Access the full text.
Sign up today, get DeepDyve free for 14 days.
The COVID-19 pandemic caused job losses to rise dramatically. Herein, the purpose of the article is to identify which personal and job characteristics make individuals more vulnerable or more resilient to COVID-19 unemployment in Portugal and thus to help policymakers, organizations and individuals themselves, in creating mechanisms to avoid unemployment within this new context.Design/methodology/approachUsing extensive personal and job-related data on the complete population of newly unemployed in Portugal over several months after the emergence of the COVID-19 pandemic, a logit model is estimated to identify the characteristics that make workers more resilient or more vulnerable to COVID-19 unemployment, in comparison with the pre-crisis period.FindingsThe COVID-19 crisis is shown to be disruptive by changing the unemployment structure, increasing socioeconomic inequalities and weakening traditional mechanisms of employment protection. Additionally, the authors identify a higher vulnerability of low-skilled individuals and of those in occupations with low working-from-home feasibility and/or from non-essential sectors (particularly tourism).Practical implicationsPolicy indications are given aiming to protect the most vulnerable individuals, sectors and regions in Portugal, in this new and unprecedented context.Originality/valueA seven-month period following the emergence of the pandemic is considered, which allows investigating both the immediate and the medium-term effects of the COVID-19 crisis on job losses. Additionally, by matching data from three different sources, an extensive set of multilevel variables is considered, some of them new in the literature.
International Journal of Manpower – Emerald Publishing
Published: Aug 10, 2022
Keywords: COVID-19; Unemployment; Job-specific characteristics; Human capital; Working-from-home; Tourism
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.