This paper sheds light on the extent to which different types of skills are rewarded as industries go digital. It relies on information from the OECD Survey of Adult Skills on labour market participation and workers' skills for 31 countries as well as on a novel OECD index on the digital penetration of industries. It investigates how cognitive and non-cognitive skills are rewarded in digital vs. less digital intensive industries and assesses the extent to which skills bundles matter. The results indicate that digital intensive industries especially reward workers having relatively higher levels of self-organisation and advanced numeracy skills. Moreover, for workers in digital intensive industries, bundles of skills are particularly important: workers endowed with a high level of numeracy skills receive an additional wage premium, if they also show high levels of self-organisation or managing and communication skills.
This report asks what is happening to middle-skill workers. Driven by mega trends such as automation, ageing and offshoring, the share of jobs whose wages placed them firmly in the middle of the wage distribution has been declining. Termed job polarisation, economists have observed the decline in the share of middle-skill jobs in the majority of OECD labour markets. One little explored question is where are these workers going? This report examines what workers are doing who in the past would have been employed in middle-skill jobs. The report first examines the traits of previous middle-skill workers to build a picture of the 'typical' middle-skill worker. Using this profile, the report next examines what types of jobs a worker with the typical middle-skill profile is taking, and how likely such a worker is to be working. The study then analyses different metrics of job stability and compensation to put in perspective what shifts out of middle-skill work imply for labour market outcomes.
What are the policy options?: A systematic review of policy responses to the impacts of robotisation and automation on the labour market
Three main policy responses to the labour market challenges posed by robotisation and automation have emerged in the research literature. The first is 'taxing robots' and using this revenue to introduce a basic income that could offset the negative impacts of replacing humans by robots. The second option highlights the ownership of robots so that taking part in the new source of wealth is possible. The third focuses on strengthening the comparative advantages, the creativity, and the social intelligence of humans that robots will never be able to match. All of these policy responses are supported by economic rationales and research findings, but a systematic review shows that all of them raise further questions and challenges that should be carefully investigated in order to choose the right path. This paper offers a comprehensive overview of these questions. Furthermore, in a broader sense these policy options - redistributing the benefits of technological changes, increasing accesses to the benefits and utilisation of changes, and supporting the individual and institutional adjustment to changes - are relevant to every technological transformation. Hence, the lessons that are drawn from the current discussion of policy options driven by specific technologies, robotization, and automation might serve as a precursor to potential policy responses triggered by other technologies.
This paper analyses the effect of the economic crisis in 2008 and 2009 on individual training activities of different employee groups within establishments. We use a unique German linked employer-employee panel data set with detailed information on individual training history (WeLL-ADIAB). The so-called Great Recession can be seen as an exogenous, unexpected, and time-limited shock. Therefore, our quasi-experimental setting using Diff-in-Diff analyses reveals the causal impact of the crisis on the training participation and the number of training measures. We find a direct negative effect of the crisis on individual training activities in 2009 and 2010. The negative effect therefore sets in with a time lag and lasts until after the recession. Furthermore, the recession effect is stronger for employees in unskilled jobs than for employees in skilled jobs.
A variety of researchers and public entities have estimated the prevalence of nontraditional work arrangements, using diverse definitions, in recent decades, and the topic has received increasing attention in the past five years. Despite numerous media reports that the prevalence of nonstandard work has increased since the Great Recession, not all sources agree on this point, and very little evidence exists relating to hours or earnings from such arrangements and their changes over time. Using unique data from the Survey of Informal Work Participation (SIWP), we describe changes in informal work activity across 2015, 2016, and 2017 along multiple dimensions and for a variety of specific jobs. Considering the net changes observed between 2015 and 2017, we find that participation rates and earnings were mostly flat across the period, while average hours for gig workers declined by economically and statistically significant margins. The aggregate number of full-time equivalent jobs embodied in informal work, a measure combining participation rates and hours, also declined by an economically significant margin between 2015 and 2017. A major exception to these trends is that average ridesharing hours more than quadrupled between 2015 and 2017. We find some evidence that the recent declines in informal work hours represented a response to declining unemployment rates, but during this time period there also appears to have been upward structural pressure on gig work that provided a particular boost to platform-based work.
New digital technologies more and more diffuse into the economy. Due to this digitisation, machines become increasingly able to perform tasks that previously only humans could to. Production processes and organizations are changing, new products, services and business models emerge. These trends have important implications for European labour markets. This working paper presents up-to date evidence on the consequences of technological innovations on labour markets based on the academic literature and discusses the resulting policy challenges along with examples of policy responses. One key finding is that so far recent technological change has had little effect on the aggregate number of jobs but leads to significant restructuring of jobs. This implies three key challenges for European labour markets: first, digitisation induces shifts in skill requirements, and workers’ fate in changing labour markets crucially depends on their ability to keep up with the change. Secondly, digitisation is not a purely technological process, but requires an accompanying process of organisational change. Thirdly, digitisation comes along with rising shares of alternative work arrangements, due to more outsourcing, standardisation, fragmentation, and online platforms. These alternative work arrangements imply both new opportunities and challenges. These challenges require adequate policy responses at the European, national and regional level, which the working paper outlines for education and training policies, active labour market policies, income policies, tax systems and technology policies.
This paper studies the impact of labor market conditions during the education-to-work transition on workers' long-term skill development. Using representative survey data on measures of work-relevant cognitive skills for adults from 19 countries, I document four main findings: (1) cohorts of workers who faced higher unemployment rates at ages 18-25 have lower skills at ages 36-59; (2) unemployment rates faced at later ages (26-35) do not have such an effect; (3) the former findings hold even though, on average, people get more formal education as a response to higher unemployment in their late teens and early twenties; and (4) skill inequality is affected: workers whose parents were less educated bear most of the negative effects. These findings can be rationalized by on-the-job learning during the early twenties being an important factor of skill development, and such learning being negatively impacted by bad macroeconomic conditions. Using German panel data on skills, I show that young workers at large firms experience higher skill growth than those at small firms. This finding suggests firm heterogeneity in human capital provision to young workers as a potential mechanism since, in bad economic times, young workers disproportionately match with small firms.
An enormous amount of literature has emerged over the last few years in the context of the 'future of work'. However, despite a growing body of research in this area, there exists no universally accepted definition of what exactly the 'future of work' encompasses and what the most relevant drivers are. Accordingly, there is a vast variety of themes and methods covered by the literature on the future of work. Few papers cut across a multidimensional analysis of the different potential drivers of change. This literature review provides a systematic and synoptic overview of topics discussed under the umbrella of the 'future of work'. It not only highlights the trends of the most important drivers as discussed in existing studies, it also defines what the expected outcomes of the future of work might be. The review first devises a structure based on key labour market dimensions and then categorises findings from the literature conditioned on such dimensions. It also contains an assessment on the coverage of the studies on the future of work and perceived limitations and thematic gaps.