, while a fixed-effects instrumental variable (FE-IV) model is used to resolve endogeneity from reverse causality. The analysis reveals that NPIs significantly reduced quarterly GDP growth, with coefficients ranging from -0.078 to 0.154 across models. Regional heterogeneity shows stronger negative effects in eastern (-0.092) provinces compared to western and central provinces. Temporal analysis further identifies an empirically observed three-stage targeted response: significant negative impacts in 2020 (-0.180), but an insignificant effect in 2021 and 2022, reflecting policy adjustments and economic adaptation. The findings underscore the trade-offs between public health measures and economic performance, with an estimated 0.096 percentage point economic loss due to NPIs, consistent with global studies.<\/jats:p>","DOI":"10.1186\/s12889-026-28461-3","type":"journal-article","created":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T13:55:58Z","timestamp":1783518958000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The impact of China\u2019s non-pharmaceutical interventions on economic growth during COVID-19: a provincial-level panel analysis"],"prefix":"10.1186","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-4301-2114","authenticated-orcid":false,"given":"Yisha","family":"Ma","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barjoyai Bin","family":"Bardai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,8]]},"reference":[{"issue":"4, SI","key":"28461_CR1","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1007\/s12571-020-01082-3","volume":"12","author":"S Akter","year":"2020","unstructured":"Akter S. 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