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The diffusion of COVID-19 across Italian provinces: a spatial dynamic panel data approach with common factors

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  • Lisa Gianmoena
  • Vicente Rios

Abstract

This study adopts a spatial dynamic panel data model with common factors and a connectivity matrix based on cross-province population flows to help explain the spread of COVID-19 infections across Italian provinces during the period 2020–21. We find that an increase in the infections in a province has a positive and statistically significant effect on neighbours’ infections, which highlights the relevance of spatial spillover effects. This finding is robust to several robustness checks. Furthermore, we investigate cross-provincial transmission heterogeneity using a heterogeneous spatial dynamic panel, which provides novel insights into the diffusion patterns of the disease.

Suggested Citation

  • Lisa Gianmoena & Vicente Rios, 2024. "The diffusion of COVID-19 across Italian provinces: a spatial dynamic panel data approach with common factors," Regional Studies, Taylor & Francis Journals, vol. 58(2), pages 285-305, February.
    • Handle: RePEc:taf:regstd:v:58:y:2024:i:2:p:285-305
    DOI: 10.1080/00343404.2023.2171000
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    Cited by:

    1. Massimo Arnone & Angelo Leogrande & Carlo Drago & Alberto Costantiello, 2024. "Social Trust and Support Networks: A Regional Analysis of Italy," Working Papers hal-04698270, HAL.

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