Abstract

The COVID-19 global pandemic and the lockdown policies enacted to mitigate it have had profound effects on the labour market. Understanding these effects requires us to obtain and analyse data in as close to real time as possible, especially as rules change rapidly and local lockdowns are enacted. This work studies the UK labour market by analysing data from the online job board Reed.co.uk, using topic modelling and geo-inference methods to break down the data by sector and geography. I also study how the salary, contract type, and mode of work have changed since the COVID-19 crisis hit the UK in March. Overall, vacancies were down by 60 to 70% in the first weeks of lockdown. By the end of the year numbers had recovered somewhat, but the total job ad deficit is measured to be over 40%. Broken down by sector, vacancies for hospitality and graduate jobs are greatly reduced, while there were more care work and nursing vacancies during lockdown. Differences by geography are less significant than between sectors, though there is some indication that local lockdowns stall recovery and less badly hit areas may have experienced a smaller reduction in vacancies. There are also small but significant changes in the salary distribution and number of full time and permanent jobs. As well as the analysis, this work presents an open methodology that enables a rapid and detailed survey of the job market in unsettled conditions and describes a web application jobtrender.com that allows others to query this data set.

Highlights

  • The COVID-19 pandemic claimed over 90,000 lives in the UK as of the January, 2021 [1]

  • Studying the UK job market during the COVID-19 crisis with online job ads superseded by the The Health Protection (Coronavirus, Restrictions) (England) Regulations 2020 on March 26th [7]

  • Though the Reed website is searchable by topic and sector, the Javascript Object Notation (JSON) payload returned by Reed’s Application Programmer Interface (API) does not include a theme or topic marker and so this must be inferred

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Summary

Rudy ArthurID*

OPEN ACCESS Citation: Arthur R (2021) Studying the UK job market during the COVID-19 crisis with online job ads. The COVID-19 global pandemic and the lockdown policies enacted to mitigate it have had profound effects on the labour market. Understanding these effects requires us to obtain and analyse data in as close to real time as possible, especially as rules change rapidly and local lockdowns are enacted. This work studies the UK labour market by analysing data from the online job board Reed.co.uk, using topic modelling and geo-inference methods to break down the data by sector and geography. I study how the salary, contract type, and mode of work have changed since the COVID-19 crisis hit the UK in March.

Introduction
Data and methods
Topic modelling
Location inference
Jobs by sector
Jobs by location
Salary and contract type
Web interface
Findings
Discussion
Full Text
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