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Local inequalities of the COVID-19 crisis

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  • Cerqua, Augusto
  • Letta, Marco

Abstract

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.

Suggested Citation

  • Cerqua, Augusto & Letta, Marco, 2021. "Local inequalities of the COVID-19 crisis," GLO Discussion Paper Series 875, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:875
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    3. Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2023. "Taste of home: Birth town bias in Geographical Indications," Economics & Statistics Discussion Papers esdp23089, University of Molise, Department of Economics.
    4. Mauro Caselli & Andrea Fracasso & Sergio Scicchitano, 2022. "From the lockdown to the new normal: individual mobility and local labor market characteristics following the COVID-19 pandemic in Italy," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(4), pages 1517-1550, October.
    5. Viviana Celli & Augusto Cerqua & Guido Pellegrini, 2023. "The long-term effects of mass layoffs: do local economies (ever) recover?," Journal of Economic Geography, Oxford University Press, vol. 23(5), pages 1121-1144.
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    7. Cerqua, Augusto & Ferrante, Chiara & Letta, Marco, 2023. "Electoral earthquake: Local shocks and authoritarian voting," European Economic Review, Elsevier, vol. 156(C).
    8. Lorena Skufi & Adam Geršl, 2023. "Using Macrofinancial Models to Simulate Macroeconomic Developments During the COVID-19 Pandemic: The Case of Albania," Eastern European Economics, Taylor & Francis Journals, vol. 61(5), pages 517-553, September.
    9. Batalha, Mafalda & Gonçalves, Duarte & Peralta, Susana & Pereira dos Santos, João, 2022. "The virus that devastated tourism: The impact of covid-19 on the housing market," Regional Science and Urban Economics, Elsevier, vol. 95(C).
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    More about this item

    Keywords

    impact evaluation; counterfactual approach; machine learning; local labor markets; COVID-19; Italy;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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