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The polarisation of remote work

Abstract:
The Covid-19 pandemic has led to the rise of remote work with consequences for the global division of work. Remote work could connect labour markets, but it could also increase spatial polarisation. However, our understanding of the geographies of remote work is limited. Specifically, does remote work bring jobs to rural areas or is it concentrating in large cities, and how do skill requirements affect competition for jobs and wages? We use data from a fully remote labour market - an online labour platform - to show that remote work is polarised along three dimensions. First, countries are globally divided: North American, European, and South Asian remote workers attract most jobs, while many Global South countries participate only marginally. Secondly, remote jobs are pulled to urban regions; rural areas fall behind. Thirdly, remote work is polarised along the skill axis: workers with in-demand skills attract profitable jobs, while others face intense competition and obtain low wages. The findings suggest that remote work is shaped by agglomerative forces, which are deepening the gap between urban and rural areas. To make remote work an effective tool for rural development, it needs to be embedded in local skill-building and labour market programmes.
Publication status:
Published
Peer review status:
Not peer reviewed

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Publisher copy:
10.21203/rs.3.rs-855246/v1

Authors


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Institution:
University of Oxford
Division:
SSD
Department:
Said Business School
Research group:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0002-7671-1920
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author


More from this funder
Funder identifier:
https://ror.org/0472cxd90
Grant:
335716
639652


Publisher:
Research Square Company
Host title:
Research Square
Publication date:
2021-09-01
DOI:
EISSN:
2693-5015


Language:
English
Keywords:
Pubs id:
1196787
Local pid:
pubs:1196787
Deposit date:
2024-09-05

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