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.
The diffusion of COVID-19 across Italian provinces: a spatial dynamic panel data approach with common factors
Lisa Gianmoena
Co-primo
;Vicente Rios
Co-primo
2023-01-01
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.| File | Dimensione | Formato | |
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19. RS The diffusion of COVID 19 across Italian provinces a spatial dynamic panel data approach with common factors.pdf
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