Labour-market data from online sources can identify emerging occupations and skill demand, helping policymakers prepare better for future needs.
One in four Europeans worries about the difficulties of learning new digital skills. These insecurities on the supply side of the labour market are reflected on the demand side: more than half of European Union companies struggled to fill job vacancies for ICT specialists in 2019. To a great extent, technological change drives this growing cleavage between the skills people have and the skills sought by employers.
Technological change is not ‘skill-neutral’. New technologies, including for data management, digital design and autonomous systems, favour certain new skills while making others redundant or devaluing them. In addition, for many newly emerging jobs, precise skill requirements are evolving and are therefore unclear. Innovation will create jobs in the future but they will involve entirely new tasks.
The skill gap means there is simultaneous unemployment and labour shortage. Figure 1 shows the relationship between unemployment and job vacancy rates (known as the Beveridge curve) since 2008. It shows that during economic contractions, job vacancy rates decrease and unemployment rises – for example, from 2008 to 2010 as a result of the global financial crisis and the beginning of the euro-area crisis.
Figure 1: In the EU from 2008-2021, job vacancy rates increased and unemployment rates declined
Source: Bruegel based on Eurostat.
In times of skill mismatches or increased job-search intensity, however, upward shifts in the curve can occur, when unemployment rises while the share of unfilled vacancies remains the same. This happened between 2009 and 2013 (Figure 1), but thereafter job vacancy rates increased and unemployment rates declined. Another large shift seems to have occurred in 2020, when vacancies rose but the unemployment rate didn’t change. Currently, vacancy rates are much higher than ten years ago, with a slightly lower level of unemployment, indicating that, despite economic recovery, many firms are not able to fill their job vacancies. Some of this can be attributed to labour market reshuffling caused by the COVID-19 pandemic, but it is nevertheless reasonable to assume that sustained skill mismatches have also contributed to a rise in vacancy rates in the EU. Findings from the United States show that occupational mismatch has become one of the main reasons for unemployment there too.
Skills of the future
In this fast-changing labour market, it is crucial to know for which skills there will be a sustainable demand in the future, and how to acquire those skills. The conventional policy response is to align training programmes with changing labour-market demand, but this is increasingly ineffective as technological and social transformation outpaces national training systems.
Large employers are also struggling to keep their workforces’ skills up to date. In addition, COVID-19 tightened company budgets, forced employees to work remotely and further drove the global need for reskilling. Workers have begun to assume greater personal responsibility for their reskilling via online courses, distance education tools and entrepreneurial approaches to work. In the absence of institutional support, independent professionals today develop new skills incrementally, adding closely related skills to their existing knowledge.
Online labour platforms – global marketplaces that match millions of buyers and sellers of digitally delivered work in various occupational domains – are a source of data for research on how workers develop new skills. Other sources of online generated data are also becoming increasingly important for the study of skill development. Information from job vacancy portals, such as Indeed or Glassdoor, or professional social networks like LinkedIn, could be used to inform skill development and predict the emergence of novel occupational domains. These data sources have different advantages and shortcomings in terms of informing research into skills development (Table 1).
Online job vacancy notices cover a large segment of the labour market, including many industry sectors and also non-digital and manual work. However, they seldom include information on price levels and give no indication on the possible supply in the targeted population. Data from professional social media sites, such as LinkedIn, on the other hand, can enable in-depth analysis of skill compositions in the population. However, no price or income information is revealed, and matching efficiencies can’t be evaluated in the absence of demand-side data.
Online labour market data from platforms including UpWork and Fiverr covers only a small segment of the labour market: digitised tasks from jobs in the professional service sector. However, the professional service sector is the largest and fastest growing segment of the European Union labour market. These properties make online labour markets a particularly valuable data source for studying skill formation, skill matching, and the evaluation of individual skills or skill bundles.
Public-interest data-access policies
The European Commission has recognised the need for, and potential of, a data-driven approach in closing the skill gap. The Commission’s 2020 Pact for Skills, for example, aimed to maximise the impact and effectiveness of skills investment, with a particular focus on upskilling and reskilling in the vocational training sector. To implement the Pact successfully, two aspects are crucial. First, industry’s specific skill needs must be made explicit. Second, the unique training history of workers needs to be acknowledged.
Online generated data can help update occupational taxonomies and understand the skill requirements of new jobs. This is aligned with Europe’s interest in developing skill foresight and support for career transitions. The approach can offer targeted and near-real time reskilling advice to workers, on both industry needs and the worker skills required to meet them, and could support the Commission’s proposals for recommendations on individual learning accounts and more flexible certification of competences developed through short courses or training programmes (so-called micro-credentials).
The Commission identified the importance and the difficulties of accessing business (and platform) data in the public interest, while acknowledging the protection of businesses’ interests, in the February 2022 proposal for a Data Act. However, the act would not necessarily enable retrieval and usage by public bodies of private-sector data, including online labour market and job vacancy data. Enforced sharing of private-sector data would require ex-ante proof of a “public emergency”, and the Data Act would prohibit current modes of automated data retrieval, such as web-scraping, if such activity was considered coercive or deceptive. Amendments to the proposed act should push for the right for public bodies acting in the interest to access data (including via web-scraping). This would benefit not only assessment of the digital skills gap, but also work on other societal challenges, including gentrification and polarisation via social media.