Publications
Zhaolu Liu, Jonathan Clarke, Bertha Rohenkohl, Mauricio Barahona
A job usually involves the application of several complementary or synergistic skills to perform its required tasks. Such relationships are implicitly recognised by employers in the skills they demand when recruiting new employees. Here we construct a skills network based on their co-occurrence in a national level data set of 65 million job postings from the UK spanning 2016 to 2022. We then apply multiscale graph-based community detection to obtain data-driven skill clusters at different levels of resolution that reveal a modular structure across scales. Skill clusters display diverse levels of demand and occupy varying roles within the skills network: some have broad reach across the network (high closeness centrality) while others have higher levels of within-cluster containment, yet with high interconnection across clusters and no skill silos. The skill clusters also display varying levels of semantic similarity, highlighting the difference between co-occurrence in adverts and intrinsic thematic consistency. Clear geographic variation is evident in the demand for each skill cluster across the UK, broadly reflecting the industrial characteristics of each region, e.g., London appears as an outlier as an international hub for finance, education and business. Comparison of data from 2016 and 2022 reveals employers are demanding a broader range of skills over time, with more adverts featuring skills spanning different clusters. We also show that our data-driven clusters differ from expert-authored categorisations of skills, indicating that important relationships between skills are not captured by expert assessment alone.
The code used in this analysis as available here.
Hummd Ghouri, Bertha Rohenkohl, Jonathan M Clarke
This interactive dashoard enables users to examine the data compiled for the Disruption Index in more detail and apply the data to their own research.
Anna Thomas, Oliver Nash, Dr Bertha Rohenkohl, Dr Jonathan Clarke, Hummd Ghouri, Claddagh NicLochlainn, Dr Abigail Gilbert, Kester Brewin
This interactive report accompanies the Disruption Index and integrates other sources with this to elicit new insights and inform key policy areas, showcasing how the DI can be used in practice by policymakers at national and regional levels.
Bertha Rohenkohl, Jonathan M Clarke, Christopher Pissarides
In this report we present the results of the Disruption Index, which examines how technological transformation may already be affecting parts of England differently, and how ready these regions are to adopt further new technologies in the years to come.
Rui Costa, Zhaolu Liu, Christopher Pissarides, Bertha Rohenkohl
In this report, we use a comprehensive dataset of online job postings from Adzuna, which provides information on the type of positions advertised and the skills that they require. We find rapid emergence of new skills and the disappearance of other, old skills. Notably, most skills becoming obsolete and new ones emerging to take their place, are related to IT. We quantify the magnitude and pace of skill change and find that it varies considerably across occupations. Occupations like IT directors, production engineers and cybersecurity professionals have experienced a high turnover of skill requirements, in contrast to slower-changing occupations, such as teaching, carpentry and several elementary trades.
Rui Costa, Zhaolu Liu, Sandra McNally, Louise Murphy, Christopher Pissarides, Bertha Rohenkohl, Anna Valero & Guglielmo Ventura
In this joint report with the Economy 2030 Inquiry - also funded by the Nuffield Foundation - and the Centre for Economic Performance, we examine how best to situate skills in an economic strategy.
Jiyuan Zheng, Bertha Rohenkohl, Mauricio Barahona, Jonathan M Clarke
The personal well-being of workers may be influenced by the risk of job automation brought about by technological innovation. Here we use data from the Understanding Society survey in the UK and a fixed-effects model to examine associations between working in a highly automatable job and life and job satisfaction. We find that employees in highly automatable jobs report significantly lower job satisfaction, a result that holds across demographic groups categorised by gender, age and education, with higher negative association among men, higher degree holders and younger workers. On the other hand, life satisfaction of workers is not generally associated with the risk of job automation, a result that persists among groups disaggregated by gender and education, but with age differences, since the life satisfaction of workers aged 30 to 49 is negatively associated with job automation risk. Our analysis also reveals differences in these associations across UK industries and regions.
Bertha Rohenkohl and Jonathan M Clarke
Automation technologies are reshaping work, which has complex impacts on the wellbeing of workers. In this paper we review the literature on the impact of automation technologies on subjective wellbeing. We explore automation risk, the expectations of automation and technology adoption, and analyse their effects on job and life satisfaction. While negative consequences of automation are commonly studied, our review uncovers potential for both positive and negative effects on wellbeing.
