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Local inequalities of the COVID-19 crisis

Augusto Cerqua () and Marco Letta

Regional Science and Urban Economics, 2022, vol. 92, issue C

Abstract: This paper assesses the pandemic's impact on Italian local economies with the newly developed machine learning control method for counterfactual building. Our results document that the economic effects of the COVID-19 shock vary dramatically across the Italian territory and are spatially uncorrelated with the epidemiological pattern of the first wave. The largest employment losses occurred in areas characterized by high exposure to social aggregation risks and pre-existing labor market fragilities. Lastly, we show that the hotspots of the COVID-19 crisis do not overlap with those of the Great Recession. These findings call for a place-based policy response to address the uneven economic geography of the pandemic.

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)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:regeco:v:92:y:2022:i:c:s0166046221001125

DOI: 10.1016/j.regsciurbeco.2021.103752

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