Local economies amidst the COVID-19 crisis in Italy: a tale of diverging trajectories
Augusto Cerqua () and
MPRA Paper from University Library of Munich, Germany
Impact evaluations of the microeconomic effects of the COVID-19 upheavals are essential but nonetheless highly challenging. Data scarcity and identification issues due to the ubiquitous nature of the exogenous shock account for the current dearth of counterfactual studies. To fill this gap, we combine up-to-date quarterly local labor markets (LLMs) data, collected from the Business Register kept by the Italian Chamber of Commerce, with the machine learning control method for counterfactual building. This allows us to shed light on the pandemic impact on the local economic dynamics of one of the hardest-hit countries, Italy. We document that the shock has already caused a moderate drop in employment and firm exit and an abrupt decrease in firm entry at the country level. More importantly, these effects have been dramatically uneven across the Italian territory and spatially uncorrelated with the epidemiological pattern of the first wave. We then use the estimated individual treatment effects to investigate the main predictors of such unbalanced patterns, finding that the heterogeneity of impacts is primarily associated with interactions among the exposure of economic activities to high social aggregation risks and pre-existing labor market fragilities. These results call for immediate place- and sector-based policy responses.
Keywords: impact evaluation; counterfactual approach; machine learning; local labor markets; firms; 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-bec, nep-big, nep-cmp, nep-eur, nep-geo, nep-lma and nep-mac
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