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.

Local inequalities of the COVID-19 crisis / Cerqua, A.; Letta, M.. - In: REGIONAL SCIENCE AND URBAN ECONOMICS. - ISSN 0166-0462. - 92:(2022), p. 103752. [10.1016/j.regsciurbeco.2021.103752]

Local inequalities of the COVID-19 crisis

Cerqua A.
;
Letta M.
2022

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.
2022
Counterfactual approach; COVID-19; Impact evaluation; Italy; Local labor markets; Machine learning
01 Pubblicazione su rivista::01a Articolo in rivista
Local inequalities of the COVID-19 crisis / Cerqua, A.; Letta, M.. - In: REGIONAL SCIENCE AND URBAN ECONOMICS. - ISSN 0166-0462. - 92:(2022), p. 103752. [10.1016/j.regsciurbeco.2021.103752]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1610455
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