Modelling the Differing Impacts of Covid‐19 in the UK Labour Market†
| Published date | 01 October 2022 |
| Author | Chris Martin,Magdalyn Okolo |
| Date | 01 October 2022 |
| DOI | http://doi.org/10.1111/obes.12497 |
OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 84, 5 (2022) 0305-9049
doi: 10.1111/obes.12497
Modelling the Differing Impacts of Covid-19 in the
UK Labour Market*
CHRIS MARTIN and MAGDALYN OKOLO
Department of Economics, University of Bath, Bath, BA2 7AY, UK (e-mail:
c.i.martin@bath.ac.uk)
Abstract
This article studies the impact of the Covid-19 pandemic on graduates and non-graduates
in the United Kingdom. We construct a DSGE model with search frictions that is designed
around key features of the UK labour market and simulate the model using an array
of shocks, designed to mimic the impact of the Covid-19 pandemic. We show that our
relatively simple macroeconomic model can describe the impact of the pandemic on
output, employment and wages. Our results show that the impact of the pandemic on
employment and wages was more severe for non-graduates than for graduates, and that
up to 5 million jobs would have been lost in the first wave of the pandemic in the absence
of the Job Retention Scheme.
I. Introduction
This article models the response of the labour markets for graduates and non-graduates
in the United Kingdom to the Covid-19 pandemic. The crisis has had a major impact.
At the peak of the pandemic, only around 50% of workers were at work; two-thirds of
employers made use of the Job Retention Scheme (JRS) and up to 10 million workers
were furloughed (Leslie, 2020). GDP fell by 20% in April 2020, and was 5% lower in
2020 compared with 2019. Across 2020, employment fell by 1%– 3% ONS (2021a).
We address three main questions. First, can this extreme turbulence be explained
using a relatively simple macroeconomic model? Second, how did the pandemic affect
the labour market experience of different types of workers in the United Kingdom and
what is the likely adjustment process as the economy recovers? And, third, what was the
impact of the JRS, adopted by the UK Government in March 2020 as the core of their
economic policy response to the pandemic?
We address these questions using a DSGE model with labour market frictions, which
we simulate using a series of shocks that are constructed to mimic the effects of the
pandemic. We adapt the models of Krause and Lubik (2007), Thomas and Zanetti (2009),
Blanchard and Gali (2010), Ravenna and Walsh (2011), Zanetti (2011)andMumtaz
JEL Classification numbers: E23, E32, J23, J30, J64.
*This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit
sectors. We thank Andreea Camilli, Carl Singleton and Bingsong Wang for helpful comments and suggestions.
994
©2022 Oxford University and John Wiley & Sons Ltd.
Modelling the Differing Impacts of Covid-19 in the UK Labour Market 995
and Zanetti (2015)1to allow for three key features of the UK labour market, which we
document below using data from the Labour Force Survey. First, the labour market
experience of graduates and non-graduates differs markedly; graduates typically have
higher wages and greater job security than non-graduates (ONS, 2017a). Second, many
graduates are employed in ‘non-graduate’ occupations (see also ONS, 2017a). And third,
there is substantial movement of workers between jobs, with most hires coming from the
employed rather than the unemployed (see also ONS, 2017b). These features imply that
non-graduates are especially vulnerable to severe shocks such as the Covid-19 pandemic,
and highlight the complexities of the UK labour market that our analysis needs to take
account of.
Reflecting these features, our model distinguishes between graduates and non-graduates
and between ‘high productivity’ and ‘low productivity’ occupations. Both graduates
and non-graduates can be employed in both types of occupation, but with differing
productivities2. As we document below, the UK labour market is characterized by
complex flows of workers between high productivity and low productivity occupations
and between these and non-employment. We generate worker flows to match these data
through job search by employed and non-employed workers, and job destruction.
We model the impact of Covid-19 on the UK labour market as a series of simultaneous
adverse shocks. Baqaee and Farhi (2020) and Maria del Rio-Chanona et al. (2020)usea
similar approach for the United States. Related work includes Fornaro and Wolf (2020)and
Guerrieri, Lorenzoni and Straub (2020), who conceptualize the transmission of adverse
supply shocks into adverse demand shocks. Other models (e.g. Eichenbaum, Rebelo and
Trabandt, 2020; Mihailov, 2020) incorporate simple Susceptible-Infectious-Recovered
epidemiological processes into DSGE models. Our simulations of the impact of the
pandemic are mainly driven by adverse shocks to aggregate demand and supply, where
the latter reflects the impact of workers who are furloughed through the JRS or working
from home, as well as social distancing. Reflecting the JRS, we model wage shocks that
reduce the cost of labour to firms. We also model shocks to job destruction. Productivity
and wage shocks are specific to the job and not the worker and so are the same for
graduates and non-graduates in the same occupation.
In our baseline scenario, we show that our simple model can match the experience of the
UK economy during the pandemic. We focus on three key features of the UK experience:
(i) there were deep reductions in output, but relatively little change to employment; (ii)
most of the reduction in employment came from non-graduates; and (iii) aggregate real
wages increased in the first half of 2021. We are able to match the behaviour of GDP
throughout 2020– 21. There is some uncertainty about changes in employment during
the pandemic; data from the Labour Force Survey suggest a fall of 1%– 2%, while the
Workforce Jobs Survey suggests a larger fall, of around 3%. Our simulated values for
employment follow the values from the Workforce Job Survey across the pandemic.
Our simulations also match the disproportionate impact on non-graduate employment,
1Faccini, Millard and Zanetti (2013) is a prominent earlier application of this approach to the UK labour market.
2Our model has similarities with the literature on ‘good and bad jobs’ (e.g. Gertler, Huckfeldt and Trigari, 2020;
and Faccini and Melosi, 2020). In these models, the productivity of a job match is random; in our model, it reflects
the characteristics of workers and jobs.
©2022 Oxford University and John Wiley & Sons Ltd.
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