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      COVID-19: a crisis of the female self-employed

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          Abstract

          We investigate how the economic consequences of the pandemic and the government-mandated measures to contain its spread affect the self-employed — particularly women — in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are about one-third more likely to experience income losses than their male counterparts. We do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, e.g., the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.

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          Most cited references31

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          Inequality in the impact of the coronavirus shock: Evidence from real time surveys

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            The Gender Wage Gap: Extent, Trends, and Explanations

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              How many jobs can be done at home? ☆

              Evaluating the economic impact of “social distancing” measures taken to arrest the spread of COVID-19 raises a fundamental question about the modern economy: how many jobs can be performed at home? We classify the feasibility of working at home for all occupations and merge this classification with occupational employment counts. We find that 37% of jobs in the United States can be performed entirely at home, with significant variation across cities and industries. These jobs typically pay more than jobs that cannot be done at home and account for 46% of all US wages. Applying our occupational classification to 85 other countries reveals that lower-income economies have a lower share of jobs that can be done at home.
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                Author and article information

                Contributors
                akritikos@diw.de
                Journal
                J Popul Econ
                J Popul Econ
                Journal of Population Economics
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0933-1433
                1432-1475
                11 June 2021
                11 June 2021
                : 1-47
                Affiliations
                [1 ]GRID grid.8465.f, ISNI 0000 0001 1931 3152, DIW Berlin, ; Mohrenstr. 58, 10117 Berlin, Germany
                [2 ]GRID grid.11348.3f, ISNI 0000 0001 0942 1117, University of Potsdam, ; Potsdam, Germany
                [3 ]GLO, Essen, Germany
                [4 ]GRID grid.14095.39, ISNI 0000 0000 9116 4836, Freie Universität Berlin, ; Berlin, Germany
                Author notes

                Responsible editor: Klaus F. Zimmermann

                Article
                849
                10.1007/s00148-021-00849-y
                8192686
                34131364
                5087547f-391a-4c64-be1e-d1629a1cae58
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 27 October 2020
                : 30 March 2021
                Funding
                Funded by: Deutsches Institut für Wirtschaftsforschung e.V. (DIW Berlin) (3436)
                Categories
                Original Paper

                self-employed,covid-19,income,gender,representative real-time survey data,decomposition methods,j16,l26,j31,j71,i18

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