Local inequalities of the COVID-19 crisis
Augusto Cerqua () and
No 875, GLO Discussion Paper Series from Global Labor Organization (GLO)
This paper assesses the impact of the first wave of the pandemic on the local economies of one of the hardest-hit countries, Italy. We combine quarterly local labor market data with the new machine learning control method for counterfactual building. Our results document that the economic effects of the COVID-19 shock are dramatically unbalanced across the Italian territory and spatially uncorrelated with the epidemiological pattern of the first wave. The heterogeneity of employment losses is associated with exposure to social aggregation risks and pre-existing labor market fragilities. Finally, we quantify the protective role played by the labor market interventions implemented by the government and show that, while effective, they disproportionately benefitted the most developed Italian regions. Such diverging trajectories and unequal policy effects call for a place-based policy approach that promptly addresses the uneven economic geography of the current crisis.
Keywords: impact evaluation; counterfactual approach; machine learning; local labor markets; COVID-19; Italy (search for similar items in EconPapers)
JEL-codes: C53 D22 E24 R12 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-big, nep-cmp, nep-eur, nep-geo, nep-hea, nep-mac and nep-ure
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Journal Article: Local inequalities of the COVID-19 crisis (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:glodps:875
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