3. The impact of the future of work on Berlin’s labour market

Across the OECD, megatrends such as digitalisation, automation and artificial intelligence (AI) are contributing to one of the most profound transformation of local labour markets in decades. As elsewhere, these trends will have a strong and lasting impact on Berlin’s labour market. While the effects of these trends are already in motion, the COVID-19 pandemic is accelerating digitalisation and automation. With social distancing rules in place, millions of workers have adopted teleworking. It seems likely that a non-negligible degree of teleworking or hybrid working arrangements might prevail beyond the pandemic. Thus, COVID-19 appears to be a catalyst for long-lasting change in the way firms operate and people work as they embrace technological change to find innovative solutions that allow them to work.

Against this backdrop, the changing future of work will come with greater risks for some people and sectors in Berlin than for others. The pandemic has been exacerbating pre-existing structural issues within Berlin’s labour market, such as skills gaps, skills imbalances and a polarisation into well-paying and precarious jobs. Sound adult learning and skills development strategies are an essential policy tool that can help address these issues and can ensure that Berlin is prepared for the future of work, and the new types of jobs and alternative work arrangements such as part-time work that are on the rise.

In managing the economic consequences of the crisis and the subsequent recovery, policy makers in Berlin need to provide new solutions. For a strong and sustainable economic recovery, those solutions need to not only address the direct economic effects of the pandemic but also address structural labour market challenges. In analysing these trends and challenges, this chapter has the following structure. First, it examines the impact of automation on Berlin’s local labour market. Second, it describes how job polarisation affects the availability of different types of jobs. Finally, it shows trends in the growth of non-standard work, which creates both opportunities and new challenges for individuals.

Labour markets in OECD countries have undergone significant structural changes over recent decades. Driven by new technologies, products and consumption patterns, a range of new types of jobs have emerged. On the flipside, employment in some traditional industries has declined. As a result, the type of skills that firms seek and workers need to thrive professionally has changed. Global megatrends such as automation and digitalisation that have accelerated during the COVID-19 pandemic will further drive this structural transformation of the economy, leading to a significantly different future of work. The pandemic being a catalyst for change, as firms and employees have embraced new ways of working and collaborating, ranging from sudden rise in remote working to a significant uptake of digital technology and services. These developments, especially since they are likely to continue at least partly, will have a considerable impact on how people work as well as what type of skills they need to have.

Automation will cause one of the most significant transformation of labour markets in OECD countries in decades. On the one hand, the automation of production processes offers new opportunities and enhances productivity, thus raising prosperity and living standards. On the other hand, it poses new and unequal risks to workers because it is a skills-biased technological change. It tends to benefit some workers (mainly high-skill) but potentially replaces or strongly changes the jobs of other workers (mainly low-skill or middle-skill). Automation will result in a replacement of certain tasks and jobs, creating a risk that some workers may not enjoy the benefits that automation can generate but instead might struggle to find new jobs given the changing labour market and skill needs (OECD, 2018[1]). Consequently, automation could aggravate existing socio-economic inequalities by leading to lower wages for some jobs and further job polarisation across types of skills (Acemoglu and Autor, 2011[2]).

Across the OECD, about 46% of jobs face risks of automation. Around 14% of jobs are highly automatable (i.e. face a probability of automation of over 70%). Another 32% of jobs face a significant risk of being strongly affected by automation, which means they are likely to see significant change in their tasks and the required skill sets for such tasks. On average, automation tends to have smaller metropolitan areas in the OECD due to their stronger focus on service-sector jobs. However, several metropolitan areas in Spain, Italy, or Germany, face an even higher automation risk to jobs than the OECD average (Figure 3.1).

The risk of job automation affects almost every second job in Berlin. Compared to other major OECD metropolitan areas, Berlin faces relatively high risks of automation (Figure 3.1). In total, 14% of jobs in Berlin are highly automatable and a further 33% are likely to be changed significantly by automation (see Box 3.1 for a detailed explanation of the computation of risks of automation). Among peer metropolitan areas, only Barcelona, Madrid, Milan and Hamburg record a higher share of jobs that are likely to be automated or significantly transformed. At the other end of the spectrum, the labour markets in Oslo and London appear more resilient with respect to the impact of automation, which will only affect around 28% and 29% of jobs respectively.

Across German states, Berlin records the lowest share of jobs at risk of automation. In Berlin, the share of jobs at high risk of automation and the share of jobs that will be significantly changed are both lower than in any other German state (Figure 3.2). However, they are still above the OECD average. Jobs in Thüringen and Mecklenburg-Vorpommern face the highest risks of automation, with more than 50% of jobs facing either high automation risk or risk of significant change. Overall, automation risks are greater in German states than in the OECD, partly due to the greater share of jobs in manufacturing in Germany.

The occupational profile of local labour markets help explain why the risk of automation differs within Germany and across OECD metropolitan areas. Occupational differences mainly reflect different industrial structures of regions or metropolitan areas. For example, sectors such as agriculture, construction, food and beverage services, manufacturing, or transport have a higher probability of losing jobs to automation (Box 3.1). German regions that face a higher risk of automation than Berlin tend to rely more strongly on employment in such sectors. Almost 60% of employees in Berlin work in a sector with low automation risks, whereas only around 38% work in high-risk sectors (Figure 3.3). In contrast, in Thüringen, the share of employees in industries with high automation risks amounts to 25%, while only 40% of employees work in industries with low automation risks. Employees in Berlin face lower risks of automation because many work in occupations and industries that involver fewer routine tasks, including jobs in professional and scientific services, finance, or real estate.

Promisingly, the bulk of recent job creation in Berlin has mostly taken place in occupations with a low to medium risk of automation. Since 2011, the vast majority of new jobs appeared in high skill occupations that are less vulnerable to automation (Figure 3.4). For example, the number of jobs for information and communication technology professionals increased by around 70 000. Similarly, Berlin’s economy created 55 000 jobs for teaching professionals, which consist of occupations that are not only high skilled but also face a relatively low risk of automation. Encouragingly, those low skill occupations that are more robust in light of automation, such as personal service workers, fared better than low skill occupations that are highly vulnerable. The recent patterns of job creation help reduce the exposure of Berlin’s labour to the risk of automation. However, the data on job creation also reveal that the opportunities for the low skilled are shrinking, as little to no growth in employment occurred in occupations that provide employment for people with low levels of educations.

Automation and digitalisation make digital skills ever more relevant in Berlin. Digital skills are essential for people to maximise their opportunities, work efficiently in a job; and are crucial for ensuring productivity and growth in Berlin. Digital skills are particularly important for those groups that are most at risk of redundancy because new jobs increasingly require basic or advanced digital skills and the ability to work in a technology-rich environment. To enhance employability of vulnerable groups in the labour market, Berlin could look at interesting local initiatives such as the Local Digital Skills Partnership in Lancashire in the UK that aim to equip workers with highly sought after digital skills in close collaboration with the local business community (Box 3.3).

Even before the COVID-19 pandemic started, most OECD economies experienced dramatic shifts in their labour markets. Over the last decades, labour markets across the OECD have become increasingly polarised. The share of employment in middle-skill jobs has declined strongly relative to jobs with higher or lower skill levels (OECD, 2017[8]). High-skill jobs include managers, professionals and technicians; middle-skill jobs compose clerks, craft and related trades workers, machine operators and assemblers; and low-skill jobs include elementary occupations, service workers, and shop and market sales workers. In almost all OECD countries, job polarisation has been characterised primarily by a shift towards high-skill occupations (OECD, 2019[9]).

Job polarisation is not only part of labour market transformations but also poses a social challenge in OECD societies. It raises public concern about growing inequality in OECD countries. Middle-skill jobs were historically associated with a middle-class lifestyle and socio-economic mobility for future generations. In recent years, however, the overall skill distribution on the labour market has shifted towards higher-skill jobs as growth in high-skill occupations has outpaced growth in middle- and low-skill occupations, which has changed the relationship between skills and income classes. Consequently, middle-skill workers are now more likely to be in lower-income classes than middle-income classes (OECD, 2019[9]). Furthermore, the wage structure in many OECD countries is now also showing a growing divide between top earners and others, instead of experiencing growth at both ends of the wage structure.

Skills-biased technological change has been driving a labour market polarisation across the OECD. This is particularly noticeable in large cities, which tend to be at the forefront of labour market transformations. Across OECD metropolitan areas, labour markets are increasingly polarising into high and low skilled jobs. In contrast, middle-skill jobs are rapidly disappearing in many places. All the 17 OECD metropolitan areas considered, including Berlin, have lost middle-skill jobs in relative terms since 2000 (Figure 3.6). On average, the share of workers in such jobs decreased by more than 7 percentage points between 2000 and 2018. Most of those metropolitan areas have replaced middle-skill jobs with both high-skill and low-skill jobs, with the former recording the largest relative increase in jobs. In fact, 16 metropolitan areas have mostly replaced middle-skill jobs with high-skill jobs.

Compared to other OECD metropolitan areas, middle-skilled jobs disappeared at a lower rate in Berlin. Since 2000, the share of middle-skilled jobs fell by 2.7 percentage points (Figure 3.6). A significant rise in high-skilled jobs (+ 4.9 percentage points) more than compensated for the loss in middle-skilled jobs. Contrary to most comparable OECD metropolitan areas, Berlin did not experience a simultaneous increase in the share of low-skilled jobs. Instead, the share of low-skilled jobs fell by 2.2 percentage points. In summary, Berlin’s labour market has experienced a shift towards high-skilled jobs, with both middle-skilled and low-skilled jobs falling at similar rates.1

The green transition to a low-carbon economy is another major development that will shape labour markets over the coming decades. Reaching the political objective of reducing emissions and achieving a net-zero economy, requires decisive actions by many countries around the world. Those actions, which include the phasing out of fossil fuels and a move towards renewable energies, will inevitably also affect the labour market. Jobs and sectors that support the green transition could thrive, while others that are emission-intensive such as the chemical industry or parts of manufacturing could see job losses or at least a significant structural transformation.

The opportunities and challenges that the green transition brings will differ vastly across local labour markets. Due to differences in their economic structure and the share of jobs across sectors, some local labour markets will face significant risks while others could benefit from growing green sectors. Currently, a lack of clear empirical evidence on green jobs and skills across local areas hampers the assessment of where the green transition might create new economic opportunities other than in the renewable energy sector. However, by looking at a subset of jobs that are emission-intensive, one can assess the extent to which jobs across OECD regions might be put at risk by a move towards net-zero economy.

In Berlin, employment risks due to the net-zero transition appear low. Figure 3.7 presents data on the share of jobs in four manufacturing sectors that entail, on average, high levels of emissions. Those sectors are transport, coal and other mining, chemical and plastic products, and other manufacturing. In Berlin, these sectors only account for around 0.8% of total employment, the lowest share across all German federal states. Similarly, the share of employment in those sectors is much lower that the OECD average of 2.2%. In the extent to which those jobs could be classified as “brown jobs” that face heightened risk from the move to a net-zero economy, Berlin’s labour market seems relatively well-shielded. The relevant dominance of the service sector in Berlin’s economy provides further protection against adverse shocks from the green transition, as the major impact is likely to be on manufacturing jobs. Looking a step further, the green transition could in fact provide new economic opportunities for Berlin supported by its young workforce and dynamic entrepreneurship scene.

The transformation of the world of work changes the skills firms need. As a result, it could create a discrepancy between the demand for skills and its supply, which is based on the education and the qualifications of the labour force. Since skills and their effective use are a fundamental driver of economic development and productivity, rising skills mismatches and gaps could harm Berlin’s economic prosperity and growth. Across the OECD, skills gaps help explain a significant share of cross-country variation in labour productivity (Adalet McGowan and Andrews, 2017[12]). Industry-level analysis shows that firms in industries with higher skills mismatches tend to have a lower labour productivity performance (Adalet McGowan and Andrews, 2015[13]). Crucially, skills also matter for resilience, as they allow workers to be more flexible in reacting to changing labour markets and economic crises.

The matching of workers to jobs in which they can utilise their skills in the best possible way is a vital element of functioning labour markets. To the contrary, mismatches between workers’ skills and the requirements of their jobs can have negative effects, ranging from lower job satisfaction, wages, and labour productivity to unused potential of human capital (OECD, 2018[1]). Mismatch by qualification is one source of such skills mismatches. It arises when workers’ educational attainment is above (over-qualification) or below (under-qualification) the level usually required by the tasks of their job.

Skills mismatches by qualification are widespread in Berlin. Around 41% of all workers in Berlin have a job that does not correspond to their level of qualification (Figure 3.8). Twenty-two percent of workers in Berlin have a job for which they are formally overqualified. Another 19% appear to be underqualified for their job, meaning they do not have the skills and qualifications normally expected to fill out their position. Compared to selected large and economically important OECD metropolitan areas, Berlin records the second highest (out of 13) degree of skills mismatch by qualification, pointing out the strong disconnect between labour supply and demand in the local economy. This is particularly true for the over-qualification of workers, i.e. people working below their educational attainment, which exceeds the OECD and EU averages of 17% and 13% significantly.

Skills gaps and mismatches already inhibit Berlin’s economy. With the rapidly changing demand for new skills and the emergence of new types of jobs, the problem could become more severe if it is not addressed. Therefore, it is more important than ever to have a robust adult education and training system that provides on- and off-ramps for all individuals and firms to participate. Such a system will allow workers to gain new skills, retrain, or extend existing skills in bringing them up-to-date with recent developments. An important prerequisite for dealing with and alleviating skills gaps and mismatches consists of collecting sound data on the local labour market. A number of publicly available tools provide such data that policy makers can use to track regional labour demand, which helps design effective policy (Figure 3.5).

Many labour markets across the OECD have undergone a gradual transition away from traditional open-ended contracts. Non-standard forms of work, which include temporary, part-time, or self-employed work, have been rising (see Box 3.6 for information on the definition of non-standard work). Changing consumer preferences and new technological developments are two important factors explaining the increase in non-standard work forms. The latter allows firms to adopt more job flexibility and outsourcing of tasks, including the hiring of temporary help or freelance contractors. The former, have caused a shift among firms to more just-in-time delivery and customised services.

Non-standard work brings new opportunities as well as challenges for local labour markets. It offers opportunities to find employment or increase flexibility for some workers but it also worsens working conditions for others. On the one hand, non-standard work arrangements can enhance the compatibility of work and family life and increase worker flexibility more generally. Thus, it can encourage labour force participation, especially among those who would otherwise have stayed out of the labour market. For instance, it can help women to combine professional and personal responsibilities. Moreover, it can facilitate school-to-work transitions by providing a stepping-stone for young people (OECD, 2018[14]). However, on the other hand, non-standard work is often associated with worse working conditions in terms of reduced job security, higher income volatility, and slower career progression.

Non-standard work employment has increased in most OECD countries since 2000. Temporary contracts have become more common in OECD countries, especially among young workers (Figure 3.9 Panel A). Compared to 1980, the share of OECD workers under the age of 26 in a fixed-term contract has risen from 17% to 25% in 2016. Moreover, the share of employees in part-time work has also increased significantly (Figure 3.9 Panel B). While a large part of this trend is due to the entry of women into the labour market that historically struggled to combine family and professional life, part-time work has also increased amongst men.

In Berlin, part-time employment has grown at a similar pace as Germany overall. In 2019, around 26% of employment in was part time, an increase of 6 percentage points from 2002 (Figure 3.10). In Germany overall, a slightly higher share of total employment, 27%, is part time. Compared to the EU27 countries, part-time employment in Berlin and Germany is relatively high. On average, 18% of 16 to 64 year olds have a part-time job in the EU27. A number of reasons could help explain this difference. For example, women make up a large share of part-time employees. As such, part-time employment can be a means of ensuring a work-life balance and making family and professional life compatible. In countries such as the Netherlands, Switzerland, Germany, the United Kingdom or Norway, women’s increased labour market participation partly explains the rise in part-time employment, with women being more than twice as likely as men to work part time and on average, almost one quarter of women – often mothers – work part-time (OECD, 2020[16]). However, part-time employment often comes with disadvantages too.

Part-time employees face higher job security and tend to earn lower hourly wages in OECD countries (OECD, 2018[17]). Poverty rates tend to be higher for part-time workers than for standard employees. While on average 10% of part-time workers live in a household with an annual disposable income of less than 50% of the national median, this is only the case for 3% of standard employees (OECD, 2020[16]). Furthermore, part-time workers are less likely to participate in training, which has a negative impact on their future earnings. Lower training participation also means that part-time workers are less likely to adapt to the future of work and changing skills requirement. As pointed out in the previous section, automation and digitalisation change labour market needs and skill profiles that employers seek. Part-time workers are less able to react to these developments by using learning opportunities to retrain or upskill.

Another dimension of non-standard work is self-employment, which has been increasing significantly in Berlin. More than 13% of all workers in Berlin are self-employed, making it the federal state in Germany with the highest rate of self-employment (Figure 3.11). Self-employment is not only much more common in Berlin than elsewhere in Germany but also grown over the past 15 years, while it fell in Germany overall. The share of self-employed workers grew from around 11.7% to 13.4% between 2004 and 2019 in Berlin, whereas it decreased from 9.8% to 8.5% nationally. As of 2019, the proportion of self-employment among workers in Berlin was similar to the average of the EU27 countries. However, contrary to the development in Berlin’s economy, the EU27 self-employment rate markedly decreased from 2004 to 2019. One factor that contributes to the rise of self-employment in Berlin is the emergence of the digital economy. Some self-employed workers in the digital economy have been able to benefit from new markets and opportunities by finding high-value added work as independent professionals or freelancers. However, for others, self-employment in the digital economy takes on precarious forms, as some work for a single client that is effectively their employer, without having the benefits of a formal employer-employee relationship including social security or work regulation that protects employees.

During the COVID-19 pandemic, Berlin has experienced a surge in demand for digital skills. The shift to teleworking has led to the adoption of new technology and a proliferation of technological solutions to work elements such as meetings that were limited by social distancing measures. This push, which has forced firms and workers to experiment with new working arrangements and embrace virtual approaches to some of their tasks, is likely to have a lasting impact. It has emphasised the relevance of being able to work in a digital environment and has thus increased the demand for digital skills.

Berlin has recorded a significant jump in new jobs that require advanced information and communications technology (ICT) skills. From the start of the pandemic until the end of 2020, the share of job postings in Berlin that require advanced ICT skills rose from 26% to 33% (Figure 3.12). Such jobs entail specialised skills such as programming, coding and data analysis (see Box 3.7 for more details). While many German cities saw a rising demand for ICT skills during the pandemic, it rose particularly fast in Berlin, suggesting that Berlin might be experiencing a faster transformation of its local economy than other places in Germany. Looking at the requirements of job postings offers a timely alternative to measuring labour demand and the changing skills mix in Berlin’s economy.

Contrary to advanced digital skills such as programming or data analysis, demand for more basic digital skills has not risen. Not all digital skills recorded significant increases in demand as firms and employees had to embrace digital ways of working. Demand for generic digital skills that encompass simple ICT skills, for instance referring to knowledge of “MS Excel”, remained mostly constant (Figure 3.13). In fact, their relative importance has fallen since 2015, which probably indicates that such skills are increasingly taking for granted. They appear to become a minimum work requirement for many jobs in Berlin.

Comprehensive data on digital skills among Berlin’s workforce are missing but alternative measures can provide an approximation. Ideally, extensive surveys of adult workers or firms could highlight the extent to which individuals have the necessary digital skills to succeed in the local economy. However, most of those data sources are either not representative at the subnational level (e.g. the OECD Programme for the International Assessment of Adult Competencies (PIAAC) or do not offer systematic evidence on digital skills gaps as in the case of employer surveys that cover Berlin. To approximate basic digital skills, regular internet use might offer an alternative. In Berlin, as in other OECD metropolitan areas, internet use has not only risen over the past decade but has become ubiquitous in most people’s lives (Figure 3.14).

While most people in Berlin use the internet regularly, almost half of Berlin’s population does not perform basic tasks online. In comparison to other OECD metropolitan areas such as Oslo, London, Brussels or Hamburg, many more people in Berlin do not appear to use social networks, buy or sell goods online, or use online banking. While there could be several factors at play for those differences, the data might also suggest that many individuals in Berlin could lack the necessary familiarity and experience in pursuing tasks online. This, in turn, could indicate a lack of digital skills that goes beyond the minimal competency of simply using the internet for minimal tasks such as browsing or search queries. In a broader sense, such data appear to corroborate the widespread views expressed by employers in Berlin that many workers or job seekers do not meet the requirements in terms of digital skills that many jobs entail.


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← 1. Technological change is a major reason for the disappearance of middle-skilled jobs. Information and Communication Technology (ICT) mainly offers a substitute for middle-skill jobs. Thus, technological developments and their capacity to replace routine tasks are drivers of job polarisation, as the impact of technology on jobs varies across the skills distribution. Across industries, occupations, and education levels, digitalisation is linked with reduced labour input of routine manual and routine cognitive tasks. Meanwhile, technological change and digitalisation are associated with an increase in non-routine cognitive tasks (Autor, Levy and Murnane, 2003[24]). As middle-skill jobs, such as clerical and production jobs, often entail routine tasks, they are easier to automate. In contrast, low-skill jobs often also involve non-routine manual tasks, which are more difficult to automate.

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