EconPapers    
Economics at your fingertips  
 

Unemployment Disrupts Sleep

David Blanchflower () and Alex Bryson ()

No 20-13, DoQSS Working Papers from Quantitative Social Science - UCL Social Research Institute, University College London

Abstract: Although there is a substantial literature indicating that unemployment and joblessness have profound adverse impacts on individuals’ health and wellbeing, there is relatively little evidence of their impact on sleep. Using data for over 3.5 million individuals in the United States over the period 2006-2019 from the Behavioral Risk Factor Surveillance System (BRFSS) survey series we show sleep disruption patterns that vary by labor market status. We look at sleep measured by hours in a day and days in a month and whether sleep is disturbed over a fortnight, as indicated by problems falling or staying asleep or staying asleep too much. We find the short-term unemployed suffer more short and long sleep than the employed and are more likely to suffer from disturbed sleep. These problems are greater still for the long-term unemployed and for the jobless who say they are unable to work.

Keywords: sleep; short sleep; long sleep, disturbed sleep; unemployment; unable to work; joblessness; COVID-19 (search for similar items in EconPapers)
JEL-codes: I31 J64 (search for similar items in EconPapers)
Date: 2020-09-01
New Economics Papers: this item is included in nep-hap and nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://repec.ioe.ac.uk/REPEc/pdf/qsswp2013.pdf (application/pdf)

Related works:
Working Paper: Unemployment Disrupts Sleep (2020) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:qss:dqsswp:2013

Access Statistics for this paper

More papers in DoQSS Working Papers from Quantitative Social Science - UCL Social Research Institute, University College London Quantitative Social Science, Social Research Institute, 55-59 Gordon Square, London WC1H 0NU. Contact information at EDIRC.
Bibliographic data for series maintained by Dr Neus Bover Fonts ().

 
Page updated 2021-10-21
Handle: RePEc:qss:dqsswp:2013