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. 2022 Mar 23;20(3):537–558. doi: 10.1007/s10888-021-09522-6

The heterogeneous effects of COVID-19 on labor market flows: evidence from administrative data

Alessandra Casarico 1,2,3,, Salvatore Lattanzio 4
PMCID: PMC8940582  PMID: 35342379

Abstract

We investigate the short-term effects of COVID-19 on labor market flows and how they are mediated by labor market policy. Using Italian administrative data on a sample of active contracts between 2009 and the second quarter of 2020, we show that, before the pandemic, a higher share of female compared to male, young compared to old and low educated compared to high educated workers is employed in non-essential activities. When we look at the change in hirings and separations, from the 9th week of 2020 - the time when first cases and deaths due to COVID-19 were recorded -, we find a pronounced drop in hirings and endings of fixed-term contracts. Layoffs and quits increase after the 9th week, and then decline significantly, reflecting the effects of government intervention. The lifting of the lockdown triggers a slow recovery of labor market flows. Young workers, those on temporary contracts, low-educated workers, those employed in the South and those with no opportunities of working from home experience a greater decline in separation probability, indicating that government policy partly protected them from the labor market impact of the recession. The decline in the separation probability for women is lower than that for men.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10888-021-09522-610.1007/s10888-021-09522-6.

Keywords: COVID-19, Hirings, Separations, Flows, Gender

Electronic supplementary material

Below is the link to the electronic supplementary material.

(PDF 91.2 KB) (91.2KB, pdf)

Acknowledgements

We would like to thank the associate editor, three anonymous referees, Bruno Anastasia, Giulia Bovini, Francesco D’Amuri, Domenico Depalo, Andrea Garnero and Christopher Rauh for useful comments and discussion. We are grateful to Gaetano Basso for providing data on the classification of occupations according to the opportunity of remote work. Salvatore Lattanzio gratefully acknowledges ESRC DTP Studentship (nr. ES/J500033/1) and Cambridge Commonwealth European and International Trust for financial support for PhD studies at the University of Cambridge. The views expressed in this article are those of the authors and are not the responsibility of the Bank of Italy or the Eurosystem.

Data Availability

The data we use are provided by the Ministry of Labor and Social Policy and can be accessed by sending a request through the modules provided at https://www.cliclavoro.gov.it/Barometro-Del-Lavoro/Pagine/Microdati-per-la-ricerca.aspx.

Declarations

Conflict of Interest

The authors declare no conflict of interest.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Alessandra Casarico, Email: alessandra.casarico@unibocconi.it.

Salvatore Lattanzio, Email: salvatore.lattanzio@bancaditalia.it.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

(PDF 91.2 KB) (91.2KB, pdf)

Data Availability Statement

The data we use are provided by the Ministry of Labor and Social Policy and can be accessed by sending a request through the modules provided at https://www.cliclavoro.gov.it/Barometro-Del-Lavoro/Pagine/Microdati-per-la-ricerca.aspx.


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